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1 NAME
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2 SimilaritySearchingFingerprints.pl - Perform similarity search using
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3 fingerprints strings data in SD, FP and CSV/TSV text file(s)
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4
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5 SYNOPSIS
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6 SimilaritySearchingFingerprints.pl ReferenceFPFile DatabaseFPFile
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7
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8 SimilaritySearchingFingerprints.pl [--alpha *number*] [--beta *number*]
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9 [-b, --BitVectorComparisonMode *TanimotoSimilarity | TverskySimilarity |
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10 ...*] [--DatabaseColMode *ColNum | ColLabel*] [--DatabaseCompoundIDCol
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11 *col number | col name*] [--DatabaseCompoundIDPrefix *text*]
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12 [--DatabaseCompoundIDField *DataFieldName*] [--DatabaseCompoundIDMode
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13 *DataField | MolName | LabelPrefix | MolNameOrLabelPrefix*]
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14 [--DatabaseDataCols *"DataColNum1, DataColNum2,... " | DataColLabel1,
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15 DataCoLabel2,... "*] [--DatabaseDataColsMode *All | Specify |
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16 CompoundID*] [--DatabaseDataFields *"FieldLabel1, FieldLabel2,... "*]
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17 [--DatabaseDataFieldsMode *All | Common | Specify | CompoundID*]
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18 [--DatabaseFingerprintsCol *col number | col name*]
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19 [--DatabaseFingerprintsField *FieldLabel*] []--DistanceCutoff *number*]
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20 [-d, --detail *InfoLevel*] [-f, --fast] [--FingerprintsMode *AutoDetect
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21 | FingerprintsBitVectorString | FingerprintsVectorString*] [-g,
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22 --GroupFusionRule *Max, Mean, Median, Min, Sum, Euclidean*]
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23 [--GroupFusionApplyCutoff *Yes | No*] [-h, --help] [--InDelim *comma |
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24 semicolon*] [-k, --KNN *all | number*] [-m, --mode *IndividualReference
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25 | MultipleReferences*] [-n, --NumOfSimilarMolecules *number*]
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26 [--OutDelim *comma | tab | semicolon*] [--output *SD | text | both*]
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27 [-o, --overwrite] [-p, --PercentSimilarMolecules *number*] [--precision
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28 *number*] [-q, --quote *Yes | No*] [--ReferenceColMode *ColNum |
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29 ColLabel*] [--ReferenceCompoundIDCol *col number | col name*]
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30 [--ReferenceCompoundIDPrefix *text*] [--ReferenceCompoundIDField
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31 *DataFieldName*] [--ReferenceCompoundIDMode *DataField | MolName |
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32 LabelPrefix | MolNameOrLabelPrefix*] [--ReferenceFingerprintsCol *col
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33 number | col name*] [--ReferenceFingerprintsField *FieldLabel*] [-r,
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34 --root *RootName*] [-s, --SearchMode *SimilaritySearch |
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35 DissimilaritySearch*] [--SimilarCountMode *NumOfSimilar |
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36 PercentSimilar*] [--SimilarityCutoff *number*] [-v,
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37 --VectorComparisonMode *TanimotoSimilairy | ... | ManhattanDistance |
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38 ...*] [--VectorComparisonFormulism *AlgebraicForm | BinaryForm |
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39 SetTheoreticForm*] [-w, --WorkingDir dirname] ReferenceFingerprintsFile
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40 DatabaseFingerprintsFile
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41
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42 DESCRIPTION
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43 Perform molecular similarity search [ Ref 94-113 ] using fingerprint
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44 bit-vector or vector strings data in *SD, FP, or CSV/TSV text* files
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45 corresponding to *ReferenceFingerprintsFile* and
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46 *DatabaseFingerprintsFile*, and generate SD and CSV/TSV text file(s)
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47 containing database molecules which are similar to reference
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48 molecule(s). The reference molecules are also referred to as query or
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49 seed molecules and database molecules as target molecules in the
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50 literature.
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51
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52 The current release of MayaChemTools supports two types of similarity
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53 search modes: *IndividualReference or MultipleReferences*. For default
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54 value of *MultipleReferences* for -m, --mode option, reference molecules
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55 are considered as a set and -g, --GroupFusionRule is used to calculate
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56 similarity of a database molecule against reference molecules set. The
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57 group fusion rule is also referred to as data fusion of consensus
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58 scoring in the literature. However, for *IndividualReference* value of
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59 -m, --mode option, reference molecules are treated as individual
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60 molecules and each reference molecule is compared against a database
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61 molecule by itself to identify similar molecules.
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62
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63 The molecular dissimilarity search can also be performed using
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64 *DissimilaritySearch* value for -s, --SearchMode option. During
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65 dissimilarity search or usage of distance comparison coefficient in
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66 similarity similarity search, the meaning of fingerprints comparison
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67 value is automatically reversed as shown below:
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68
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69 SeachMode ComparisonCoefficient ResultsSort ComparisonValues
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70
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71 Similarity SimilarityCoefficient Descending Higher value imples
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72 high similarity
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73 Similarity DistanceCoefficient Ascending Lower value implies
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74 high similarity
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75
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76 Dissimilarity SimilarityCoefficient Ascending Lower value implies
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77 high dissimilarity
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78 Dissimilarity DistanceCoefficient Descending Higher value implies
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79 high dissimilarity
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80
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81 During *IndividualReference* value of -m, --Mode option for similarity
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82 search, fingerprints bit-vector or vector string of each reference
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83 molecule is compared with database molecules using specified similarity
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84 or distance coefficients to identify most similar molecules for each
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85 reference molecule. Based on value of --SimilarCountMode, up to --n,
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86 --NumOfSimilarMolecules or -p, --PercentSimilarMolecules at specified
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87 --SimilarityCutoff or --DistanceCutoff are identified for each reference
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88 molecule.
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89
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90 During *MultipleReferences* value -m, --mode option for similarity
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91 search, all reference molecules are considered as a set and -g,
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92 --GroupFusionRule is used to calculate similarity of a database molecule
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93 against reference molecules set either using all reference molecules or
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94 number of k-nearest neighbors (k-NN) to a database molecule specified
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95 using -k, --kNN. The fingerprints bit-vector or vector string of each
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96 reference molecule in a set is compared with a database molecule using a
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97 similarity or distance coefficient specified via -b,
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98 --BitVectorComparisonMode or -v, --VectorComparisonMode. The reference
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99 molecules whose comparison values with a database molecule fall outside
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100 specified --SimilarityCutoff or --DistanceCutoff are ignored during
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101 *Yes* value of --GroupFusionApplyCutoff. The specified -g,
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102 --GroupFusionRule is applied to -k, --kNN reference molecules to
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103 calculate final similarity value between a database molecule and
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104 reference molecules set.
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105
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106 The input fingerprints *SD, FP, or Text (CSV/TSV)* files for
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107 *ReferenceFingerprintsFile* and *DatabaseTextFile* must contain valid
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108 fingerprint bit-vector or vector strings data corresponding to same type
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109 of fingerprints.
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110
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111 The valid fingerprints *SDFile* extensions are *.sdf* and *.sd*. The
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112 valid fingerprints *FPFile* extensions are *.fpf* and *.fp*. The valid
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113 fingerprints *TextFile (CSV/TSV)* extensions are *.csv* and *.tsv* for
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114 comma/semicolon and tab delimited text files respectively. The --indelim
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115 option determines the format of *TextFile*. Any file which doesn't
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116 correspond to the format indicated by --indelim option is ignored.
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117
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118 Example of *FP* file containing fingerprints bit-vector string data:
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119
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120 #
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121 # Package = MayaChemTools 7.4
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122 # ReleaseDate = Oct 21, 2010
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123 #
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124 # TimeStamp = Mon Mar 7 15:14:01 2011
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125 #
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126 # FingerprintsStringType = FingerprintsBitVector
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127 #
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128 # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
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129 # Size = 1024
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130 # BitStringFormat = HexadecimalString
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131 # BitsOrder = Ascending
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132 #
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133 Cmpd1 9c8460989ec8a49913991a6603130b0a19e8051c89184414953800cc21510...
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134 Cmpd2 000000249400840040100042011001001980410c000000001010088001120...
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135 ... ...
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136 ... ..
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137
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138 Example of *FP* file containing fingerprints vector string data:
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139
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140 #
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141 # Package = MayaChemTools 7.4
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142 # ReleaseDate = Oct 21, 2010
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143 #
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144 # TimeStamp = Mon Mar 7 15:14:01 2011
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145 #
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146 # FingerprintsStringType = FingerprintsVector
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147 #
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148 # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
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149 # VectorStringFormat = IDsAndValuesString
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150 # VectorValuesType = NumericalValues
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151 #
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152 Cmpd1 338;C F N O C:C C:N C=O CC CF CN CO C:C:C C:C:N C:CC C:CF C:CN C:
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153 N:C C:NC CC:N CC=O CCC CCN CCO CNC NC=O O=CO C:C:C:C C:C:C:N C:C:CC...;
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154 33 1 2 5 21 2 2 12 1 3 3 20 2 10 2 2 1 2 2 2 8 2 5 1 1 1 19 2 8 2 2 2 2
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155 6 2 2 2 2 2 2 2 2 3 2 2 1 4 1 5 1 1 18 6 2 2 1 2 10 2 1 2 1 2 2 2 2 ...
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156 Cmpd2 103;C N O C=N C=O CC CN CO CC=O CCC CCN CCO CNC N=CN NC=O NCN O=C
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157 O C CC=O CCCC CCCN CCCO CCNC CNC=N CNC=O CNCN CCCC=O CCCCC CCCCN CC...;
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158 15 4 4 1 2 13 5 2 2 15 5 3 2 2 1 1 1 2 17 7 6 5 1 1 1 2 15 8 5 7 2 2 2 2
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159 1 2 1 1 3 15 7 6 8 3 4 4 3 2 2 1 2 3 14 2 4 7 4 4 4 4 1 1 1 2 1 1 1 ...
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160 ... ...
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161 ... ...
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162
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163 Example of *SD* file containing fingerprints bit-vector string data:
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164
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165 ... ...
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166 ... ...
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167 $$$$
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168 ... ...
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169 ... ...
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170 ... ...
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171 41 44 0 0 0 0 0 0 0 0999 V2000
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172 -3.3652 1.4499 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
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173 ... ...
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174 2 3 1 0 0 0 0
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175 ... ...
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176 M END
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177 > <CmpdID>
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178 Cmpd1
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179
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180 > <PathLengthFingerprints>
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181 FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLengt
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182 h1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a49913991a66
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183 03130b0a19e8051c89184414953800cc2151082844a201042800130860308e8204d4028
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184 00831048940e44281c00060449a5000ac80c894114e006321264401600846c050164462
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185 08190410805000304a10205b0100e04c0038ba0fad0209c0ca8b1200012268b61c0026a
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186 aa0660a11014a011d46
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187
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188 $$$$
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189 ... ...
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190 ... ...
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191
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192 Example of CSV *TextFile* containing fingerprints bit-vector string
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193 data:
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194
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195 "CompoundID","PathLengthFingerprints"
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196 "Cmpd1","FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes
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197 :MinLength1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a4
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198 9913991a6603130b0a19e8051c89184414953800cc2151082844a20104280013086030
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199 8e8204d402800831048940e44281c00060449a5000ac80c894114e006321264401..."
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200 ... ...
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201 ... ...
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202
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203 The current release of MayaChemTools supports the following types of
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204 fingerprint bit-vector and vector strings:
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205
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206 FingerprintsVector;AtomNeighborhoods:AtomicInvariantsAtomTypes:MinRadi
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207 us0:MaxRadius2;41;AlphaNumericalValues;ValuesString;NR0-C.X1.BO1.H3-AT
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208 C1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-ATC1 NR0-C.X
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209 1.BO1.H3-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-A
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210 TC1 NR0-C.X2.BO2.H2-ATC1:NR1-C.X2.BO2.H2-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2
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211 -C.X2.BO2.H2-ATC1:NR2-N.X3.BO3-ATC1:NR2-O.X1.BO1.H1-ATC1 NR0-C.X2.B...
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212
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213 FingerprintsVector;AtomTypesCount:AtomicInvariantsAtomTypes:ArbitraryS
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214 ize;10;NumericalValues;IDsAndValuesString;C.X1.BO1.H3 C.X2.BO2.H2 C.X2
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215 .BO3.H1 C.X3.BO3.H1 C.X3.BO4 F.X1.BO1 N.X2.BO2.H1 N.X3.BO3 O.X1.BO1.H1
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216 O.X1.BO2;2 4 14 3 10 1 1 1 3 2
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217
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218 FingerprintsVector;AtomTypesCount:SLogPAtomTypes:ArbitrarySize;16;Nume
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219 ricalValues;IDsAndValuesString;C1 C10 C11 C14 C18 C20 C21 C22 C5 CS F
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220 N11 N4 O10 O2 O9;5 1 1 1 14 4 2 1 2 2 1 1 1 1 3 1
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221
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222 FingerprintsVector;AtomTypesCount:SLogPAtomTypes:FixedSize;67;OrderedN
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223 umericalValues;IDsAndValuesString;C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C
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224 12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 CS N1 N
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225 2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 N13 N14 NS O1 O2 O3 O4 O5 O6 O7 O8
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226 O9 O10 O11 O12 OS F Cl Br I Hal P S1 S2 S3 Me1 Me2;5 0 0 0 2 0 0 0 0 1
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227 1 0 0 1 0 0 0 14 0 4 2 1 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0...
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228
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229 FingerprintsVector;EStateIndicies:ArbitrarySize;11;NumericalValues;IDs
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230 AndValuesString;SaaCH SaasC SaasN SdO SdssC SsCH3 SsF SsOH SssCH2 SssN
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231 H SsssCH;24.778 4.387 1.993 25.023 -1.435 3.975 14.006 29.759 -0.073 3
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232 .024 -2.270
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233
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234 FingerprintsVector;EStateIndicies:FixedSize;87;OrderedNumericalValues;
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235 ValuesString;0 0 0 0 0 0 0 3.975 0 -0.073 0 0 24.778 -2.270 0 0 -1.435
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236 4.387 0 0 0 0 0 0 3.024 0 0 0 0 0 0 0 1.993 0 29.759 25.023 0 0 0 0 1
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237 4.006 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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238 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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239
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240 FingerprintsVector;ExtendedConnectivity:AtomicInvariantsAtomTypes:Radi
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241 us2;60;AlphaNumericalValues;ValuesString;73555770 333564680 352413391
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242 666191900 1001270906 1371674323 1481469939 1977749791 2006158649 21414
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243 08799 49532520 64643108 79385615 96062769 273726379 564565671 85514103
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244 5 906706094 988546669 1018231313 1032696425 1197507444 1331250018 1338
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245 532734 1455473691 1607485225 1609687129 1631614296 1670251330 17303...
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246
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247 FingerprintsVector;ExtendedConnectivityCount:AtomicInvariantsAtomTypes
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248 :Radius2;60;NumericalValues;IDsAndValuesString;73555770 333564680 3524
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249 13391 666191900 1001270906 1371674323 1481469939 1977749791 2006158649
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250 2141408799 49532520 64643108 79385615 96062769 273726379 564565671...;
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251 3 2 1 1 14 1 2 10 4 3 1 1 1 1 2 1 2 1 1 1 2 3 1 1 2 1 3 3 8 2 2 2 6 2
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252 1 2 1 1 2 1 1 1 2 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1
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253
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254 FingerprintsBitVector;ExtendedConnectivityBits:AtomicInvariantsAtomTyp
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255 es:Radius2;1024;BinaryString;Ascending;0000000000000000000000000000100
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256 0000000001010000000110000011000000000000100000000000000000000000100001
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257 1000000110000000000000000000000000010011000000000000000000000000010000
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258 0000000000000000000000000010000000000000000001000000000000000000000000
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259 0000000000010000100001000000000000101000000000000000100000000000000...
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260
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261 FingerprintsVector;ExtendedConnectivity:FunctionalClassAtomTypes:Radiu
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262 s2;57;AlphaNumericalValues;ValuesString;24769214 508787397 850393286 8
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263 62102353 981185303 1231636850 1649386610 1941540674 263599683 32920567
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264 1 571109041 639579325 683993318 723853089 810600886 885767127 90326012
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265 7 958841485 981022393 1126908698 1152248391 1317567065 1421489994 1455
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266 632544 1557272891 1826413669 1983319256 2015750777 2029559552 20404...
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267
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268 FingerprintsVector;ExtendedConnectivity:EStateAtomTypes:Radius2;62;Alp
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269 haNumericalValues;ValuesString;25189973 528584866 662581668 671034184
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270 926543080 1347067490 1738510057 1759600920 2034425745 2097234755 21450
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271 44754 96779665 180364292 341712110 345278822 386540408 387387308 50430
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272 1706 617094135 771528807 957666640 997798220 1158349170 1291258082 134
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273 1138533 1395329837 1420277211 1479584608 1486476397 1487556246 1566...
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274
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275 FingerprintsBitVector;MACCSKeyBits;166;BinaryString;Ascending;00000000
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276 0000000000000000000000000000000001001000010010000000010010000000011100
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277 0100101010111100011011000100110110000011011110100110111111111111011111
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278 11111111111110111000
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279
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280 FingerprintsBitVector;MACCSKeyBits;322;BinaryString;Ascending;11101011
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281 1110011111100101111111000111101100110000000000000011100010000000000000
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282 0000000000000000000000000000000000000000000000101000000000000000000000
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283 0000000000000000000000000000000000000000000000000000000000000000000000
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284 0000000000000000000000000000000000000011000000000000000000000000000000
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285 0000000000000000000000000000000000000000
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286
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287 FingerprintsVector;MACCSKeyCount;166;OrderedNumericalValues;ValuesStri
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288 ng;0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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289 0 0 0 0 0 0 0 1 0 0 3 0 0 0 0 4 0 0 2 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0
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290 0 0 0 0 1 1 8 0 0 0 1 0 0 1 0 1 0 1 0 3 1 3 1 0 0 0 1 2 0 11 1 0 0 0
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291 5 0 0 1 2 0 1 1 0 0 0 0 0 1 1 0 1 1 1 1 0 4 0 0 1 1 0 4 6 1 1 1 2 1 1
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292 3 5 2 2 0 5 3 5 1 1 2 5 1 2 1 2 4 8 3 5 5 2 2 0 3 5 4 1
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293
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294 FingerprintsVector;MACCSKeyCount;322;OrderedNumericalValues;ValuesStri
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295 ng;14 8 2 0 2 0 4 4 2 1 4 0 0 2 5 10 5 2 1 0 0 2 0 5 13 3 28 5 5 3 0 0
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296 0 4 2 1 1 0 1 1 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 5 3 0 0 0 1 0
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297 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
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298 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 2 0 0 0 0 0 0 0 0 0
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299 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ...
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300
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301 FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLeng
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302 th1:MaxLength8;1024;BinaryString;Ascending;001000010011010101011000110
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303 0100010101011000101001011100110001000010001001101000001001001001001000
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304 0010110100000111001001000001001010100100100000000011000000101001011100
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305 0010000001000101010100000100111100110111011011011000000010110111001101
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306 0101100011000000010001000011000010100011101100001000001000100000000...
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307
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308 FingerprintsVector;PathLengthCount:AtomicInvariantsAtomTypes:MinLength
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309 1:MaxLength8;432;NumericalValues;IDsAndValuesPairsString;C.X1.BO1.H3 2
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310 C.X2.BO2.H2 4 C.X2.BO3.H1 14 C.X3.BO3.H1 3 C.X3.BO4 10 F.X1.BO1 1 N.X
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311 2.BO2.H1 1 N.X3.BO3 1 O.X1.BO1.H1 3 O.X1.BO2 2 C.X1.BO1.H3C.X3.BO3.H1
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312 2 C.X2.BO2.H2C.X2.BO2.H2 1 C.X2.BO2.H2C.X3.BO3.H1 4 C.X2.BO2.H2C.X3.BO
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313 4 1 C.X2.BO2.H2N.X3.BO3 1 C.X2.BO3.H1:C.X2.BO3.H1 10 C.X2.BO3.H1:C....
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314
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315 FingerprintsVector;PathLengthCount:MMFF94AtomTypes:MinLength1:MaxLengt
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316 h8;463;NumericalValues;IDsAndValuesPairsString;C5A 2 C5B 2 C=ON 1 CB 1
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317 8 COO 1 CR 9 F 1 N5 1 NC=O 1 O=CN 1 O=CO 1 OC=O 1 OR 2 C5A:C5B 2 C5A:N
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318 5 2 C5ACB 1 C5ACR 1 C5B:C5B 1 C5BC=ON 1 C5BCB 1 C=ON=O=CN 1 C=ONNC=O 1
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319 CB:CB 18 CBF 1 CBNC=O 1 COO=O=CO 1 COOCR 1 COOOC=O 1 CRCR 7 CRN5 1 CR
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320 OR 2 C5A:C5B:C5B 2 C5A:C5BC=ON 1 C5A:C5BCB 1 C5A:N5:C5A 1 C5A:N5CR ...
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321
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322 FingerprintsVector;TopologicalAtomPairs:AtomicInvariantsAtomTypes:MinD
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323 istance1:MaxDistance10;223;NumericalValues;IDsAndValuesString;C.X1.BO1
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324 .H3-D1-C.X3.BO3.H1 C.X2.BO2.H2-D1-C.X2.BO2.H2 C.X2.BO2.H2-D1-C.X3.BO3.
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325 H1 C.X2.BO2.H2-D1-C.X3.BO4 C.X2.BO2.H2-D1-N.X3.BO3 C.X2.BO3.H1-D1-...;
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326 2 1 4 1 1 10 8 1 2 6 1 2 2 1 2 1 2 2 1 2 1 5 1 10 12 2 2 1 2 1 9 1 3 1
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327 1 1 2 2 1 3 6 1 6 14 2 2 2 3 1 3 1 8 2 2 1 3 2 6 1 2 2 5 1 3 1 23 1...
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328
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329 FingerprintsVector;TopologicalAtomPairs:FunctionalClassAtomTypes:MinDi
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330 stance1:MaxDistance10;144;NumericalValues;IDsAndValuesString;Ar-D1-Ar
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331 Ar-D1-Ar.HBA Ar-D1-HBD Ar-D1-Hal Ar-D1-None Ar.HBA-D1-None HBA-D1-NI H
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332 BA-D1-None HBA.HBD-D1-NI HBA.HBD-D1-None HBD-D1-None NI-D1-None No...;
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333 23 2 1 1 2 1 1 1 1 2 1 1 7 28 3 1 3 2 8 2 1 1 1 5 1 5 24 3 3 4 2 13 4
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334 1 1 4 1 5 22 4 4 3 1 19 1 1 1 1 1 2 2 3 1 1 8 25 4 5 2 3 1 26 1 4 1 ...
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335
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336 FingerprintsVector;TopologicalAtomTorsions:AtomicInvariantsAtomTypes;3
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337 3;NumericalValues;IDsAndValuesString;C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4-
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338 C.X3.BO4 C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4-N.X3.BO3 C.X2.BO2.H2-C.X2.BO
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339 2.H2-C.X3.BO3.H1-C.X2.BO2.H2 C.X2.BO2.H2-C.X2.BO2.H2-C.X3.BO3.H1-O...;
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340 2 2 1 1 2 2 1 1 3 4 4 8 4 2 2 6 2 2 1 2 1 1 2 1 1 2 6 2 4 2 1 3 1
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341
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342 FingerprintsVector;TopologicalAtomTorsions:EStateAtomTypes;36;Numerica
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343 lValues;IDsAndValuesString;aaCH-aaCH-aaCH-aaCH aaCH-aaCH-aaCH-aasC aaC
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344 H-aaCH-aasC-aaCH aaCH-aaCH-aasC-aasC aaCH-aaCH-aasC-sF aaCH-aaCH-aasC-
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345 ssNH aaCH-aasC-aasC-aasC aaCH-aasC-aasC-aasN aaCH-aasC-ssNH-dssC a...;
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346 4 4 8 4 2 2 6 2 2 2 4 3 2 1 3 3 2 2 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2
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347
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348 FingerprintsVector;TopologicalAtomTriplets:AtomicInvariantsAtomTypes:M
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349 inDistance1:MaxDistance10;3096;NumericalValues;IDsAndValuesString;C.X1
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350 .BO1.H3-D1-C.X1.BO1.H3-D1-C.X3.BO3.H1-D2 C.X1.BO1.H3-D1-C.X2.BO2.H2-D1
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351 0-C.X3.BO4-D9 C.X1.BO1.H3-D1-C.X2.BO2.H2-D3-N.X3.BO3-D4 C.X1.BO1.H3-D1
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352 -C.X2.BO2.H2-D4-C.X2.BO2.H2-D5 C.X1.BO1.H3-D1-C.X2.BO2.H2-D6-C.X3....;
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353 1 2 2 2 2 2 2 2 8 8 4 8 4 4 2 2 2 2 4 2 2 2 4 2 2 2 2 1 2 2 4 4 4 2 2
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354 2 4 4 4 8 4 4 2 4 4 4 2 4 4 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 8...
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355
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356 FingerprintsVector;TopologicalAtomTriplets:SYBYLAtomTypes:MinDistance1
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357 :MaxDistance10;2332;NumericalValues;IDsAndValuesString;C.2-D1-C.2-D9-C
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358 .3-D10 C.2-D1-C.2-D9-C.ar-D10 C.2-D1-C.3-D1-C.3-D2 C.2-D1-C.3-D10-C.3-
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359 D9 C.2-D1-C.3-D2-C.3-D3 C.2-D1-C.3-D2-C.ar-D3 C.2-D1-C.3-D3-C.3-D4 C.2
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360 -D1-C.3-D3-N.ar-D4 C.2-D1-C.3-D3-O.3-D2 C.2-D1-C.3-D4-C.3-D5 C.2-D1-C.
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361 3-D5-C.3-D6 C.2-D1-C.3-D5-O.3-D4 C.2-D1-C.3-D6-C.3-D7 C.2-D1-C.3-D7...
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362
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363 FingerprintsVector;TopologicalPharmacophoreAtomPairs:ArbitrarySize:Min
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364 Distance1:MaxDistance10;54;NumericalValues;IDsAndValuesString;H-D1-H H
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365 -D1-NI HBA-D1-NI HBD-D1-NI H-D2-H H-D2-HBA H-D2-HBD HBA-D2-HBA HBA-D2-
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366 HBD H-D3-H H-D3-HBA H-D3-HBD H-D3-NI HBA-D3-NI HBD-D3-NI H-D4-H H-D4-H
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367 BA H-D4-HBD HBA-D4-HBA HBA-D4-HBD HBD-D4-HBD H-D5-H H-D5-HBA H-D5-...;
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368 18 1 2 1 22 12 8 1 2 18 6 3 1 1 1 22 13 6 5 7 2 28 9 5 1 1 1 36 16 10
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369 3 4 1 37 10 8 1 35 10 9 3 3 1 28 7 7 4 18 16 12 5 1 2 1
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370
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371 FingerprintsVector;TopologicalPharmacophoreAtomPairs:FixedSize:MinDist
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372 ance1:MaxDistance10;150;OrderedNumericalValues;ValuesString;18 0 0 1 0
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373 0 0 2 0 0 1 0 0 0 0 22 12 8 0 0 1 2 0 0 0 0 0 0 0 0 18 6 3 1 0 0 0 1
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374 0 0 1 0 0 0 0 22 13 6 0 0 5 7 0 0 2 0 0 0 0 0 28 9 5 1 0 0 0 1 0 0 1 0
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375 0 0 0 36 16 10 0 0 3 4 0 0 1 0 0 0 0 0 37 10 8 0 0 0 0 1 0 0 0 0 0 0
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376 0 35 10 9 0 0 3 3 0 0 1 0 0 0 0 0 28 7 7 4 0 0 0 0 0 0 0 0 0 0 0 18...
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377
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378 FingerprintsVector;TopologicalPharmacophoreAtomTriplets:ArbitrarySize:
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379 MinDistance1:MaxDistance10;696;NumericalValues;IDsAndValuesString;Ar1-
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380 Ar1-Ar1 Ar1-Ar1-H1 Ar1-Ar1-HBA1 Ar1-Ar1-HBD1 Ar1-H1-H1 Ar1-H1-HBA1 Ar1
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381 -H1-HBD1 Ar1-HBA1-HBD1 H1-H1-H1 H1-H1-HBA1 H1-H1-HBD1 H1-HBA1-HBA1 H1-
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382 HBA1-HBD1 H1-HBA1-NI1 H1-HBD1-NI1 HBA1-HBA1-NI1 HBA1-HBD1-NI1 Ar1-...;
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383 46 106 8 3 83 11 4 1 21 5 3 1 2 2 1 1 1 100 101 18 11 145 132 26 14 23
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384 28 3 3 5 4 61 45 10 4 16 20 7 5 1 3 4 5 3 1 1 1 1 5 4 2 1 2 2 2 1 1 1
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385 119 123 24 15 185 202 41 25 22 17 3 5 85 95 18 11 23 17 3 1 1 6 4 ...
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386
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387 FingerprintsVector;TopologicalPharmacophoreAtomTriplets:FixedSize:MinD
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388 istance1:MaxDistance10;2692;OrderedNumericalValues;ValuesString;46 106
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389 8 3 0 0 83 11 4 0 0 0 1 0 0 0 0 0 0 0 0 21 5 3 0 0 1 2 2 0 0 1 0 0 0
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390 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 101 18 11 0 0 145 132 26
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391 14 0 0 23 28 3 3 0 0 5 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 61 45 10 4 0
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392 0 16 20 7 5 1 0 3 4 5 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 5 ...
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393
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394 OPTIONS
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395 --alpha *number*
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396 Value of alpha parameter for calculating *Tversky* similarity
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397 coefficient specified for -b, --BitVectorComparisonMode option. It
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398 corresponds to weights assigned for bits set to "1" in a pair of
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399 fingerprint bit-vectors during the calculation of similarity
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400 coefficient. Possible values: *0 to 1*. Default value: <0.5>.
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401
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402 --beta *number*
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403 Value of beta parameter for calculating *WeightedTanimoto* and
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404 *WeightedTversky* similarity coefficients specified for -b,
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405 --BitVectorComparisonMode option. It is used to weight the
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406 contributions of bits set to "0" during the calculation of
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407 similarity coefficients. Possible values: *0 to 1*. Default value of
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408 <1> makes *WeightedTanimoto* and *WeightedTversky* equivalent to
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409 *Tanimoto* and *Tversky*.
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410
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411 -b, --BitVectorComparisonMode *TanimotoSimilarity | TverskySimilarity |
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412 ...*
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413 Specify what similarity coefficient to use for calculating
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414 similarity between fingerprints bit-vector string data values in
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415 *ReferenceFingerprintsFile* and *DatabaseFingerprintsFile* during
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416 similarity search. Possible values: *TanimotoSimilarity |
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417 TverskySimilarity | ...*. Default: *TanimotoSimilarity*
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418
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419 The current release supports the following similarity coefficients:
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420 *BaroniUrbaniSimilarity, BuserSimilarity, CosineSimilarity,
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421 DiceSimilarity, DennisSimilarity, ForbesSimilarity,
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422 FossumSimilarity, HamannSimilarity, JacardSimilarity,
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423 Kulczynski1Similarity, Kulczynski2Similarity, MatchingSimilarity,
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424 McConnaugheySimilarity, OchiaiSimilarity, PearsonSimilarity,
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425 RogersTanimotoSimilarity, RussellRaoSimilarity, SimpsonSimilarity,
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426 SkoalSneath1Similarity, SkoalSneath2Similarity,
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427 SkoalSneath3Similarity, TanimotoSimilarity, TverskySimilarity,
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428 YuleSimilarity, WeightedTanimotoSimilarity,
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429 WeightedTverskySimilarity*. These similarity coefficients are
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430 described below.
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431
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432 For two fingerprint bit-vectors A and B of same size, let:
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433
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434 Na = Number of bits set to "1" in A
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435 Nb = Number of bits set to "1" in B
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436 Nc = Number of bits set to "1" in both A and B
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437 Nd = Number of bits set to "0" in both A and B
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438
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439 Nt = Number of bits set to "1" or "0" in A or B (Size of A or B)
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440 Nt = Na + Nb - Nc + Nd
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441
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442 Na - Nc = Number of bits set to "1" in A but not in B
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443 Nb - Nc = Number of bits set to "1" in B but not in A
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444
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445 Then, various similarity coefficients [ Ref. 40 - 42 ] for a pair of
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446 bit-vectors A and B are defined as follows:
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447
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448 *BaroniUrbaniSimilarity*: ( SQRT( Nc * Nd ) + Nc ) / ( SQRT ( Nc *
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449 Nd ) + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as Buser )
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450
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451 *BuserSimilarity*: ( SQRT ( Nc * Nd ) + Nc ) / ( SQRT ( Nc * Nd ) +
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452 Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as BaroniUrbani )
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453
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454 *CosineSimilarity*: Nc / SQRT ( Na * Nb ) (same as Ochiai)
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455
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456 *DiceSimilarity*: (2 * Nc) / ( Na + Nb )
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457
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458 *DennisSimilarity*: ( Nc * Nd - ( ( Na - Nc ) * ( Nb - Nc ) ) ) /
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459 SQRT ( Nt * Na * Nb)
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460
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461 *ForbesSimilarity*: ( Nt * Nc ) / ( Na * Nb )
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462
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463 *FossumSimilarity*: ( Nt * ( ( Nc - 1/2 ) ** 2 ) / ( Na * Nb )
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464
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465 *HamannSimilarity*: ( ( Nc + Nd ) - ( Na - Nc ) - ( Nb - Nc ) ) / Nt
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466
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467 *JaccardSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / (
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468 Na + Nb - Nc ) (same as Tanimoto)
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469
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470 *Kulczynski1Similarity*: Nc / ( ( Na - Nc ) + ( Nb - Nc) ) = Nc / (
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471 Na + Nb - 2Nc )
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472
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473 *Kulczynski2Similarity*: ( ( Nc / 2 ) * ( 2 * Nc + ( Na - Nc ) + (
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474 Nb - Nc) ) ) / ( ( Nc + ( Na - Nc ) ) * ( Nc + ( Nb - Nc ) ) ) = 0.5
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475 * ( Nc / Na + Nc / Nb )
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476
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477 *MatchingSimilarity*: ( Nc + Nd ) / Nt
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478
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479 *McConnaugheySimilarity*: ( Nc ** 2 - ( Na - Nc ) * ( Nb - Nc) ) / (
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480 Na * Nb )
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481
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482 *OchiaiSimilarity*: Nc / SQRT ( Na * Nb ) (same as Cosine)
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483
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484 *PearsonSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) /
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485 SQRT ( Na * Nb * ( Na - Nc + Nd ) * ( Nb - Nc + Nd ) )
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486
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487 *RogersTanimotoSimilarity*: ( Nc + Nd ) / ( ( Na - Nc) + ( Nb - Nc)
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488 + Nt) = ( Nc + Nd ) / ( Na + Nb - 2Nc + Nt)
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489
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490 *RussellRaoSimilarity*: Nc / Nt
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491
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492 *SimpsonSimilarity*: Nc / MIN ( Na, Nb)
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493
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494 *SkoalSneath1Similarity*: Nc / ( Nc + 2 * ( Na - Nc) + 2 * ( Nb -
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495 Nc) ) = Nc / ( 2 * Na + 2 * Nb - 3 * Nc )
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496
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497 *SkoalSneath2Similarity*: ( 2 * Nc + 2 * Nd ) / ( Nc + Nd + Nt )
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498
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499 *SkoalSneath3Similarity*: ( Nc + Nd ) / ( ( Na - Nc ) + ( Nb - Nc )
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500 ) = ( Nc + Nd ) / ( Na + Nb - 2 * Nc )
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501
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502 *TanimotoSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc /
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503 ( Na + Nb - Nc ) (same as Jaccard)
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504
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505 *TverskySimilarity*: Nc / ( alpha * ( Na - Nc ) + ( 1 - alpha) * (
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506 Nb - Nc) + Nc ) = Nc / ( alpha * ( Na - Nb ) + Nb)
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507
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508 *YuleSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) ) /
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509 ( ( Nc * Nd ) + ( ( Na - Nc ) * ( Nb - Nc ) ) )
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510
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511 Values of Tanimoto/Jaccard and Tversky coefficients are dependent on
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512 only those bit which are set to "1" in both A and B. In order to
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513 take into account all bit positions, modified versions of Tanimoto [
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514 Ref. 42 ] and Tversky [ Ref. 43 ] have been developed.
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515
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516 Let:
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517
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518 Na' = Number of bits set to "0" in A
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519 Nb' = Number of bits set to "0" in B
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520 Nc' = Number of bits set to "0" in both A and B
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521
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522 Tanimoto': Nc' / ( ( Na' - Nc') + ( Nb' - Nc' ) + Nc' ) = Nc' / (
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523 Na' + Nb' - Nc' )
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524
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525 Tversky': Nc' / ( alpha * ( Na' - Nc' ) + ( 1 - alpha) * ( Nb' - Nc'
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526 ) + Nc' ) = Nc' / ( alpha * ( Na' - Nb' ) + Nb')
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527
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528 Then:
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529
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530 *WeightedTanimotoSimilarity* = beta * Tanimoto + (1 - beta) *
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531 Tanimoto'
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532
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533 *WeightedTverskySimilarity* = beta * Tversky + (1 - beta) * Tversky'
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534
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535 --DatabaseColMode *ColNum | ColLabel*
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536 Specify how columns are identified in database fingerprints
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537 *TextFile*: using column number or column label. Possible values:
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538 *ColNum or ColLabel*. Default value: *ColNum*.
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539
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540 --DatabaseCompoundIDCol *col number | col name*
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541 This value is --DatabaseColMode mode specific. It specifies column
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542 to use for retrieving compound ID from database fingerprints
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543 *TextFile* during similarity and dissimilarity search for output SD
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544 and CSV/TSV text files. Possible values: *col number or col label*.
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545 Default value: *first column containing the word compoundID in its
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546 column label or sequentially generated IDs*.
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547
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548 This is only used for *CompoundID* value of --DatabaseDataColsMode
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549 option.
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550
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551 --DatabaseCompoundIDPrefix *text*
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552 Specify compound ID prefix to use during sequential generation of
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|
|
553 compound IDs for database fingerprints *SDFile* and *TextFile*.
|
|
|
554 Default value: *Cmpd*. The default value generates compound IDs
|
|
|
555 which look like Cmpd<Number>.
|
|
|
556
|
|
|
557 For database fingerprints *SDFile*, this value is only used during
|
|
|
558 *LabelPrefix | MolNameOrLabelPrefix* values of
|
|
|
559 --DatabaseCompoundIDMode option; otherwise, it's ignored.
|
|
|
560
|
|
|
561 Examples for *LabelPrefix* or *MolNameOrLabelPrefix* value of
|
|
|
562 --DatabaseCompoundIDMode:
|
|
|
563
|
|
|
564 Compound
|
|
|
565
|
|
|
566 The values specified above generates compound IDs which correspond
|
|
|
567 to Compound<Number> instead of default value of Cmpd<Number>.
|
|
|
568
|
|
|
569 --DatabaseCompoundIDField *DataFieldName*
|
|
|
570 Specify database fingerprints *SDFile* datafield label for
|
|
|
571 generating compound IDs. This value is only used during *DataField*
|
|
|
572 value of --DatabaseCompoundIDMode option.
|
|
|
573
|
|
|
574 Examples for *DataField* value of --DatabaseCompoundIDMode:
|
|
|
575
|
|
|
576 MolID
|
|
|
577 ExtReg
|
|
|
578
|
|
|
579 --DatabaseCompoundIDMode *DataField | MolName | LabelPrefix |
|
|
|
580 MolNameOrLabelPrefix*
|
|
|
581 Specify how to generate compound IDs from database fingerprints
|
|
|
582 *SDFile* during similarity and dissimilarity search for output SD
|
|
|
583 and CSV/TSV text files: use a *SDFile* datafield value; use molname
|
|
|
584 line from *SDFile*; generate a sequential ID with specific prefix;
|
|
|
585 use combination of both MolName and LabelPrefix with usage of
|
|
|
586 LabelPrefix values for empty molname lines.
|
|
|
587
|
|
|
588 Possible values: *DataField | MolName | LabelPrefix |
|
|
|
589 MolNameOrLabelPrefix*. Default: *LabelPrefix*.
|
|
|
590
|
|
|
591 For *MolNameAndLabelPrefix* value of --DatabaseCompoundIDMode,
|
|
|
592 molname line in *SDFile* takes precedence over sequential compound
|
|
|
593 IDs generated using *LabelPrefix* and only empty molname values are
|
|
|
594 replaced with sequential compound IDs.
|
|
|
595
|
|
|
596 This is only used for *CompoundID* value of --DatabaseDataFieldsMode
|
|
|
597 option.
|
|
|
598
|
|
|
599 --DatabaseDataCols *"DataColNum1,DataColNum2,... " |
|
|
|
600 DataColLabel1,DataCoLabel2,... "*
|
|
|
601 This value is --DatabaseColMode mode specific. It is a comma
|
|
|
602 delimited list of database fingerprints *TextFile* data column
|
|
|
603 numbers or labels to extract and write to SD and CSV/TSV text files
|
|
|
604 along with other information for *SD | text | both* values of
|
|
|
605 --output option.
|
|
|
606
|
|
|
607 This is only used for *Specify* value of --DatabaseDataColsMode
|
|
|
608 option.
|
|
|
609
|
|
|
610 Examples:
|
|
|
611
|
|
|
612 1,2,3
|
|
|
613 CompoundName,MolWt
|
|
|
614
|
|
|
615 --DatabaseDataColsMode *All | Specify | CompoundID*
|
|
|
616 Specify how data columns from database fingerprints *TextFile* are
|
|
|
617 transferred to output SD and CSV/TSV text files along with other
|
|
|
618 information for *SD | text | both* values of --output option:
|
|
|
619 transfer all data columns; extract specified data columns; generate
|
|
|
620 a compound ID database compound prefix. Possible values: *All |
|
|
|
621 Specify | CompoundID*. Default value: *CompoundID*.
|
|
|
622
|
|
|
623 --DatabaseDataFields *"FieldLabel1,FieldLabel2,... "*
|
|
|
624 Comma delimited list of database fingerprints *SDFile* data fields
|
|
|
625 to extract and write to SD and CSV/TSV text files along with other
|
|
|
626 information for *SD | text | both* values of --output option.
|
|
|
627
|
|
|
628 This is only used for *Specify* value of --DatabaseDataFieldsMode
|
|
|
629 option.
|
|
|
630
|
|
|
631 Examples:
|
|
|
632
|
|
|
633 Extreg
|
|
|
634 MolID,CompoundName
|
|
|
635
|
|
|
636 --DatabaseDataFieldsMode *All | Common | Specify | CompoundID*
|
|
|
637 Specify how data fields from database fingerprints *SDFile* are
|
|
|
638 transferred to output SD and CSV/TSV text files along with other
|
|
|
639 information for *SD | text | both* values of --output option:
|
|
|
640 transfer all SD data field; transfer SD data files common to all
|
|
|
641 compounds; extract specified data fields; generate a compound ID
|
|
|
642 using molname line, a compound prefix, or a combination of both.
|
|
|
643 Possible values: *All | Common | specify | CompoundID*. Default
|
|
|
644 value: *CompoundID*.
|
|
|
645
|
|
|
646 --DatabaseFingerprintsCol *col number | col name*
|
|
|
647 This value is --DatabaseColMode specific. It specifies fingerprints
|
|
|
648 column to use during similarity and dissimilarity search for
|
|
|
649 database fingerprints *TextFile*. Possible values: *col number or
|
|
|
650 col label*. Default value: *first column containing the word
|
|
|
651 Fingerprints in its column label*.
|
|
|
652
|
|
|
653 --DatabaseFingerprintsField *FieldLabel*
|
|
|
654 Fingerprints field label to use during similarity and dissimilarity
|
|
|
655 search for database fingerprints *SDFile*. Default value: *first
|
|
|
656 data field label containing the word Fingerprints in its label*
|
|
|
657
|
|
|
658 --DistanceCutoff *number*
|
|
|
659 Distance cutoff value to use during comparison of distance value
|
|
|
660 between a pair of database and reference molecule calculated by
|
|
|
661 distance comparison methods for fingerprints vector string data
|
|
|
662 values. Possible values: *Any valid number*. Default value: *10*.
|
|
|
663
|
|
|
664 The comparison value between a pair of database and reference
|
|
|
665 molecule must meet the cutoff criterion as shown below:
|
|
|
666
|
|
|
667 SeachMode CutoffCriterion ComparisonValues
|
|
|
668
|
|
|
669 Similarity <= Lower value implies high similarity
|
|
|
670 Dissimilarity >= Higher value implies high dissimilarity
|
|
|
671
|
|
|
672 This option is only used during distance coefficients values of -v,
|
|
|
673 --VectorComparisonMode option.
|
|
|
674
|
|
|
675 This option is ignored during *No* value of --GroupFusionApplyCutoff
|
|
|
676 for *MultipleReferences* -m, --mode.
|
|
|
677
|
|
|
678 -d, --detail *InfoLevel*
|
|
|
679 Level of information to print about lines being ignored. Default:
|
|
|
680 *1*. Possible values: *1, 2 or 3*.
|
|
|
681
|
|
|
682 -f, --fast
|
|
|
683 In this mode, fingerprints columns specified using --FingerprintsCol
|
|
|
684 for reference and database fingerprints *TextFile(s)*, and
|
|
|
685 --FingerprintsField for reference and database fingerprints
|
|
|
686 *SDFile(s)* are assumed to contain valid fingerprints data and no
|
|
|
687 checking is performed before performing similarity and dissimilarity
|
|
|
688 search. By default, fingerprints data is validated before computing
|
|
|
689 pairwise similarity and distance coefficients.
|
|
|
690
|
|
|
691 --FingerprintsMode *AutoDetect | FingerprintsBitVectorString |
|
|
|
692 FingerprintsVectorString*
|
|
|
693 Format of fingerprint strings data in reference and database
|
|
|
694 fingerprints *SD, FP, or Text (CSV/TSV)* files: automatically detect
|
|
|
695 format of fingerprints string created by MayaChemTools fingerprints
|
|
|
696 generation scripts or explicitly specify its format. Possible
|
|
|
697 values: *AutoDetect | FingerprintsBitVectorString |
|
|
|
698 FingerprintsVectorString*. Default value: *AutoDetect*.
|
|
|
699
|
|
|
700 -g, --GroupFusionRule *Max, Min, Mean, Median, Sum, Euclidean*
|
|
|
701 Specify what group fusion [ Ref 94-97, Ref 100, Ref 105 ] rule to
|
|
|
702 use for calculating similarity of a database molecule against a set
|
|
|
703 of reference molecules during *MultipleReferences* value of
|
|
|
704 similarity search -m, --mode. Possible values: *Max, Min, Mean,
|
|
|
705 Median, Sum, Euclidean*. Default value: *Max*. *Mean* value
|
|
|
706 corresponds to average or arithmetic mean. The group fusion rule is
|
|
|
707 also referred to as data fusion of consensus scoring in the
|
|
|
708 literature.
|
|
|
709
|
|
|
710 For a reference molecules set and a database molecule, let:
|
|
|
711
|
|
|
712 N = Number of reference molecules in a set
|
|
|
713
|
|
|
714 i = ith reference reference molecule in a set
|
|
|
715 n = Nth reference reference molecule in a set
|
|
|
716
|
|
|
717 d = dth database molecule
|
|
|
718
|
|
|
719 Crd = Fingerprints comparison value between rth reference and dth database
|
|
|
720 molecule - similarity/dissimilarity comparison using similarity or
|
|
|
721 distance coefficient
|
|
|
722
|
|
|
723 Then, various group fusion rules to calculate fused similarity
|
|
|
724 between a database molecule and reference molecules set are defined
|
|
|
725 as follows:
|
|
|
726
|
|
|
727 Max: MAX ( C1d, C2d, ..., Cid, ..., Cnd )
|
|
|
728
|
|
|
729 Min: MIN ( C1d, C2d, ..., Cid, ..., Cnd )
|
|
|
730
|
|
|
731 Mean: SUM ( C1d, C2d, ..., Cid, ..., Cnd ) / N
|
|
|
732
|
|
|
733 Median: MEDIAN ( C1d, C2d, ..., Cid, ..., Cnd )
|
|
|
734
|
|
|
735 Sum: SUM ( C1d, C2d, ..., Cid, ..., Cnd )
|
|
|
736
|
|
|
737 Euclidean: SQRT( SUM( C1d ** 2, C2d ** 2, ..., Cid ** 2, ..., Cnd
|
|
|
738 *** 2) )
|
|
|
739
|
|
|
740 The fingerprints bit-vector or vector string of each reference
|
|
|
741 molecule in a set is compared with a database molecule using a
|
|
|
742 similarity or distance coefficient specified via -b,
|
|
|
743 --BitVectorComparisonMode or -v, --VectorComparisonMode. The
|
|
|
744 reference molecules whose comparison values with a database molecule
|
|
|
745 fall outside specified --SimilarityCutoff or --DistanceCutoff are
|
|
|
746 ignored during *Yes* value of --GroupFusionApplyCutoff. The
|
|
|
747 specified -g, --GroupFusionRule is applied to -k, --kNN reference
|
|
|
748 molecules to calculate final fused similarity value between a
|
|
|
749 database molecule and reference molecules set.
|
|
|
750
|
|
|
751 During dissimilarity search or usage of distance comparison
|
|
|
752 coefficient in similarity search, the meaning of fingerprints
|
|
|
753 comaprison value is automatically reversed as shown below:
|
|
|
754
|
|
|
755 SeachMode ComparisonCoefficient ComparisonValues
|
|
|
756
|
|
|
757 Similarity SimilarityCoefficient Higher value imples high similarity
|
|
|
758 Similarity DistanceCoefficient Lower value implies high similarity
|
|
|
759
|
|
|
760 Dissimilarity SimilarityCoefficient Lower value implies high
|
|
|
761 dissimilarity
|
|
|
762 Dissimilarity DistanceCoefficient Higher value implies high
|
|
|
763 dissimilarity
|
|
|
764
|
|
|
765 Consequently, *Max* implies highest and lowest comparison value for
|
|
|
766 usage of similarity and distance coefficient respectively during
|
|
|
767 similarity search. And it corresponds to lowest and highest
|
|
|
768 comparison value for usage of similarity and distance coefficient
|
|
|
769 respectively during dissimilarity search. During *Min* fusion rule,
|
|
|
770 the highest and lowest comparison values are appropriately reversed.
|
|
|
771
|
|
|
772 --GroupFusionApplyCutoff *Yes | No*
|
|
|
773 Specify whether to apply --SimilarityCutoff or --DistanceCutoff
|
|
|
774 values during application of -g, --GroupFusionRule to reference
|
|
|
775 molecules set. Possible values: *Yes or No*. Default value: *Yes*.
|
|
|
776
|
|
|
777 During *Yes* value of --GroupFusionApplyCutoff, the reference
|
|
|
778 molecules whose comparison values with a database molecule fall
|
|
|
779 outside specified --SimilarityCutoff or --DistanceCutoff are not
|
|
|
780 used to calculate final fused similarity value between a database
|
|
|
781 molecule and reference molecules set.
|
|
|
782
|
|
|
783 -h, --help
|
|
|
784 Print this help message.
|
|
|
785
|
|
|
786 --InDelim *comma | semicolon*
|
|
|
787 Input delimiter for reference and database fingerprints CSV
|
|
|
788 *TextFile(s)*. Possible values: *comma or semicolon*. Default value:
|
|
|
789 *comma*. For TSV files, this option is ignored and *tab* is used as
|
|
|
790 a delimiter.
|
|
|
791
|
|
|
792 -k, --kNN *all | number*
|
|
|
793 Number of k-nearest neighbors (k-NN) reference molecules to use
|
|
|
794 during -g, --GroupFusionRule for calculating similarity of a
|
|
|
795 database molecule against a set of reference molecules. Possible
|
|
|
796 values: *all | positive integers*. Default: *all*.
|
|
|
797
|
|
|
798 After ranking similarity values between a database molecule and
|
|
|
799 reference molecules during *MultipleReferences* value of similarity
|
|
|
800 search -m, --mode option, a top -k, --KNN reference molecule are
|
|
|
801 selected and used during -g, --GroupFusionRule.
|
|
|
802
|
|
|
803 This option is -s, --SearchMode dependent: It corresponds to
|
|
|
804 dissimilar molecules during *DissimilaritySearch* value of -s,
|
|
|
805 --SearchMode option.
|
|
|
806
|
|
|
807 -m, --mode *IndividualReference | MultipleReferences*
|
|
|
808 Specify how to treat reference molecules in
|
|
|
809 *ReferenceFingerprintsFile* during similarity search: Treat each
|
|
|
810 reference molecule individually during similarity search or perform
|
|
|
811 similarity search by treating multiple reference molecules as a set.
|
|
|
812 Possible values: *IndividualReference | MultipleReferences*. Default
|
|
|
813 value: *MultipleReferences*.
|
|
|
814
|
|
|
815 During *IndividualReference* value of -m, --Mode for similarity
|
|
|
816 search, fingerprints bit-vector or vector string of each reference
|
|
|
817 molecule is compared with database molecules using specified
|
|
|
818 similarity or distance coefficients to identify most similar
|
|
|
819 molecules for each reference molecule. Based on value of
|
|
|
820 --SimilarCountMode, upto --n, NumOfSimilarMolecules or -p,
|
|
|
821 --PercentSimilarMolecules at specified <--SimilarityCutoff> or
|
|
|
822 --DistanceCutoff are identified for each reference molecule.
|
|
|
823
|
|
|
824 During *MultipleReferences* value -m, --mode for similarity search,
|
|
|
825 all reference molecules are considered as a set and -g,
|
|
|
826 --GroupFusionRule is used to calculate similarity of a database
|
|
|
827 molecule against reference molecules set either using all reference
|
|
|
828 molecules or number of k-nearest neighbors (k-NN) to a database
|
|
|
829 molecule specified using -k, --kNN. The fingerprints bit-vector or
|
|
|
830 vector string of each reference molecule in a set is compared with a
|
|
|
831 database molecule using a similarity or distance coefficient
|
|
|
832 specified via -b, --BitVectorComparisonMode or -v,
|
|
|
833 --VectorComparisonMode. The reference molecules whose comparison
|
|
|
834 values with a database molecule fall outside specified
|
|
|
835 --SimilarityCutoff or --DistanceCutoff are ignored. The specified
|
|
|
836 -g, --GroupFusionRule is applied to rest of -k, --kNN reference
|
|
|
837 molecules to calculate final similarity value between a database
|
|
|
838 molecule and reference molecules set.
|
|
|
839
|
|
|
840 The meaning of similarity and distance is automatically reversed
|
|
|
841 during *DissimilaritySearch* value of -s, --SearchMode along with
|
|
|
842 appropriate handling of --SimilarityCutoff or --DistanceCutoff
|
|
|
843 values.
|
|
|
844
|
|
|
845 -n, --NumOfSimilarMolecules *number*
|
|
|
846 Maximum number of most similar database molecules to find for each
|
|
|
847 reference molecule or set of reference molecules based on
|
|
|
848 *IndividualReference* or *MultipleReferences* value of similarity
|
|
|
849 search -m, --mode option. Default: *10*. Valid values: positive
|
|
|
850 integers.
|
|
|
851
|
|
|
852 This option is ignored during *PercentSimilar* value of
|
|
|
853 --SimilarCountMode option.
|
|
|
854
|
|
|
855 This option is -s, --SearchMode dependent: It corresponds to
|
|
|
856 dissimilar molecules during *DissimilaritySearch* value of -s,
|
|
|
857 --SearchMode option.
|
|
|
858
|
|
|
859 --OutDelim *comma | tab | semicolon*
|
|
|
860 Delimiter for output CSV/TSV text file. Possible values: *comma,
|
|
|
861 tab, or semicolon* Default value: *comma*.
|
|
|
862
|
|
|
863 --output *SD | text | both*
|
|
|
864 Type of output files to generate. Possible values: *SD, text, or
|
|
|
865 both*. Default value: *text*.
|
|
|
866
|
|
|
867 -o, --overwrite
|
|
|
868 Overwrite existing files
|
|
|
869
|
|
|
870 -p, --PercentSimilarMolecules *number*
|
|
|
871 Maximum percent of mosy similar database molecules to find for each
|
|
|
872 reference molecule or set of reference molecules based on
|
|
|
873 *IndividualReference* or *MultipleReferences* value of similarity
|
|
|
874 search -m, --mode option. Default: *1* percent of database
|
|
|
875 molecules. Valid values: non-zero values in between *0 to 100*.
|
|
|
876
|
|
|
877 This option is ignored during *NumOfSimilar* value of
|
|
|
878 --SimilarCountMode option.
|
|
|
879
|
|
|
880 During *PercentSimilar* value of --SimilarCountMode option, the
|
|
|
881 number of molecules in *DatabaseFingerprintsFile* is counted and
|
|
|
882 number of similar molecules correspond to --PercentSimilarMolecules
|
|
|
883 of the total number of database molecules.
|
|
|
884
|
|
|
885 This option is -s, --SearchMode dependent: It corresponds to
|
|
|
886 dissimilar molecules during *DissimilaritySearch* value of -s,
|
|
|
887 --SearchMode option.
|
|
|
888
|
|
|
889 --precision *number*
|
|
|
890 Precision of calculated similarity values for comparison and
|
|
|
891 generating output files. Default: up to *2* decimal places. Valid
|
|
|
892 values: positive integers.
|
|
|
893
|
|
|
894 -q, --quote *Yes | No*
|
|
|
895 Put quote around column values in output CSV/TSV text file. Possible
|
|
|
896 values: *Yes or No*. Default value: *Yes*.
|
|
|
897
|
|
|
898 --ReferenceColMode *ColNum | ColLabel*
|
|
|
899 Specify how columns are identified in reference fingerprints
|
|
|
900 *TextFile*: using column number or column label. Possible values:
|
|
|
901 *ColNum or ColLabel*. Default value: *ColNum*.
|
|
|
902
|
|
|
903 --ReferenceCompoundIDCol *col number | col name*
|
|
|
904 This value is --ReferenceColMode mode specific. It specifies column
|
|
|
905 to use for retrieving compound ID from reference fingerprints
|
|
|
906 *TextFile* during similarity and dissimilarity search for output SD
|
|
|
907 and CSV/TSV text files. Possible values: *col number or col label*.
|
|
|
908 Default value: *first column containing the word compoundID in its
|
|
|
909 column label or sequentially generated IDs*.
|
|
|
910
|
|
|
911 --ReferenceCompoundIDPrefix *text*
|
|
|
912 Specify compound ID prefix to use during sequential generation of
|
|
|
913 compound IDs for reference fingerprints *SDFile* and *TextFile*.
|
|
|
914 Default value: *Cmpd*. The default value generates compound IDs
|
|
|
915 which looks like Cmpd<Number>.
|
|
|
916
|
|
|
917 For reference fingerprints *SDFile*, this value is only used during
|
|
|
918 *LabelPrefix | MolNameOrLabelPrefix* values of
|
|
|
919 --ReferenceCompoundIDMode option; otherwise, it's ignored.
|
|
|
920
|
|
|
921 Examples for *LabelPrefix* or *MolNameOrLabelPrefix* value of
|
|
|
922 --DatabaseCompoundIDMode:
|
|
|
923
|
|
|
924 Compound
|
|
|
925
|
|
|
926 The values specified above generates compound IDs which correspond
|
|
|
927 to Compound<Number> instead of default value of Cmpd<Number>.
|
|
|
928
|
|
|
929 --ReferenceCompoundIDField *DataFieldName*
|
|
|
930 Specify reference fingerprints *SDFile* datafield label for
|
|
|
931 generating compound IDs. This value is only used during *DataField*
|
|
|
932 value of --ReferenceCompoundIDMode option.
|
|
|
933
|
|
|
934 Examples for *DataField* value of --ReferenceCompoundIDMode:
|
|
|
935
|
|
|
936 MolID
|
|
|
937 ExtReg
|
|
|
938
|
|
|
939 --ReferenceCompoundIDMode *DataField | MolName | LabelPrefix |
|
|
|
940 MolNameOrLabelPrefix*
|
|
|
941 Specify how to generate compound IDs from reference fingerprints
|
|
|
942 *SDFile* during similarity and dissimilarity search for output SD
|
|
|
943 and CSV/TSV text files: use a *SDFile* datafield value; use molname
|
|
|
944 line from *SDFile*; generate a sequential ID with specific prefix;
|
|
|
945 use combination of both MolName and LabelPrefix with usage of
|
|
|
946 LabelPrefix values for empty molname lines.
|
|
|
947
|
|
|
948 Possible values: *DataField | MolName | LabelPrefix |
|
|
|
949 MolNameOrLabelPrefix*. Default: *LabelPrefix*.
|
|
|
950
|
|
|
951 For *MolNameAndLabelPrefix* value of --ReferenceCompoundIDMode,
|
|
|
952 molname line in *SDFiles* takes precedence over sequential compound
|
|
|
953 IDs generated using *LabelPrefix* and only empty molname values are
|
|
|
954 replaced with sequential compound IDs.
|
|
|
955
|
|
|
956 --ReferenceFingerprintsCol *col number | col name*
|
|
|
957 This value is --ReferenceColMode specific. It specifies fingerprints
|
|
|
958 column to use during similarity and dissimilarity search for
|
|
|
959 reference fingerprints *TextFile*. Possible values: *col number or
|
|
|
960 col label*. Default value: *first column containing the word
|
|
|
961 Fingerprints in its column label*.
|
|
|
962
|
|
|
963 --ReferenceFingerprintsField *FieldLabel*
|
|
|
964 Fingerprints field label to use during similarity and dissimilarity
|
|
|
965 search for reference fingerprints *SDFile*. Default value: *first
|
|
|
966 data field label containing the word Fingerprints in its label*
|
|
|
967
|
|
|
968 -r, --root *RootName*
|
|
|
969 New file name is generated using the root: <Root>.<Ext>. Default for
|
|
|
970 new file name: <ReferenceFileName>SimilaritySearching.<Ext>. The
|
|
|
971 output file type determines <Ext> value. The sdf, csv, and tsv <Ext>
|
|
|
972 values are used for SD, comma/semicolon, and tab delimited text
|
|
|
973 files respectively.
|
|
|
974
|
|
|
975 -s, --SearchMode *SimilaritySearch | DissimilaritySearch*
|
|
|
976 Specify how to find molecules from database molecules for individual
|
|
|
977 reference molecules or set of reference molecules: Find similar
|
|
|
978 molecules or dissimilar molecules from database molecules. Possible
|
|
|
979 values: *SimilaritySearch | DissimilaritySearch*. Default value:
|
|
|
980 *SimilaritySearch*.
|
|
|
981
|
|
|
982 During *DissimilaritySearch* value of -s, --SearchMode option, the
|
|
|
983 meaning of the following options is switched and they correspond to
|
|
|
984 dissimilar molecules instead of similar molecules:
|
|
|
985 --SimilarCountMode, -n, --NumOfSimilarMolecules,
|
|
|
986 --PercentSimilarMolecules, -k, --kNN.
|
|
|
987
|
|
|
988 --SimilarCountMode *NumOfSimilar | PercentSimilar*
|
|
|
989 Specify method used to count similar molecules found from database
|
|
|
990 molecules for individual reference molecules or set of reference
|
|
|
991 molecules: Find number of similar molecules or percent of similar
|
|
|
992 molecules from database molecules. Possible values: *NumOfSimilar |
|
|
|
993 PercentSimilar*. Default value: *NumOfSimilar*.
|
|
|
994
|
|
|
995 The values for number of similar molecules and percent similar
|
|
|
996 molecules are specified using options -n, NumOfSimilarMolecule and
|
|
|
997 --PercentSimilarMolecules.
|
|
|
998
|
|
|
999 This option is -s, --SearchMode dependent: It corresponds to
|
|
|
1000 dissimilar molecules during *DissimilaritySearch* value of -s,
|
|
|
1001 --SearchMode option.
|
|
|
1002
|
|
|
1003 --SimilarityCutoff *number*
|
|
|
1004 Similarity cutoff value to use during comparison of similarity value
|
|
|
1005 between a pair of database and reference molecules calculated by
|
|
|
1006 similarity comparison methods for fingerprints bit-vector vector
|
|
|
1007 strings data values. Possible values: *Any valid number*. Default
|
|
|
1008 value: *0.75*.
|
|
|
1009
|
|
|
1010 The comparison value between a pair of database and reference
|
|
|
1011 molecule must meet the cutoff criterion as shown below:
|
|
|
1012
|
|
|
1013 SeachMode CutoffCriterion ComparisonValues
|
|
|
1014
|
|
|
1015 Similarity >= Higher value implies high similarity
|
|
|
1016 Dissimilarity <= Lower value implies high dissimilarity
|
|
|
1017
|
|
|
1018 This option is ignored during *No* value of --GroupFusionApplyCutoff
|
|
|
1019 for *MultipleReferences* -m, --mode.
|
|
|
1020
|
|
|
1021 This option is -s, --SearchMode dependent: It corresponds to
|
|
|
1022 dissimilar molecules during *DissimilaritySearch* value of -s,
|
|
|
1023 --SearchMode option.
|
|
|
1024
|
|
|
1025 -v, --VectorComparisonMode *SupportedSimilarityName |
|
|
|
1026 SupportedDistanceName*
|
|
|
1027 Specify what similarity or distance coefficient to use for
|
|
|
1028 calculating similarity between fingerprint vector strings data
|
|
|
1029 values in *ReferenceFingerprintsFile* and *DatabaseFingerprintsFile*
|
|
|
1030 during similarity search. Possible values: *TanimotoSimilairy | ...
|
|
|
1031 | ManhattanDistance | ...*. Default value: *TanimotoSimilarity*.
|
|
|
1032
|
|
|
1033 The value of -v, --VectorComparisonMode, in conjunction with
|
|
|
1034 --VectorComparisonFormulism, decides which type of similarity and
|
|
|
1035 distance coefficient formulism gets used.
|
|
|
1036
|
|
|
1037 The current releases supports the following similarity and distance
|
|
|
1038 coefficients: *CosineSimilarity, CzekanowskiSimilarity,
|
|
|
1039 DiceSimilarity, OchiaiSimilarity, JaccardSimilarity,
|
|
|
1040 SorensonSimilarity, TanimotoSimilarity, CityBlockDistance,
|
|
|
1041 EuclideanDistance, HammingDistance, ManhattanDistance,
|
|
|
1042 SoergelDistance*. These similarity and distance coefficients are
|
|
|
1043 described below.
|
|
|
1044
|
|
|
1045 FingerprintsVector.pm module, used to calculate similarity and
|
|
|
1046 distance coefficients, provides support to perform comparison
|
|
|
1047 between vectors containing three different types of values:
|
|
|
1048
|
|
|
1049 Type I: OrderedNumericalValues
|
|
|
1050
|
|
|
1051 . Size of two vectors are same
|
|
|
1052 . Vectors contain real values in a specific order. For example: MACCS keys
|
|
|
1053 count, Topological pharmnacophore atom pairs and so on.
|
|
|
1054
|
|
|
1055 Type II: UnorderedNumericalValues
|
|
|
1056
|
|
|
1057 . Size of two vectors might not be same
|
|
|
1058 . Vectors contain unordered real value identified by value IDs. For example:
|
|
|
1059 Toplogical atom pairs, Topological atom torsions and so on
|
|
|
1060
|
|
|
1061 Type III: AlphaNumericalValues
|
|
|
1062
|
|
|
1063 . Size of two vectors might not be same
|
|
|
1064 . Vectors contain unordered alphanumerical values. For example: Extended
|
|
|
1065 connectivity fingerprints, atom neighborhood fingerprints.
|
|
|
1066
|
|
|
1067 Before performing similarity or distance calculations between
|
|
|
1068 vectors containing UnorderedNumericalValues or AlphaNumericalValues,
|
|
|
1069 the vectors are transformed into vectors containing unique
|
|
|
1070 OrderedNumericalValues using value IDs for UnorderedNumericalValues
|
|
|
1071 and values itself for AlphaNumericalValues.
|
|
|
1072
|
|
|
1073 Three forms of similarity and distance calculation between two
|
|
|
1074 vectors, specified using --VectorComparisonFormulism option, are
|
|
|
1075 supported: *AlgebraicForm, BinaryForm or SetTheoreticForm*.
|
|
|
1076
|
|
|
1077 For *BinaryForm*, the ordered list of processed final vector values
|
|
|
1078 containing the value or count of each unique value type is simply
|
|
|
1079 converted into a binary vector containing 1s and 0s corresponding to
|
|
|
1080 presence or absence of values before calculating similarity or
|
|
|
1081 distance between two vectors.
|
|
|
1082
|
|
|
1083 For two fingerprint vectors A and B of same size containing
|
|
|
1084 OrderedNumericalValues, let:
|
|
|
1085
|
|
|
1086 N = Number values in A or B
|
|
|
1087
|
|
|
1088 Xa = Values of vector A
|
|
|
1089 Xb = Values of vector B
|
|
|
1090
|
|
|
1091 Xai = Value of ith element in A
|
|
|
1092 Xbi = Value of ith element in B
|
|
|
1093
|
|
|
1094 SUM = Sum of i over N values
|
|
|
1095
|
|
|
1096 For SetTheoreticForm of calculation between two vectors, let:
|
|
|
1097
|
|
|
1098 SetIntersectionXaXb = SUM ( MIN ( Xai, Xbi ) )
|
|
|
1099 SetDifferenceXaXb = SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN ( Xai, Xbi ) )
|
|
|
1100
|
|
|
1101 For BinaryForm of calculation between two vectors, let:
|
|
|
1102
|
|
|
1103 Na = Number of bits set to "1" in A = SUM ( Xai )
|
|
|
1104 Nb = Number of bits set to "1" in B = SUM ( Xbi )
|
|
|
1105 Nc = Number of bits set to "1" in both A and B = SUM ( Xai * Xbi )
|
|
|
1106 Nd = Number of bits set to "0" in both A and B
|
|
|
1107 = SUM ( 1 - Xai - Xbi + Xai * Xbi)
|
|
|
1108
|
|
|
1109 N = Number of bits set to "1" or "0" in A or B = Size of A or B = Na + Nb - Nc + Nd
|
|
|
1110
|
|
|
1111 Additionally, for BinaryForm various values also correspond to:
|
|
|
1112
|
|
|
1113 Na = | Xa |
|
|
|
1114 Nb = | Xb |
|
|
|
1115 Nc = | SetIntersectionXaXb |
|
|
|
1116 Nd = N - | SetDifferenceXaXb |
|
|
|
1117
|
|
|
1118 | SetDifferenceXaXb | = N - Nd = Na + Nb - Nc + Nd - Nd = Na + Nb - Nc
|
|
|
1119 = | Xa | + | Xb | - | SetIntersectionXaXb |
|
|
|
1120
|
|
|
1121 Various similarity and distance coefficients [ Ref 40, Ref 62, Ref
|
|
|
1122 64 ] for a pair of vectors A and B in *AlgebraicForm, BinaryForm and
|
|
|
1123 SetTheoreticForm* are defined as follows:
|
|
|
1124
|
|
|
1125 CityBlockDistance: ( same as HammingDistance and ManhattanDistance)
|
|
|
1126
|
|
|
1127 *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) )
|
|
|
1128
|
|
|
1129 *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc
|
|
|
1130
|
|
|
1131 *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb |
|
|
|
1132 = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) )
|
|
|
1133
|
|
|
1134 CosineSimilarity: ( same as OchiaiSimilarityCoefficient)
|
|
|
1135
|
|
|
1136 *AlgebraicForm*: SUM ( Xai * Xbi ) / SQRT ( SUM ( Xai ** 2) * SUM (
|
|
|
1137 Xbi ** 2) )
|
|
|
1138
|
|
|
1139 *BinaryForm*: Nc / SQRT ( Na * Nb)
|
|
|
1140
|
|
|
1141 *SetTheoreticForm*: | SetIntersectionXaXb | / SQRT ( |Xa| * |Xb| ) =
|
|
|
1142 SUM ( MIN ( Xai, Xbi ) ) / SQRT ( SUM ( Xai ) * SUM ( Xbi ) )
|
|
|
1143
|
|
|
1144 CzekanowskiSimilarity: ( same as DiceSimilarity and
|
|
|
1145 SorensonSimilarity)
|
|
|
1146
|
|
|
1147 *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) +
|
|
|
1148 SUM ( Xbi **2 ) )
|
|
|
1149
|
|
|
1150 *BinaryForm*: 2 * Nc / ( Na + Nb )
|
|
|
1151
|
|
|
1152 *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) =
|
|
|
1153 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) )
|
|
|
1154
|
|
|
1155 DiceSimilarity: ( same as CzekanowskiSimilarity and
|
|
|
1156 SorensonSimilarity)
|
|
|
1157
|
|
|
1158 *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) +
|
|
|
1159 SUM ( Xbi **2 ) )
|
|
|
1160
|
|
|
1161 *BinaryForm*: 2 * Nc / ( Na + Nb )
|
|
|
1162
|
|
|
1163 *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) =
|
|
|
1164 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) )
|
|
|
1165
|
|
|
1166 EuclideanDistance:
|
|
|
1167
|
|
|
1168 *AlgebraicForm*: SQRT ( SUM ( ( ( Xai - Xbi ) ** 2 ) ) )
|
|
|
1169
|
|
|
1170 *BinaryForm*: SQRT ( ( Na - Nc ) + ( Nb - Nc ) ) = SQRT ( Na + Nb -
|
|
|
1171 2 * Nc )
|
|
|
1172
|
|
|
1173 *SetTheoreticForm*: SQRT ( | SetDifferenceXaXb | - |
|
|
|
1174 SetIntersectionXaXb | ) = SQRT ( SUM ( Xai ) + SUM ( Xbi ) - 2 * (
|
|
|
1175 SUM ( MIN ( Xai, Xbi ) ) ) )
|
|
|
1176
|
|
|
1177 HammingDistance: ( same as CityBlockDistance and ManhattanDistance)
|
|
|
1178
|
|
|
1179 *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) )
|
|
|
1180
|
|
|
1181 *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc
|
|
|
1182
|
|
|
1183 *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb |
|
|
|
1184 = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) )
|
|
|
1185
|
|
|
1186 JaccardSimilarity: ( same as TanimotoSimilarity)
|
|
|
1187
|
|
|
1188 *AlgebraicForm*: SUM ( Xai * Xbi ) / ( SUM ( Xai ** 2 ) + SUM ( Xbi
|
|
|
1189 ** 2 ) - SUM ( Xai * Xbi ) )
|
|
|
1190
|
|
|
1191 *BinaryForm*: Nc / ( ( Na - Nc ) + ( Nb - Nc ) + Nc ) = Nc / ( Na +
|
|
|
1192 Nb - Nc )
|
|
|
1193
|
|
|
1194 *SetTheoreticForm*: | SetIntersectionXaXb | / | SetDifferenceXaXb |
|
|
|
1195 = SUM ( MIN ( Xai, Xbi ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN
|
|
|
1196 ( Xai, Xbi ) ) )
|
|
|
1197
|
|
|
1198 ManhattanDistance: ( same as CityBlockDistance and HammingDistance)
|
|
|
1199
|
|
|
1200 *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) )
|
|
|
1201
|
|
|
1202 *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc
|
|
|
1203
|
|
|
1204 *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb |
|
|
|
1205 = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) )
|
|
|
1206
|
|
|
1207 OchiaiSimilarity: ( same as CosineSimilarity)
|
|
|
1208
|
|
|
1209 *AlgebraicForm*: SUM ( Xai * Xbi ) / SQRT ( SUM ( Xai ** 2) * SUM (
|
|
|
1210 Xbi ** 2) )
|
|
|
1211
|
|
|
1212 *BinaryForm*: Nc / SQRT ( Na * Nb)
|
|
|
1213
|
|
|
1214 *SetTheoreticForm*: | SetIntersectionXaXb | / SQRT ( |Xa| * |Xb| ) =
|
|
|
1215 SUM ( MIN ( Xai, Xbi ) ) / SQRT ( SUM ( Xai ) * SUM ( Xbi ) )
|
|
|
1216
|
|
|
1217 SorensonSimilarity: ( same as CzekanowskiSimilarity and
|
|
|
1218 DiceSimilarity)
|
|
|
1219
|
|
|
1220 *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) +
|
|
|
1221 SUM ( Xbi **2 ) )
|
|
|
1222
|
|
|
1223 *BinaryForm*: 2 * Nc / ( Na + Nb )
|
|
|
1224
|
|
|
1225 *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) =
|
|
|
1226 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) )
|
|
|
1227
|
|
|
1228 SoergelDistance:
|
|
|
1229
|
|
|
1230 *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) ) / SUM ( MAX ( Xai, Xbi )
|
|
|
1231 )
|
|
|
1232
|
|
|
1233 *BinaryForm*: 1 - Nc / ( Na + Nb - Nc ) = ( Na + Nb - 2 * Nc ) / (
|
|
|
1234 Na + Nb - Nc )
|
|
|
1235
|
|
|
1236 *SetTheoreticForm*: ( | SetDifferenceXaXb | - | SetIntersectionXaXb
|
|
|
1237 | ) / | SetDifferenceXaXb | = ( SUM ( Xai ) + SUM ( Xbi ) - 2 * (
|
|
|
1238 SUM ( MIN ( Xai, Xbi ) ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM (
|
|
|
1239 MIN ( Xai, Xbi ) ) )
|
|
|
1240
|
|
|
1241 TanimotoSimilarity: ( same as JaccardSimilarity)
|
|
|
1242
|
|
|
1243 *AlgebraicForm*: SUM ( Xai * Xbi ) / ( SUM ( Xai ** 2 ) + SUM ( Xbi
|
|
|
1244 ** 2 ) - SUM ( Xai * Xbi ) )
|
|
|
1245
|
|
|
1246 *BinaryForm*: Nc / ( ( Na - Nc ) + ( Nb - Nc ) + Nc ) = Nc / ( Na +
|
|
|
1247 Nb - Nc )
|
|
|
1248
|
|
|
1249 *SetTheoreticForm*: | SetIntersectionXaXb | / | SetDifferenceXaXb |
|
|
|
1250 = SUM ( MIN ( Xai, Xbi ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN
|
|
|
1251 ( Xai, Xbi ) ) )
|
|
|
1252
|
|
|
1253 --VectorComparisonFormulism *AlgebraicForm | BinaryForm |
|
|
|
1254 SetTheoreticForm*
|
|
|
1255 Specify fingerprints vector comparison formulism to use for
|
|
|
1256 calculation similarity and distance coefficients during -v,
|
|
|
1257 --VectorComparisonMode. Possible values: *AlgebraicForm | BinaryForm
|
|
|
1258 | SetTheoreticForm*. Default value: *AlgebraicForm*.
|
|
|
1259
|
|
|
1260 For fingerprint vector strings containing AlphaNumericalValues data
|
|
|
1261 values - ExtendedConnectivityFingerprints,
|
|
|
1262 AtomNeighborhoodsFingerprints and so on - all three formulism result
|
|
|
1263 in same value during similarity and distance calculations.
|
|
|
1264
|
|
|
1265 -w, --WorkingDir *DirName*
|
|
|
1266 Location of working directory. Default: current directory.
|
|
|
1267
|
|
|
1268 EXAMPLES
|
|
|
1269 To perform similarity search using Tanimoto coefficient by treating all
|
|
|
1270 reference molecules as a set to find 10 most similar database molecules
|
|
|
1271 with application of Max group fusion rule and similarity cutoff to
|
|
|
1272 supported fingerprints strings data in SD fingerprints files present in
|
|
|
1273 a data fields with Fingerprint substring in their labels, and create a
|
|
|
1274 ReferenceFPHexSimilaritySearching.csv file containing sequentially
|
|
|
1275 generated database compound IDs with Cmpd prefix, type:
|
|
|
1276
|
|
|
1277 % SimilaritySearchingFingerprints.pl -o ReferenceSampleFPHex.sdf
|
|
|
1278 DatabaseSampleFPHex.sdf
|
|
|
1279
|
|
|
1280 To perform similarity search using Tanimoto coefficient by treating all
|
|
|
1281 reference molecules as a set to find 10 most similar database molecules
|
|
|
1282 with application of Max group fusion rule and similarity cutoff to
|
|
|
1283 supported fingerprints strings data in FP fingerprints files, and create
|
|
|
1284 a SimilaritySearchResults.csv file containing database compound IDs
|
|
|
1285 retireved from FP file, type:
|
|
|
1286
|
|
|
1287 % SimilaritySearchingFingerprints.pl -r SimilaritySearchResults -o
|
|
|
1288 ReferenceSampleFPBin.fpf DatabaseSampleFPBin.fpf
|
|
|
1289
|
|
|
1290 To perform similarity search using Tanimoto coefficient by treating all
|
|
|
1291 reference molecules as a set to find 10 most similar database database
|
|
|
1292 molecules with application of Max group fusion rule and similarity
|
|
|
1293 cutoff to supported fingerprints strings data in text fingerprints files
|
|
|
1294 present in a column names containing Fingerprint substring in their
|
|
|
1295 names, and create a ReferenceFPHexSimilaritySearching.csv file
|
|
|
1296 containing database compound IDs retireved column name containing
|
|
|
1297 CompoundID substring or sequentially generated compound IDs, type:
|
|
|
1298
|
|
|
1299 % SimilaritySearchingFingerprints.pl -o ReferenceSampleFPCount.csv
|
|
|
1300 DatabaseSampleFPCount.csv
|
|
|
1301
|
|
|
1302 To perform similarity search using Tanimoto coefficient by treating
|
|
|
1303 reference molecules as individual molecules to find 10 most similar
|
|
|
1304 database molecules for each reference molecule with application of
|
|
|
1305 similarity cutoff to supported fingerprints strings data in SD
|
|
|
1306 fingerprints files present in a data fields with Fingerprint substring
|
|
|
1307 in their labels, and create a ReferenceFPHexSimilaritySearching.csv file
|
|
|
1308 containing sequentially generated reference and database compound IDs
|
|
|
1309 with Cmpd prefix, type:
|
|
|
1310
|
|
|
1311 % SimilaritySearchingFingerprints.pl -mode IndividualReference -o
|
|
|
1312 ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
|
|
|
1313
|
|
|
1314 To perform similarity search using Tanimoto coefficient by treating
|
|
|
1315 reference molecules as individual molecules to find 10 most similar
|
|
|
1316 database molecules for each reference molecule with application of
|
|
|
1317 similarity cutoff to supported fingerprints strings data in FP
|
|
|
1318 fingerprints files, and create a ReferenceFPHexSimilaritySearching.csv
|
|
|
1319 file containing references and database compound IDs retireved from FP
|
|
|
1320 file, type:
|
|
|
1321
|
|
|
1322 % SimilaritySearchingFingerprints.pl -mode IndividualReference -o
|
|
|
1323 ReferenceSampleFPHex.fpf DatabaseSampleFPHex.fpf
|
|
|
1324
|
|
|
1325 To perform similarity search using Tanimoto coefficient by treating
|
|
|
1326 reference molecules as individual molecules to find 10 most similar
|
|
|
1327 database molecules for each reference molecule with application of
|
|
|
1328 similarity cutoff to supported fingerprints strings data in text
|
|
|
1329 fingerprints files present in a column names containing Fingerprint
|
|
|
1330 substring in their names, and create a
|
|
|
1331 ReferenceFPHexSimilaritySearching.csv file containing reference and
|
|
|
1332 database compound IDs retrieved column name containing CompoundID
|
|
|
1333 substring or sequentially generated compound IDs, type:
|
|
|
1334
|
|
|
1335 % SimilaritySearchingFingerprints.pl -mode IndividualReference -o
|
|
|
1336 ReferenceSampleFPHex.csv DatabaseSampleFPHex.csv
|
|
|
1337
|
|
|
1338 To perform dissimilarity search using Tanimoto coefficient by treating
|
|
|
1339 all reference molecules as a set to find 10 most dissimilar database
|
|
|
1340 molecules with application of Max group fusion rule and similarity
|
|
|
1341 cutoff to supported fingerprints strings data in SD fingerprints files
|
|
|
1342 present in a data fields with Fingerprint substring in their labels, and
|
|
|
1343 create a ReferenceFPHexSimilaritySearching.csv file containing
|
|
|
1344 sequentially generated database compound IDs with Cmpd prefix, type:
|
|
|
1345
|
|
|
1346 % SimilaritySearchingFingerprints.pl --mode MultipleReferences --SearchMode
|
|
|
1347 DissimilaritySearch -o ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
|
|
|
1348
|
|
|
1349 To perform similarity search using CityBlock distance by treating
|
|
|
1350 reference molecules as individual molecules to find 10 most similar
|
|
|
1351 database molecules for each reference molecule with application of
|
|
|
1352 distance cutoff to supported vector fingerprints strings data in SD
|
|
|
1353 fingerprints files present in a data fields with Fingerprint substring
|
|
|
1354 in their labels, and create a ReferenceFPHexSimilaritySearching.csv file
|
|
|
1355 containing sequentially generated reference and database compound IDs
|
|
|
1356 with Cmpd prefix, type:
|
|
|
1357
|
|
|
1358 % SimilaritySearchingFingerprints.pl -mode IndividualReference
|
|
|
1359 --VectorComparisonMode CityBlockDistance --VectorComparisonFormulism
|
|
|
1360 AlgebraicForm --DistanceCutoff 10 -o
|
|
|
1361 ReferenceSampleFPCount.sdf DatabaseSampleFPCount.sdf
|
|
|
1362
|
|
|
1363 To perform similarity search using Tanimoto coefficient by treating all
|
|
|
1364 reference molecules as a set to find 100 most similar database molecules
|
|
|
1365 with application of Mean group fusion rule to to top 10 reference
|
|
|
1366 molecules with in similarity cutoff of 0.75 to supported fingerprints
|
|
|
1367 strings data in FP fingerprints files, and create a
|
|
|
1368 ReferenceFPHexSimilaritySearching.csv file containing database compound
|
|
|
1369 IDs retrieved from FP file, type:
|
|
|
1370
|
|
|
1371 % SimilaritySearchingFingerprints.pl --mode MultipleReferences --SearchMode
|
|
|
1372 SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity
|
|
|
1373 --GroupFusionRule Mean --GroupFusionApplyCutoff Yes --kNN 10
|
|
|
1374 --SimilarityCutoff 0.75 --SimilarCountMode NumOfSimilar
|
|
|
1375 --NumOfSimilarMolecules 100 -o
|
|
|
1376 ReferenceSampleFPHex.fpf DatabaseSampleFPHex.fpf
|
|
|
1377
|
|
|
1378 To perform similarity search using Tanimoto coefficient by treating
|
|
|
1379 reference molecules as individual molecules to find 2 percent of most
|
|
|
1380 similar database molecules for each reference molecule with application
|
|
|
1381 of similarity cutoff of 0.85 to supported fingerprints strings data in
|
|
|
1382 text fingerprints files present in specific columns and create a
|
|
|
1383 ReferenceFPHexSimilaritySearching.csv file containing reference and
|
|
|
1384 database compoundIDs retrieved from specific columns, type:
|
|
|
1385
|
|
|
1386 % SimilaritySearchingFingerprints.pl --mode IndividualReference --SearchMode
|
|
|
1387 SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity
|
|
|
1388 --ReferenceColMode ColLabel --ReferenceFingerprintsCol Fingerprints
|
|
|
1389 --ReferenceCompoundIDCol CompoundID --DatabaseColMode Collabel
|
|
|
1390 --DatabaseCompoundIDCol CompoundID --DatabaseFingerprintsCol
|
|
|
1391 Fingerprints --SimilarityCutoff 0.85 --SimilarCountMode PercentSimilar
|
|
|
1392 --PercentSimilarMolecules 2 -o
|
|
|
1393 ReferenceSampleFPHex.csv DatabaseSampleFPHex.csv
|
|
|
1394
|
|
|
1395 To perform similarity search using Tanimoto coefficient by treating
|
|
|
1396 reference molecules as individual molecules to find top 50 most similar
|
|
|
1397 database molecules for each reference molecule with application of
|
|
|
1398 similarity cutoff of 0.85 to supported fingerprints strings data in SD
|
|
|
1399 fingerprints files present in specific data fields and create both
|
|
|
1400 ReferenceFPHexSimilaritySearching.csv and
|
|
|
1401 ReferenceFPHexSimilaritySearching.sdf files containing reference and
|
|
|
1402 database compoundIDs retrieved from specific data fields, type:
|
|
|
1403
|
|
|
1404 % SimilaritySearchingFingerprints.pl --mode IndividualReference --SearchMode
|
|
|
1405 SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity
|
|
|
1406 --ReferenceFingerprintsField Fingerprints
|
|
|
1407 --DatabaseFingerprintsField Fingerprints
|
|
|
1408 --ReferenceCompoundIDMode DataField --ReferenceCompoundIDField CmpdID
|
|
|
1409 --DatabaseCompoundIDMode DataField --DatabaseCompoundIDField CmpdID
|
|
|
1410 --SimilarityCutoff 0.85 --SimilarCountMode NumOfSimilar
|
|
|
1411 --NumOfSimilarMolecules 50 --output both -o
|
|
|
1412 ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
|
|
|
1413
|
|
|
1414 To perform similarity search using Tanimoto coefficient by treating
|
|
|
1415 reference molecules as individual molecules to find 1 percent of most
|
|
|
1416 similar database molecules for each reference molecule with application
|
|
|
1417 of similarity cutoff to supported fingerprints strings data in SD
|
|
|
1418 fingerprints files present in specific data field labels, and create
|
|
|
1419 both ReferenceFPHexSimilaritySearching.csv
|
|
|
1420 ReferenceFPHexSimilaritySearching.sdf files containing reference and
|
|
|
1421 database compound IDs retrieved from specific data field labels along
|
|
|
1422 with other specific data for database molecules, type:
|
|
|
1423
|
|
|
1424 % SimilaritySearchingFingerprints.pl --mode IndividualReference --SearchMode
|
|
|
1425 SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity
|
|
|
1426 --ReferenceFingerprintsField Fingerprints
|
|
|
1427 --DatabaseFingerprintsField Fingerprints
|
|
|
1428 --ReferenceCompoundIDMode DataField --ReferenceCompoundIDField CmpdID
|
|
|
1429 --DatabaseCompoundIDMode DataField --DatabaseCompoundIDField CmpdID
|
|
|
1430 --DatabaseDataFieldsMode Specify --DatabaseDataFields "TPSA,SLogP"
|
|
|
1431 --SimilarityCutoff 0.75 --SimilarCountMode PercentSimilar
|
|
|
1432 --PercentSimilarMolecules 1 --output both --OutDelim comma --quote Yes
|
|
|
1433 --precision 3 -o ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf
|
|
|
1434
|
|
|
1435 AUTHOR
|
|
|
1436 Manish Sud <msud@san.rr.com>
|
|
|
1437
|
|
|
1438 SEE ALSO
|
|
|
1439 InfoFingerprintsFiles.pl, SimilarityMatricesFingerprints.pl,
|
|
|
1440 AtomNeighborhoodsFingerprints.pl, ExtendedConnectivityFingerprints.pl,
|
|
|
1441 MACCSKeysFingerprints.pl, PathLengthFingerprints.pl,
|
|
|
1442 TopologicalAtomPairsFingerprints.pl,
|
|
|
1443 TopologicalAtomTorsionsFingerprints.pl,
|
|
|
1444 TopologicalPharmacophoreAtomPairsFingerprints.pl,
|
|
|
1445 TopologicalPharmacophoreAtomTripletsFingerprints.pl
|
|
|
1446
|
|
|
1447 COPYRIGHT
|
|
|
1448 Copyright (C) 2015 Manish Sud. All rights reserved.
|
|
|
1449
|
|
|
1450 This file is part of MayaChemTools.
|
|
|
1451
|
|
|
1452 MayaChemTools is free software; you can redistribute it and/or modify it
|
|
|
1453 under the terms of the GNU Lesser General Public License as published by
|
|
|
1454 the Free Software Foundation; either version 3 of the License, or (at
|
|
|
1455 your option) any later version.
|
|
|
1456
|
