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1 NAME
2 SimilaritySearchingFingerprints.pl - Perform similarity search using
3 fingerprints strings data in SD, FP and CSV/TSV text file(s)
4
5 SYNOPSIS
6 SimilaritySearchingFingerprints.pl ReferenceFPFile DatabaseFPFile
7
8 SimilaritySearchingFingerprints.pl [--alpha *number*] [--beta *number*]
9 [-b, --BitVectorComparisonMode *TanimotoSimilarity | TverskySimilarity |
10 ...*] [--DatabaseColMode *ColNum | ColLabel*] [--DatabaseCompoundIDCol
11 *col number | col name*] [--DatabaseCompoundIDPrefix *text*]
12 [--DatabaseCompoundIDField *DataFieldName*] [--DatabaseCompoundIDMode
13 *DataField | MolName | LabelPrefix | MolNameOrLabelPrefix*]
14 [--DatabaseDataCols *"DataColNum1, DataColNum2,... " | DataColLabel1,
15 DataCoLabel2,... "*] [--DatabaseDataColsMode *All | Specify |
16 CompoundID*] [--DatabaseDataFields *"FieldLabel1, FieldLabel2,... "*]
17 [--DatabaseDataFieldsMode *All | Common | Specify | CompoundID*]
18 [--DatabaseFingerprintsCol *col number | col name*]
19 [--DatabaseFingerprintsField *FieldLabel*] []--DistanceCutoff *number*]
20 [-d, --detail *InfoLevel*] [-f, --fast] [--FingerprintsMode *AutoDetect
21 | FingerprintsBitVectorString | FingerprintsVectorString*] [-g,
22 --GroupFusionRule *Max, Mean, Median, Min, Sum, Euclidean*]
23 [--GroupFusionApplyCutoff *Yes | No*] [-h, --help] [--InDelim *comma |
24 semicolon*] [-k, --KNN *all | number*] [-m, --mode *IndividualReference
25 | MultipleReferences*] [-n, --NumOfSimilarMolecules *number*]
26 [--OutDelim *comma | tab | semicolon*] [--output *SD | text | both*]
27 [-o, --overwrite] [-p, --PercentSimilarMolecules *number*] [--precision
28 *number*] [-q, --quote *Yes | No*] [--ReferenceColMode *ColNum |
29 ColLabel*] [--ReferenceCompoundIDCol *col number | col name*]
30 [--ReferenceCompoundIDPrefix *text*] [--ReferenceCompoundIDField
31 *DataFieldName*] [--ReferenceCompoundIDMode *DataField | MolName |
32 LabelPrefix | MolNameOrLabelPrefix*] [--ReferenceFingerprintsCol *col
33 number | col name*] [--ReferenceFingerprintsField *FieldLabel*] [-r,
34 --root *RootName*] [-s, --SearchMode *SimilaritySearch |
35 DissimilaritySearch*] [--SimilarCountMode *NumOfSimilar |
36 PercentSimilar*] [--SimilarityCutoff *number*] [-v,
37 --VectorComparisonMode *TanimotoSimilairy | ... | ManhattanDistance |
38 ...*] [--VectorComparisonFormulism *AlgebraicForm | BinaryForm |
39 SetTheoreticForm*] [-w, --WorkingDir dirname] ReferenceFingerprintsFile
40 DatabaseFingerprintsFile
41
42 DESCRIPTION
43 Perform molecular similarity search [ Ref 94-113 ] using fingerprint
44 bit-vector or vector strings data in *SD, FP, or CSV/TSV text* files
45 corresponding to *ReferenceFingerprintsFile* and
46 *DatabaseFingerprintsFile*, and generate SD and CSV/TSV text file(s)
47 containing database molecules which are similar to reference
48 molecule(s). The reference molecules are also referred to as query or
49 seed molecules and database molecules as target molecules in the
50 literature.
51
52 The current release of MayaChemTools supports two types of similarity
53 search modes: *IndividualReference or MultipleReferences*. For default
54 value of *MultipleReferences* for -m, --mode option, reference molecules
55 are considered as a set and -g, --GroupFusionRule is used to calculate
56 similarity of a database molecule against reference molecules set. The
57 group fusion rule is also referred to as data fusion of consensus
58 scoring in the literature. However, for *IndividualReference* value of
59 -m, --mode option, reference molecules are treated as individual
60 molecules and each reference molecule is compared against a database
61 molecule by itself to identify similar molecules.
62
63 The molecular dissimilarity search can also be performed using
64 *DissimilaritySearch* value for -s, --SearchMode option. During
65 dissimilarity search or usage of distance comparison coefficient in
66 similarity similarity search, the meaning of fingerprints comparison
67 value is automatically reversed as shown below:
68
69 SeachMode ComparisonCoefficient ResultsSort ComparisonValues
70
71 Similarity SimilarityCoefficient Descending Higher value imples
72 high similarity
73 Similarity DistanceCoefficient Ascending Lower value implies
74 high similarity
75
76 Dissimilarity SimilarityCoefficient Ascending Lower value implies
77 high dissimilarity
78 Dissimilarity DistanceCoefficient Descending Higher value implies
79 high dissimilarity
80
81 During *IndividualReference* value of -m, --Mode option for similarity
82 search, fingerprints bit-vector or vector string of each reference
83 molecule is compared with database molecules using specified similarity
84 or distance coefficients to identify most similar molecules for each
85 reference molecule. Based on value of --SimilarCountMode, up to --n,
86 --NumOfSimilarMolecules or -p, --PercentSimilarMolecules at specified
87 --SimilarityCutoff or --DistanceCutoff are identified for each reference
88 molecule.
89
90 During *MultipleReferences* value -m, --mode option for similarity
91 search, all reference molecules are considered as a set and -g,
92 --GroupFusionRule is used to calculate similarity of a database molecule
93 against reference molecules set either using all reference molecules or
94 number of k-nearest neighbors (k-NN) to a database molecule specified
95 using -k, --kNN. The fingerprints bit-vector or vector string of each
96 reference molecule in a set is compared with a database molecule using a
97 similarity or distance coefficient specified via -b,
98 --BitVectorComparisonMode or -v, --VectorComparisonMode. The reference
99 molecules whose comparison values with a database molecule fall outside
100 specified --SimilarityCutoff or --DistanceCutoff are ignored during
101 *Yes* value of --GroupFusionApplyCutoff. The specified -g,
102 --GroupFusionRule is applied to -k, --kNN reference molecules to
103 calculate final similarity value between a database molecule and
104 reference molecules set.
105
106 The input fingerprints *SD, FP, or Text (CSV/TSV)* files for
107 *ReferenceFingerprintsFile* and *DatabaseTextFile* must contain valid
108 fingerprint bit-vector or vector strings data corresponding to same type
109 of fingerprints.
110
111 The valid fingerprints *SDFile* extensions are *.sdf* and *.sd*. The
112 valid fingerprints *FPFile* extensions are *.fpf* and *.fp*. The valid
113 fingerprints *TextFile (CSV/TSV)* extensions are *.csv* and *.tsv* for
114 comma/semicolon and tab delimited text files respectively. The --indelim
115 option determines the format of *TextFile*. Any file which doesn't
116 correspond to the format indicated by --indelim option is ignored.
117
118 Example of *FP* file containing fingerprints bit-vector string data:
119
120 #
121 # Package = MayaChemTools 7.4
122 # ReleaseDate = Oct 21, 2010
123 #
124 # TimeStamp = Mon Mar 7 15:14:01 2011
125 #
126 # FingerprintsStringType = FingerprintsBitVector
127 #
128 # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
129 # Size = 1024
130 # BitStringFormat = HexadecimalString
131 # BitsOrder = Ascending
132 #
133 Cmpd1 9c8460989ec8a49913991a6603130b0a19e8051c89184414953800cc21510...
134 Cmpd2 000000249400840040100042011001001980410c000000001010088001120...
135 ... ...
136 ... ..
137
138 Example of *FP* file containing fingerprints vector string data:
139
140 #
141 # Package = MayaChemTools 7.4
142 # ReleaseDate = Oct 21, 2010
143 #
144 # TimeStamp = Mon Mar 7 15:14:01 2011
145 #
146 # FingerprintsStringType = FingerprintsVector
147 #
148 # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:...
149 # VectorStringFormat = IDsAndValuesString
150 # VectorValuesType = NumericalValues
151 #
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:
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...;
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
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 ...
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
157 O C CC=O CCCC CCCN CCCO CCNC CNC=N CNC=O CNCN CCCC=O CCCCC CCCCN CC...;
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
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 ...
160 ... ...
161 ... ...
162
163 Example of *SD* file containing fingerprints bit-vector string data:
164
165 ... ...
166 ... ...
167 $$$$
168 ... ...
169 ... ...
170 ... ...
171 41 44 0 0 0 0 0 0 0 0999 V2000
172 -3.3652 1.4499 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
173 ... ...
174 2 3 1 0 0 0 0
175 ... ...
176 M END
177 > <CmpdID>
178 Cmpd1
179
180 > <PathLengthFingerprints>
181 FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLengt
182 h1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a49913991a66
183 03130b0a19e8051c89184414953800cc2151082844a201042800130860308e8204d4028
184 00831048940e44281c00060449a5000ac80c894114e006321264401600846c050164462
185 08190410805000304a10205b0100e04c0038ba0fad0209c0ca8b1200012268b61c0026a
186 aa0660a11014a011d46
187
188 $$$$
189 ... ...
190 ... ...
191
192 Example of CSV *TextFile* containing fingerprints bit-vector string
193 data:
194
195 "CompoundID","PathLengthFingerprints"
196 "Cmpd1","FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes
197 :MinLength1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a4
198 9913991a6603130b0a19e8051c89184414953800cc2151082844a20104280013086030
199 8e8204d402800831048940e44281c00060449a5000ac80c894114e006321264401..."
200 ... ...
201 ... ...
202
203 The current release of MayaChemTools supports the following types of
204 fingerprint bit-vector and vector strings:
205
206 FingerprintsVector;AtomNeighborhoods:AtomicInvariantsAtomTypes:MinRadi
207 us0:MaxRadius2;41;AlphaNumericalValues;ValuesString;NR0-C.X1.BO1.H3-AT
208 C1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-ATC1 NR0-C.X
209 1.BO1.H3-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-A
210 TC1 NR0-C.X2.BO2.H2-ATC1:NR1-C.X2.BO2.H2-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2
211 -C.X2.BO2.H2-ATC1:NR2-N.X3.BO3-ATC1:NR2-O.X1.BO1.H1-ATC1 NR0-C.X2.B...
212
213 FingerprintsVector;AtomTypesCount:AtomicInvariantsAtomTypes:ArbitraryS
214 ize;10;NumericalValues;IDsAndValuesString;C.X1.BO1.H3 C.X2.BO2.H2 C.X2
215 .BO3.H1 C.X3.BO3.H1 C.X3.BO4 F.X1.BO1 N.X2.BO2.H1 N.X3.BO3 O.X1.BO1.H1
216 O.X1.BO2;2 4 14 3 10 1 1 1 3 2
217
218 FingerprintsVector;AtomTypesCount:SLogPAtomTypes:ArbitrarySize;16;Nume
219 ricalValues;IDsAndValuesString;C1 C10 C11 C14 C18 C20 C21 C22 C5 CS F
220 N11 N4 O10 O2 O9;5 1 1 1 14 4 2 1 2 2 1 1 1 1 3 1
221
222 FingerprintsVector;AtomTypesCount:SLogPAtomTypes:FixedSize;67;OrderedN
223 umericalValues;IDsAndValuesString;C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C
224 12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 CS N1 N
225 2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 N13 N14 NS O1 O2 O3 O4 O5 O6 O7 O8
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
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...
228
229 FingerprintsVector;EStateIndicies:ArbitrarySize;11;NumericalValues;IDs
230 AndValuesString;SaaCH SaasC SaasN SdO SdssC SsCH3 SsF SsOH SssCH2 SssN
231 H SsssCH;24.778 4.387 1.993 25.023 -1.435 3.975 14.006 29.759 -0.073 3
232 .024 -2.270
233
234 FingerprintsVector;EStateIndicies:FixedSize;87;OrderedNumericalValues;
235 ValuesString;0 0 0 0 0 0 0 3.975 0 -0.073 0 0 24.778 -2.270 0 0 -1.435
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
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
238 0 0 0 0 0 0 0 0 0 0 0 0 0 0
239
240 FingerprintsVector;ExtendedConnectivity:AtomicInvariantsAtomTypes:Radi
241 us2;60;AlphaNumericalValues;ValuesString;73555770 333564680 352413391
242 666191900 1001270906 1371674323 1481469939 1977749791 2006158649 21414
243 08799 49532520 64643108 79385615 96062769 273726379 564565671 85514103
244 5 906706094 988546669 1018231313 1032696425 1197507444 1331250018 1338
245 532734 1455473691 1607485225 1609687129 1631614296 1670251330 17303...
246
247 FingerprintsVector;ExtendedConnectivityCount:AtomicInvariantsAtomTypes
248 :Radius2;60;NumericalValues;IDsAndValuesString;73555770 333564680 3524
249 13391 666191900 1001270906 1371674323 1481469939 1977749791 2006158649
250 2141408799 49532520 64643108 79385615 96062769 273726379 564565671...;
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
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
253
254 FingerprintsBitVector;ExtendedConnectivityBits:AtomicInvariantsAtomTyp
255 es:Radius2;1024;BinaryString;Ascending;0000000000000000000000000000100
256 0000000001010000000110000011000000000000100000000000000000000000100001
257 1000000110000000000000000000000000010011000000000000000000000000010000
258 0000000000000000000000000010000000000000000001000000000000000000000000
259 0000000000010000100001000000000000101000000000000000100000000000000...
260
261 FingerprintsVector;ExtendedConnectivity:FunctionalClassAtomTypes:Radiu
262 s2;57;AlphaNumericalValues;ValuesString;24769214 508787397 850393286 8
263 62102353 981185303 1231636850 1649386610 1941540674 263599683 32920567
264 1 571109041 639579325 683993318 723853089 810600886 885767127 90326012
265 7 958841485 981022393 1126908698 1152248391 1317567065 1421489994 1455
266 632544 1557272891 1826413669 1983319256 2015750777 2029559552 20404...
267
268 FingerprintsVector;ExtendedConnectivity:EStateAtomTypes:Radius2;62;Alp
269 haNumericalValues;ValuesString;25189973 528584866 662581668 671034184
270 926543080 1347067490 1738510057 1759600920 2034425745 2097234755 21450
271 44754 96779665 180364292 341712110 345278822 386540408 387387308 50430
272 1706 617094135 771528807 957666640 997798220 1158349170 1291258082 134
273 1138533 1395329837 1420277211 1479584608 1486476397 1487556246 1566...
274
275 FingerprintsBitVector;MACCSKeyBits;166;BinaryString;Ascending;00000000
276 0000000000000000000000000000000001001000010010000000010010000000011100
277 0100101010111100011011000100110110000011011110100110111111111111011111
278 11111111111110111000
279
280 FingerprintsBitVector;MACCSKeyBits;322;BinaryString;Ascending;11101011
281 1110011111100101111111000111101100110000000000000011100010000000000000
282 0000000000000000000000000000000000000000000000101000000000000000000000
283 0000000000000000000000000000000000000000000000000000000000000000000000
284 0000000000000000000000000000000000000011000000000000000000000000000000
285 0000000000000000000000000000000000000000
286
287 FingerprintsVector;MACCSKeyCount;166;OrderedNumericalValues;ValuesStri
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
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
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
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
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
293
294 FingerprintsVector;MACCSKeyCount;322;OrderedNumericalValues;ValuesStri
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
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
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
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
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 ...
300
301 FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLeng
302 th1:MaxLength8;1024;BinaryString;Ascending;001000010011010101011000110
303 0100010101011000101001011100110001000010001001101000001001001001001000
304 0010110100000111001001000001001010100100100000000011000000101001011100
305 0010000001000101010100000100111100110111011011011000000010110111001101
306 0101100011000000010001000011000010100011101100001000001000100000000...
307
308 FingerprintsVector;PathLengthCount:AtomicInvariantsAtomTypes:MinLength
309 1:MaxLength8;432;NumericalValues;IDsAndValuesPairsString;C.X1.BO1.H3 2
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
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
312 2 C.X2.BO2.H2C.X2.BO2.H2 1 C.X2.BO2.H2C.X3.BO3.H1 4 C.X2.BO2.H2C.X3.BO
313 4 1 C.X2.BO2.H2N.X3.BO3 1 C.X2.BO3.H1:C.X2.BO3.H1 10 C.X2.BO3.H1:C....
314
315 FingerprintsVector;PathLengthCount:MMFF94AtomTypes:MinLength1:MaxLengt
316 h8;463;NumericalValues;IDsAndValuesPairsString;C5A 2 C5B 2 C=ON 1 CB 1
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
318 5 2 C5ACB 1 C5ACR 1 C5B:C5B 1 C5BC=ON 1 C5BCB 1 C=ON=O=CN 1 C=ONNC=O 1
319 CB:CB 18 CBF 1 CBNC=O 1 COO=O=CO 1 COOCR 1 COOOC=O 1 CRCR 7 CRN5 1 CR
320 OR 2 C5A:C5B:C5B 2 C5A:C5BC=ON 1 C5A:C5BCB 1 C5A:N5:C5A 1 C5A:N5CR ...
321
322 FingerprintsVector;TopologicalAtomPairs:AtomicInvariantsAtomTypes:MinD
323 istance1:MaxDistance10;223;NumericalValues;IDsAndValuesString;C.X1.BO1
324 .H3-D1-C.X3.BO3.H1 C.X2.BO2.H2-D1-C.X2.BO2.H2 C.X2.BO2.H2-D1-C.X3.BO3.
325 H1 C.X2.BO2.H2-D1-C.X3.BO4 C.X2.BO2.H2-D1-N.X3.BO3 C.X2.BO3.H1-D1-...;
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
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...
328
329 FingerprintsVector;TopologicalAtomPairs:FunctionalClassAtomTypes:MinDi
330 stance1:MaxDistance10;144;NumericalValues;IDsAndValuesString;Ar-D1-Ar
331 Ar-D1-Ar.HBA Ar-D1-HBD Ar-D1-Hal Ar-D1-None Ar.HBA-D1-None HBA-D1-NI H
332 BA-D1-None HBA.HBD-D1-NI HBA.HBD-D1-None HBD-D1-None NI-D1-None No...;
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
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 ...
335
336 FingerprintsVector;TopologicalAtomTorsions:AtomicInvariantsAtomTypes;3
337 3;NumericalValues;IDsAndValuesString;C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4-
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
339 2.H2-C.X3.BO3.H1-C.X2.BO2.H2 C.X2.BO2.H2-C.X2.BO2.H2-C.X3.BO3.H1-O...;
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
341
342 FingerprintsVector;TopologicalAtomTorsions:EStateAtomTypes;36;Numerica
343 lValues;IDsAndValuesString;aaCH-aaCH-aaCH-aaCH aaCH-aaCH-aaCH-aasC aaC
344 H-aaCH-aasC-aaCH aaCH-aaCH-aasC-aasC aaCH-aaCH-aasC-sF aaCH-aaCH-aasC-
345 ssNH aaCH-aasC-aasC-aasC aaCH-aasC-aasC-aasN aaCH-aasC-ssNH-dssC a...;
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
347
348 FingerprintsVector;TopologicalAtomTriplets:AtomicInvariantsAtomTypes:M
349 inDistance1:MaxDistance10;3096;NumericalValues;IDsAndValuesString;C.X1
350 .BO1.H3-D1-C.X1.BO1.H3-D1-C.X3.BO3.H1-D2 C.X1.BO1.H3-D1-C.X2.BO2.H2-D1
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
352 -C.X2.BO2.H2-D4-C.X2.BO2.H2-D5 C.X1.BO1.H3-D1-C.X2.BO2.H2-D6-C.X3....;
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
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...
355
356 FingerprintsVector;TopologicalAtomTriplets:SYBYLAtomTypes:MinDistance1
357 :MaxDistance10;2332;NumericalValues;IDsAndValuesString;C.2-D1-C.2-D9-C
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-
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
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.
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...
362
363 FingerprintsVector;TopologicalPharmacophoreAtomPairs:ArbitrarySize:Min
364 Distance1:MaxDistance10;54;NumericalValues;IDsAndValuesString;H-D1-H H
365 -D1-NI HBA-D1-NI HBD-D1-NI H-D2-H H-D2-HBA H-D2-HBD HBA-D2-HBA HBA-D2-
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
367 BA H-D4-HBD HBA-D4-HBA HBA-D4-HBD HBD-D4-HBD H-D5-H H-D5-HBA H-D5-...;
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
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
370
371 FingerprintsVector;TopologicalPharmacophoreAtomPairs:FixedSize:MinDist
372 ance1:MaxDistance10;150;OrderedNumericalValues;ValuesString;18 0 0 1 0
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
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
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
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...
377
378 FingerprintsVector;TopologicalPharmacophoreAtomTriplets:ArbitrarySize:
379 MinDistance1:MaxDistance10;696;NumericalValues;IDsAndValuesString;Ar1-
380 Ar1-Ar1 Ar1-Ar1-H1 Ar1-Ar1-HBA1 Ar1-Ar1-HBD1 Ar1-H1-H1 Ar1-H1-HBA1 Ar1
381 -H1-HBD1 Ar1-HBA1-HBD1 H1-H1-H1 H1-H1-HBA1 H1-H1-HBD1 H1-HBA1-HBA1 H1-
382 HBA1-HBD1 H1-HBA1-NI1 H1-HBD1-NI1 HBA1-HBA1-NI1 HBA1-HBD1-NI1 Ar1-...;
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
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
385 119 123 24 15 185 202 41 25 22 17 3 5 85 95 18 11 23 17 3 1 1 6 4 ...
386
387 FingerprintsVector;TopologicalPharmacophoreAtomTriplets:FixedSize:MinD
388 istance1:MaxDistance10;2692;OrderedNumericalValues;ValuesString;46 106
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
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
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
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 ...
393
394 OPTIONS
395 --alpha *number*
396 Value of alpha parameter for calculating *Tversky* similarity
397 coefficient specified for -b, --BitVectorComparisonMode option. It
398 corresponds to weights assigned for bits set to "1" in a pair of
399 fingerprint bit-vectors during the calculation of similarity
400 coefficient. Possible values: *0 to 1*. Default value: <0.5>.
401
402 --beta *number*
403 Value of beta parameter for calculating *WeightedTanimoto* and
404 *WeightedTversky* similarity coefficients specified for -b,
405 --BitVectorComparisonMode option. It is used to weight the
406 contributions of bits set to "0" during the calculation of
407 similarity coefficients. Possible values: *0 to 1*. Default value of
408 <1> makes *WeightedTanimoto* and *WeightedTversky* equivalent to
409 *Tanimoto* and *Tversky*.
410
411 -b, --BitVectorComparisonMode *TanimotoSimilarity | TverskySimilarity |
412 ...*
413 Specify what similarity coefficient to use for calculating
414 similarity between fingerprints bit-vector string data values in
415 *ReferenceFingerprintsFile* and *DatabaseFingerprintsFile* during
416 similarity search. Possible values: *TanimotoSimilarity |
417 TverskySimilarity | ...*. Default: *TanimotoSimilarity*
418
419 The current release supports the following similarity coefficients:
420 *BaroniUrbaniSimilarity, BuserSimilarity, CosineSimilarity,
421 DiceSimilarity, DennisSimilarity, ForbesSimilarity,
422 FossumSimilarity, HamannSimilarity, JacardSimilarity,
423 Kulczynski1Similarity, Kulczynski2Similarity, MatchingSimilarity,
424 McConnaugheySimilarity, OchiaiSimilarity, PearsonSimilarity,
425 RogersTanimotoSimilarity, RussellRaoSimilarity, SimpsonSimilarity,
426 SkoalSneath1Similarity, SkoalSneath2Similarity,
427 SkoalSneath3Similarity, TanimotoSimilarity, TverskySimilarity,
428 YuleSimilarity, WeightedTanimotoSimilarity,
429 WeightedTverskySimilarity*. These similarity coefficients are
430 described below.
431
432 For two fingerprint bit-vectors A and B of same size, let:
433
434 Na = Number of bits set to "1" in A
435 Nb = Number of bits set to "1" in B
436 Nc = Number of bits set to "1" in both A and B
437 Nd = Number of bits set to "0" in both A and B
438
439 Nt = Number of bits set to "1" or "0" in A or B (Size of A or B)
440 Nt = Na + Nb - Nc + Nd
441
442 Na - Nc = Number of bits set to "1" in A but not in B
443 Nb - Nc = Number of bits set to "1" in B but not in A
444
445 Then, various similarity coefficients [ Ref. 40 - 42 ] for a pair of
446 bit-vectors A and B are defined as follows:
447
448 *BaroniUrbaniSimilarity*: ( SQRT( Nc * Nd ) + Nc ) / ( SQRT ( Nc *
449 Nd ) + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as Buser )
450
451 *BuserSimilarity*: ( SQRT ( Nc * Nd ) + Nc ) / ( SQRT ( Nc * Nd ) +
452 Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as BaroniUrbani )
453
454 *CosineSimilarity*: Nc / SQRT ( Na * Nb ) (same as Ochiai)
455
456 *DiceSimilarity*: (2 * Nc) / ( Na + Nb )
457
458 *DennisSimilarity*: ( Nc * Nd - ( ( Na - Nc ) * ( Nb - Nc ) ) ) /
459 SQRT ( Nt * Na * Nb)
460
461 *ForbesSimilarity*: ( Nt * Nc ) / ( Na * Nb )
462
463 *FossumSimilarity*: ( Nt * ( ( Nc - 1/2 ) ** 2 ) / ( Na * Nb )
464
465 *HamannSimilarity*: ( ( Nc + Nd ) - ( Na - Nc ) - ( Nb - Nc ) ) / Nt
466
467 *JaccardSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / (
468 Na + Nb - Nc ) (same as Tanimoto)
469
470 *Kulczynski1Similarity*: Nc / ( ( Na - Nc ) + ( Nb - Nc) ) = Nc / (
471 Na + Nb - 2Nc )
472
473 *Kulczynski2Similarity*: ( ( Nc / 2 ) * ( 2 * Nc + ( Na - Nc ) + (
474 Nb - Nc) ) ) / ( ( Nc + ( Na - Nc ) ) * ( Nc + ( Nb - Nc ) ) ) = 0.5
475 * ( Nc / Na + Nc / Nb )
476
477 *MatchingSimilarity*: ( Nc + Nd ) / Nt
478
479 *McConnaugheySimilarity*: ( Nc ** 2 - ( Na - Nc ) * ( Nb - Nc) ) / (
480 Na * Nb )
481
482 *OchiaiSimilarity*: Nc / SQRT ( Na * Nb ) (same as Cosine)
483
484 *PearsonSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) /
485 SQRT ( Na * Nb * ( Na - Nc + Nd ) * ( Nb - Nc + Nd ) )
486
487 *RogersTanimotoSimilarity*: ( Nc + Nd ) / ( ( Na - Nc) + ( Nb - Nc)
488 + Nt) = ( Nc + Nd ) / ( Na + Nb - 2Nc + Nt)
489
490 *RussellRaoSimilarity*: Nc / Nt
491
492 *SimpsonSimilarity*: Nc / MIN ( Na, Nb)
493
494 *SkoalSneath1Similarity*: Nc / ( Nc + 2 * ( Na - Nc) + 2 * ( Nb -
495 Nc) ) = Nc / ( 2 * Na + 2 * Nb - 3 * Nc )
496
497 *SkoalSneath2Similarity*: ( 2 * Nc + 2 * Nd ) / ( Nc + Nd + Nt )
498
499 *SkoalSneath3Similarity*: ( Nc + Nd ) / ( ( Na - Nc ) + ( Nb - Nc )
500 ) = ( Nc + Nd ) / ( Na + Nb - 2 * Nc )
501
502 *TanimotoSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc /
503 ( Na + Nb - Nc ) (same as Jaccard)
504
505 *TverskySimilarity*: Nc / ( alpha * ( Na - Nc ) + ( 1 - alpha) * (
506 Nb - Nc) + Nc ) = Nc / ( alpha * ( Na - Nb ) + Nb)
507
508 *YuleSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) ) /
509 ( ( Nc * Nd ) + ( ( Na - Nc ) * ( Nb - Nc ) ) )
510
511 Values of Tanimoto/Jaccard and Tversky coefficients are dependent on
512 only those bit which are set to "1" in both A and B. In order to
513 take into account all bit positions, modified versions of Tanimoto [
514 Ref. 42 ] and Tversky [ Ref. 43 ] have been developed.
515
516 Let:
517
518 Na' = Number of bits set to "0" in A
519 Nb' = Number of bits set to "0" in B
520 Nc' = Number of bits set to "0" in both A and B
521
522 Tanimoto': Nc' / ( ( Na' - Nc') + ( Nb' - Nc' ) + Nc' ) = Nc' / (
523 Na' + Nb' - Nc' )
524
525 Tversky': Nc' / ( alpha * ( Na' - Nc' ) + ( 1 - alpha) * ( Nb' - Nc'
526 ) + Nc' ) = Nc' / ( alpha * ( Na' - Nb' ) + Nb')
527
528 Then:
529
530 *WeightedTanimotoSimilarity* = beta * Tanimoto + (1 - beta) *
531 Tanimoto'
532
533 *WeightedTverskySimilarity* = beta * Tversky + (1 - beta) * Tversky'
534
535 --DatabaseColMode *ColNum | ColLabel*
536 Specify how columns are identified in database fingerprints
537 *TextFile*: using column number or column label. Possible values:
538 *ColNum or ColLabel*. Default value: *ColNum*.
539
540 --DatabaseCompoundIDCol *col number | col name*
541 This value is --DatabaseColMode mode specific. It specifies column
542 to use for retrieving compound ID from database fingerprints
543 *TextFile* during similarity and dissimilarity search for output SD
544 and CSV/TSV text files. Possible values: *col number or col label*.
545 Default value: *first column containing the word compoundID in its
546 column label or sequentially generated IDs*.
547
548 This is only used for *CompoundID* value of --DatabaseDataColsMode
549 option.
550
551 --DatabaseCompoundIDPrefix *text*
552 Specify compound ID prefix to use during sequential generation of
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