Mercurial > repos > deepakjadmin > mayatool3_test2
diff docs/scripts/txt/SimilaritySearchingFingerprints.txt @ 0:4816e4a8ae95 draft default tip
Uploaded
| author | deepakjadmin |
|---|---|
| date | Wed, 20 Jan 2016 09:23:18 -0500 |
| parents | |
| children |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/docs/scripts/txt/SimilaritySearchingFingerprints.txt Wed Jan 20 09:23:18 2016 -0500 @@ -0,0 +1,1456 @@ +NAME + SimilaritySearchingFingerprints.pl - Perform similarity search using + fingerprints strings data in SD, FP and CSV/TSV text file(s) + +SYNOPSIS + SimilaritySearchingFingerprints.pl ReferenceFPFile DatabaseFPFile + + SimilaritySearchingFingerprints.pl [--alpha *number*] [--beta *number*] + [-b, --BitVectorComparisonMode *TanimotoSimilarity | TverskySimilarity | + ...*] [--DatabaseColMode *ColNum | ColLabel*] [--DatabaseCompoundIDCol + *col number | col name*] [--DatabaseCompoundIDPrefix *text*] + [--DatabaseCompoundIDField *DataFieldName*] [--DatabaseCompoundIDMode + *DataField | MolName | LabelPrefix | MolNameOrLabelPrefix*] + [--DatabaseDataCols *"DataColNum1, DataColNum2,... " | DataColLabel1, + DataCoLabel2,... "*] [--DatabaseDataColsMode *All | Specify | + CompoundID*] [--DatabaseDataFields *"FieldLabel1, FieldLabel2,... "*] + [--DatabaseDataFieldsMode *All | Common | Specify | CompoundID*] + [--DatabaseFingerprintsCol *col number | col name*] + [--DatabaseFingerprintsField *FieldLabel*] []--DistanceCutoff *number*] + [-d, --detail *InfoLevel*] [-f, --fast] [--FingerprintsMode *AutoDetect + | FingerprintsBitVectorString | FingerprintsVectorString*] [-g, + --GroupFusionRule *Max, Mean, Median, Min, Sum, Euclidean*] + [--GroupFusionApplyCutoff *Yes | No*] [-h, --help] [--InDelim *comma | + semicolon*] [-k, --KNN *all | number*] [-m, --mode *IndividualReference + | MultipleReferences*] [-n, --NumOfSimilarMolecules *number*] + [--OutDelim *comma | tab | semicolon*] [--output *SD | text | both*] + [-o, --overwrite] [-p, --PercentSimilarMolecules *number*] [--precision + *number*] [-q, --quote *Yes | No*] [--ReferenceColMode *ColNum | + ColLabel*] [--ReferenceCompoundIDCol *col number | col name*] + [--ReferenceCompoundIDPrefix *text*] [--ReferenceCompoundIDField + *DataFieldName*] [--ReferenceCompoundIDMode *DataField | MolName | + LabelPrefix | MolNameOrLabelPrefix*] [--ReferenceFingerprintsCol *col + number | col name*] [--ReferenceFingerprintsField *FieldLabel*] [-r, + --root *RootName*] [-s, --SearchMode *SimilaritySearch | + DissimilaritySearch*] [--SimilarCountMode *NumOfSimilar | + PercentSimilar*] [--SimilarityCutoff *number*] [-v, + --VectorComparisonMode *TanimotoSimilairy | ... | ManhattanDistance | + ...*] [--VectorComparisonFormulism *AlgebraicForm | BinaryForm | + SetTheoreticForm*] [-w, --WorkingDir dirname] ReferenceFingerprintsFile + DatabaseFingerprintsFile + +DESCRIPTION + Perform molecular similarity search [ Ref 94-113 ] using fingerprint + bit-vector or vector strings data in *SD, FP, or CSV/TSV text* files + corresponding to *ReferenceFingerprintsFile* and + *DatabaseFingerprintsFile*, and generate SD and CSV/TSV text file(s) + containing database molecules which are similar to reference + molecule(s). The reference molecules are also referred to as query or + seed molecules and database molecules as target molecules in the + literature. + + The current release of MayaChemTools supports two types of similarity + search modes: *IndividualReference or MultipleReferences*. For default + value of *MultipleReferences* for -m, --mode option, reference molecules + are considered as a set and -g, --GroupFusionRule is used to calculate + similarity of a database molecule against reference molecules set. The + group fusion rule is also referred to as data fusion of consensus + scoring in the literature. However, for *IndividualReference* value of + -m, --mode option, reference molecules are treated as individual + molecules and each reference molecule is compared against a database + molecule by itself to identify similar molecules. + + The molecular dissimilarity search can also be performed using + *DissimilaritySearch* value for -s, --SearchMode option. During + dissimilarity search or usage of distance comparison coefficient in + similarity similarity search, the meaning of fingerprints comparison + value is automatically reversed as shown below: + + SeachMode ComparisonCoefficient ResultsSort ComparisonValues + + Similarity SimilarityCoefficient Descending Higher value imples + high similarity + Similarity DistanceCoefficient Ascending Lower value implies + high similarity + + Dissimilarity SimilarityCoefficient Ascending Lower value implies + high dissimilarity + Dissimilarity DistanceCoefficient Descending Higher value implies + high dissimilarity + + During *IndividualReference* value of -m, --Mode option for similarity + search, fingerprints bit-vector or vector string of each reference + molecule is compared with database molecules using specified similarity + or distance coefficients to identify most similar molecules for each + reference molecule. Based on value of --SimilarCountMode, up to --n, + --NumOfSimilarMolecules or -p, --PercentSimilarMolecules at specified + --SimilarityCutoff or --DistanceCutoff are identified for each reference + molecule. + + During *MultipleReferences* value -m, --mode option for similarity + search, all reference molecules are considered as a set and -g, + --GroupFusionRule is used to calculate similarity of a database molecule + against reference molecules set either using all reference molecules or + number of k-nearest neighbors (k-NN) to a database molecule specified + using -k, --kNN. The fingerprints bit-vector or vector string of each + reference molecule in a set is compared with a database molecule using a + similarity or distance coefficient specified via -b, + --BitVectorComparisonMode or -v, --VectorComparisonMode. The reference + molecules whose comparison values with a database molecule fall outside + specified --SimilarityCutoff or --DistanceCutoff are ignored during + *Yes* value of --GroupFusionApplyCutoff. The specified -g, + --GroupFusionRule is applied to -k, --kNN reference molecules to + calculate final similarity value between a database molecule and + reference molecules set. + + The input fingerprints *SD, FP, or Text (CSV/TSV)* files for + *ReferenceFingerprintsFile* and *DatabaseTextFile* must contain valid + fingerprint bit-vector or vector strings data corresponding to same type + of fingerprints. + + The valid fingerprints *SDFile* extensions are *.sdf* and *.sd*. The + valid fingerprints *FPFile* extensions are *.fpf* and *.fp*. The valid + fingerprints *TextFile (CSV/TSV)* extensions are *.csv* and *.tsv* for + comma/semicolon and tab delimited text files respectively. The --indelim + option determines the format of *TextFile*. Any file which doesn't + correspond to the format indicated by --indelim option is ignored. + + Example of *FP* file containing fingerprints bit-vector string data: + + # + # Package = MayaChemTools 7.4 + # ReleaseDate = Oct 21, 2010 + # + # TimeStamp = Mon Mar 7 15:14:01 2011 + # + # FingerprintsStringType = FingerprintsBitVector + # + # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:... + # Size = 1024 + # BitStringFormat = HexadecimalString + # BitsOrder = Ascending + # + Cmpd1 9c8460989ec8a49913991a6603130b0a19e8051c89184414953800cc21510... + Cmpd2 000000249400840040100042011001001980410c000000001010088001120... + ... ... + ... .. + + Example of *FP* file containing fingerprints vector string data: + + # + # Package = MayaChemTools 7.4 + # ReleaseDate = Oct 21, 2010 + # + # TimeStamp = Mon Mar 7 15:14:01 2011 + # + # FingerprintsStringType = FingerprintsVector + # + # Description = PathLengthBits:AtomicInvariantsAtomTypes:MinLength1:... + # VectorStringFormat = IDsAndValuesString + # VectorValuesType = NumericalValues + # + 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: + 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...; + 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 + 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 ... + 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 + O C CC=O CCCC CCCN CCCO CCNC CNC=N CNC=O CNCN CCCC=O CCCCC CCCCN CC...; + 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 + 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 ... + ... ... + ... ... + + Example of *SD* file containing fingerprints bit-vector string data: + + ... ... + ... ... + $$$$ + ... ... + ... ... + ... ... + 41 44 0 0 0 0 0 0 0 0999 V2000 + -3.3652 1.4499 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 + ... ... + 2 3 1 0 0 0 0 + ... ... + M END + > <CmpdID> + Cmpd1 + + > <PathLengthFingerprints> + FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLengt + h1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a49913991a66 + 03130b0a19e8051c89184414953800cc2151082844a201042800130860308e8204d4028 + 00831048940e44281c00060449a5000ac80c894114e006321264401600846c050164462 + 08190410805000304a10205b0100e04c0038ba0fad0209c0ca8b1200012268b61c0026a + aa0660a11014a011d46 + + $$$$ + ... ... + ... ... + + Example of CSV *TextFile* containing fingerprints bit-vector string + data: + + "CompoundID","PathLengthFingerprints" + "Cmpd1","FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes + :MinLength1:MaxLength8;1024;HexadecimalString;Ascending;9c8460989ec8a4 + 9913991a6603130b0a19e8051c89184414953800cc2151082844a20104280013086030 + 8e8204d402800831048940e44281c00060449a5000ac80c894114e006321264401..." + ... ... + ... ... + + The current release of MayaChemTools supports the following types of + fingerprint bit-vector and vector strings: + + FingerprintsVector;AtomNeighborhoods:AtomicInvariantsAtomTypes:MinRadi + us0:MaxRadius2;41;AlphaNumericalValues;ValuesString;NR0-C.X1.BO1.H3-AT + C1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-ATC1 NR0-C.X + 1.BO1.H3-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2-C.X1.BO1.H3-ATC1:NR2-C.X3.BO4-A + TC1 NR0-C.X2.BO2.H2-ATC1:NR1-C.X2.BO2.H2-ATC1:NR1-C.X3.BO3.H1-ATC1:NR2 + -C.X2.BO2.H2-ATC1:NR2-N.X3.BO3-ATC1:NR2-O.X1.BO1.H1-ATC1 NR0-C.X2.B... + + FingerprintsVector;AtomTypesCount:AtomicInvariantsAtomTypes:ArbitraryS + ize;10;NumericalValues;IDsAndValuesString;C.X1.BO1.H3 C.X2.BO2.H2 C.X2 + .BO3.H1 C.X3.BO3.H1 C.X3.BO4 F.X1.BO1 N.X2.BO2.H1 N.X3.BO3 O.X1.BO1.H1 + O.X1.BO2;2 4 14 3 10 1 1 1 3 2 + + FingerprintsVector;AtomTypesCount:SLogPAtomTypes:ArbitrarySize;16;Nume + ricalValues;IDsAndValuesString;C1 C10 C11 C14 C18 C20 C21 C22 C5 CS F + N11 N4 O10 O2 O9;5 1 1 1 14 4 2 1 2 2 1 1 1 1 3 1 + + FingerprintsVector;AtomTypesCount:SLogPAtomTypes:FixedSize;67;OrderedN + umericalValues;IDsAndValuesString;C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C + 12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26 C27 CS N1 N + 2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 N13 N14 NS O1 O2 O3 O4 O5 O6 O7 O8 + 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 + 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... + + FingerprintsVector;EStateIndicies:ArbitrarySize;11;NumericalValues;IDs + AndValuesString;SaaCH SaasC SaasN SdO SdssC SsCH3 SsF SsOH SssCH2 SssN + H SsssCH;24.778 4.387 1.993 25.023 -1.435 3.975 14.006 29.759 -0.073 3 + .024 -2.270 + + FingerprintsVector;EStateIndicies:FixedSize;87;OrderedNumericalValues; + ValuesString;0 0 0 0 0 0 0 3.975 0 -0.073 0 0 24.778 -2.270 0 0 -1.435 + 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 + 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 + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 + + FingerprintsVector;ExtendedConnectivity:AtomicInvariantsAtomTypes:Radi + us2;60;AlphaNumericalValues;ValuesString;73555770 333564680 352413391 + 666191900 1001270906 1371674323 1481469939 1977749791 2006158649 21414 + 08799 49532520 64643108 79385615 96062769 273726379 564565671 85514103 + 5 906706094 988546669 1018231313 1032696425 1197507444 1331250018 1338 + 532734 1455473691 1607485225 1609687129 1631614296 1670251330 17303... + + FingerprintsVector;ExtendedConnectivityCount:AtomicInvariantsAtomTypes + :Radius2;60;NumericalValues;IDsAndValuesString;73555770 333564680 3524 + 13391 666191900 1001270906 1371674323 1481469939 1977749791 2006158649 + 2141408799 49532520 64643108 79385615 96062769 273726379 564565671...; + 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 + 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 + + FingerprintsBitVector;ExtendedConnectivityBits:AtomicInvariantsAtomTyp + es:Radius2;1024;BinaryString;Ascending;0000000000000000000000000000100 + 0000000001010000000110000011000000000000100000000000000000000000100001 + 1000000110000000000000000000000000010011000000000000000000000000010000 + 0000000000000000000000000010000000000000000001000000000000000000000000 + 0000000000010000100001000000000000101000000000000000100000000000000... + + FingerprintsVector;ExtendedConnectivity:FunctionalClassAtomTypes:Radiu + s2;57;AlphaNumericalValues;ValuesString;24769214 508787397 850393286 8 + 62102353 981185303 1231636850 1649386610 1941540674 263599683 32920567 + 1 571109041 639579325 683993318 723853089 810600886 885767127 90326012 + 7 958841485 981022393 1126908698 1152248391 1317567065 1421489994 1455 + 632544 1557272891 1826413669 1983319256 2015750777 2029559552 20404... + + FingerprintsVector;ExtendedConnectivity:EStateAtomTypes:Radius2;62;Alp + haNumericalValues;ValuesString;25189973 528584866 662581668 671034184 + 926543080 1347067490 1738510057 1759600920 2034425745 2097234755 21450 + 44754 96779665 180364292 341712110 345278822 386540408 387387308 50430 + 1706 617094135 771528807 957666640 997798220 1158349170 1291258082 134 + 1138533 1395329837 1420277211 1479584608 1486476397 1487556246 1566... + + FingerprintsBitVector;MACCSKeyBits;166;BinaryString;Ascending;00000000 + 0000000000000000000000000000000001001000010010000000010010000000011100 + 0100101010111100011011000100110110000011011110100110111111111111011111 + 11111111111110111000 + + FingerprintsBitVector;MACCSKeyBits;322;BinaryString;Ascending;11101011 + 1110011111100101111111000111101100110000000000000011100010000000000000 + 0000000000000000000000000000000000000000000000101000000000000000000000 + 0000000000000000000000000000000000000000000000000000000000000000000000 + 0000000000000000000000000000000000000011000000000000000000000000000000 + 0000000000000000000000000000000000000000 + + FingerprintsVector;MACCSKeyCount;166;OrderedNumericalValues;ValuesStri + 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 + 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 + 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 + 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 + 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 + + FingerprintsVector;MACCSKeyCount;322;OrderedNumericalValues;ValuesStri + 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 + 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 + 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 + 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 + 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 ... + + FingerprintsBitVector;PathLengthBits:AtomicInvariantsAtomTypes:MinLeng + th1:MaxLength8;1024;BinaryString;Ascending;001000010011010101011000110 + 0100010101011000101001011100110001000010001001101000001001001001001000 + 0010110100000111001001000001001010100100100000000011000000101001011100 + 0010000001000101010100000100111100110111011011011000000010110111001101 + 0101100011000000010001000011000010100011101100001000001000100000000... + + FingerprintsVector;PathLengthCount:AtomicInvariantsAtomTypes:MinLength + 1:MaxLength8;432;NumericalValues;IDsAndValuesPairsString;C.X1.BO1.H3 2 + 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 + 2.BO2.H1 1 N.X3.BO3 1 O.X1.BO1.H1 3 O.X1.BO2 2 C.X1.BO1.H3C.X3.BO3.H1 + 2 C.X2.BO2.H2C.X2.BO2.H2 1 C.X2.BO2.H2C.X3.BO3.H1 4 C.X2.BO2.H2C.X3.BO + 4 1 C.X2.BO2.H2N.X3.BO3 1 C.X2.BO3.H1:C.X2.BO3.H1 10 C.X2.BO3.H1:C.... + + FingerprintsVector;PathLengthCount:MMFF94AtomTypes:MinLength1:MaxLengt + h8;463;NumericalValues;IDsAndValuesPairsString;C5A 2 C5B 2 C=ON 1 CB 1 + 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 + 5 2 C5ACB 1 C5ACR 1 C5B:C5B 1 C5BC=ON 1 C5BCB 1 C=ON=O=CN 1 C=ONNC=O 1 + CB:CB 18 CBF 1 CBNC=O 1 COO=O=CO 1 COOCR 1 COOOC=O 1 CRCR 7 CRN5 1 CR + OR 2 C5A:C5B:C5B 2 C5A:C5BC=ON 1 C5A:C5BCB 1 C5A:N5:C5A 1 C5A:N5CR ... + + FingerprintsVector;TopologicalAtomPairs:AtomicInvariantsAtomTypes:MinD + istance1:MaxDistance10;223;NumericalValues;IDsAndValuesString;C.X1.BO1 + .H3-D1-C.X3.BO3.H1 C.X2.BO2.H2-D1-C.X2.BO2.H2 C.X2.BO2.H2-D1-C.X3.BO3. + H1 C.X2.BO2.H2-D1-C.X3.BO4 C.X2.BO2.H2-D1-N.X3.BO3 C.X2.BO3.H1-D1-...; + 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 + 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... + + FingerprintsVector;TopologicalAtomPairs:FunctionalClassAtomTypes:MinDi + stance1:MaxDistance10;144;NumericalValues;IDsAndValuesString;Ar-D1-Ar + Ar-D1-Ar.HBA Ar-D1-HBD Ar-D1-Hal Ar-D1-None Ar.HBA-D1-None HBA-D1-NI H + BA-D1-None HBA.HBD-D1-NI HBA.HBD-D1-None HBD-D1-None NI-D1-None No...; + 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 + 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 ... + + FingerprintsVector;TopologicalAtomTorsions:AtomicInvariantsAtomTypes;3 + 3;NumericalValues;IDsAndValuesString;C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4- + C.X3.BO4 C.X1.BO1.H3-C.X3.BO3.H1-C.X3.BO4-N.X3.BO3 C.X2.BO2.H2-C.X2.BO + 2.H2-C.X3.BO3.H1-C.X2.BO2.H2 C.X2.BO2.H2-C.X2.BO2.H2-C.X3.BO3.H1-O...; + 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 + + FingerprintsVector;TopologicalAtomTorsions:EStateAtomTypes;36;Numerica + lValues;IDsAndValuesString;aaCH-aaCH-aaCH-aaCH aaCH-aaCH-aaCH-aasC aaC + H-aaCH-aasC-aaCH aaCH-aaCH-aasC-aasC aaCH-aaCH-aasC-sF aaCH-aaCH-aasC- + ssNH aaCH-aasC-aasC-aasC aaCH-aasC-aasC-aasN aaCH-aasC-ssNH-dssC a...; + 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 + + FingerprintsVector;TopologicalAtomTriplets:AtomicInvariantsAtomTypes:M + inDistance1:MaxDistance10;3096;NumericalValues;IDsAndValuesString;C.X1 + .BO1.H3-D1-C.X1.BO1.H3-D1-C.X3.BO3.H1-D2 C.X1.BO1.H3-D1-C.X2.BO2.H2-D1 + 0-C.X3.BO4-D9 C.X1.BO1.H3-D1-C.X2.BO2.H2-D3-N.X3.BO3-D4 C.X1.BO1.H3-D1 + -C.X2.BO2.H2-D4-C.X2.BO2.H2-D5 C.X1.BO1.H3-D1-C.X2.BO2.H2-D6-C.X3....; + 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 + 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... + + FingerprintsVector;TopologicalAtomTriplets:SYBYLAtomTypes:MinDistance1 + :MaxDistance10;2332;NumericalValues;IDsAndValuesString;C.2-D1-C.2-D9-C + .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- + 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 + -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. + 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... + + FingerprintsVector;TopologicalPharmacophoreAtomPairs:ArbitrarySize:Min + Distance1:MaxDistance10;54;NumericalValues;IDsAndValuesString;H-D1-H H + -D1-NI HBA-D1-NI HBD-D1-NI H-D2-H H-D2-HBA H-D2-HBD HBA-D2-HBA HBA-D2- + 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 + BA H-D4-HBD HBA-D4-HBA HBA-D4-HBD HBD-D4-HBD H-D5-H H-D5-HBA H-D5-...; + 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 + 3 4 1 37 10 8 1 35 10 9 3 3 1 28 7 7 4 18 16 12 5 1 2 1 + + FingerprintsVector;TopologicalPharmacophoreAtomPairs:FixedSize:MinDist + ance1:MaxDistance10;150;OrderedNumericalValues;ValuesString;18 0 0 1 0 + 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 + 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 + 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 + 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... + + FingerprintsVector;TopologicalPharmacophoreAtomTriplets:ArbitrarySize: + MinDistance1:MaxDistance10;696;NumericalValues;IDsAndValuesString;Ar1- + Ar1-Ar1 Ar1-Ar1-H1 Ar1-Ar1-HBA1 Ar1-Ar1-HBD1 Ar1-H1-H1 Ar1-H1-HBA1 Ar1 + -H1-HBD1 Ar1-HBA1-HBD1 H1-H1-H1 H1-H1-HBA1 H1-H1-HBD1 H1-HBA1-HBA1 H1- + HBA1-HBD1 H1-HBA1-NI1 H1-HBD1-NI1 HBA1-HBA1-NI1 HBA1-HBD1-NI1 Ar1-...; + 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 + 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 + 119 123 24 15 185 202 41 25 22 17 3 5 85 95 18 11 23 17 3 1 1 6 4 ... + + FingerprintsVector;TopologicalPharmacophoreAtomTriplets:FixedSize:MinD + istance1:MaxDistance10;2692;OrderedNumericalValues;ValuesString;46 106 + 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 + 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 + 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 + 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 ... + +OPTIONS + --alpha *number* + Value of alpha parameter for calculating *Tversky* similarity + coefficient specified for -b, --BitVectorComparisonMode option. It + corresponds to weights assigned for bits set to "1" in a pair of + fingerprint bit-vectors during the calculation of similarity + coefficient. Possible values: *0 to 1*. Default value: <0.5>. + + --beta *number* + Value of beta parameter for calculating *WeightedTanimoto* and + *WeightedTversky* similarity coefficients specified for -b, + --BitVectorComparisonMode option. It is used to weight the + contributions of bits set to "0" during the calculation of + similarity coefficients. Possible values: *0 to 1*. Default value of + <1> makes *WeightedTanimoto* and *WeightedTversky* equivalent to + *Tanimoto* and *Tversky*. + + -b, --BitVectorComparisonMode *TanimotoSimilarity | TverskySimilarity | + ...* + Specify what similarity coefficient to use for calculating + similarity between fingerprints bit-vector string data values in + *ReferenceFingerprintsFile* and *DatabaseFingerprintsFile* during + similarity search. Possible values: *TanimotoSimilarity | + TverskySimilarity | ...*. Default: *TanimotoSimilarity* + + The current release supports the following similarity coefficients: + *BaroniUrbaniSimilarity, BuserSimilarity, CosineSimilarity, + DiceSimilarity, DennisSimilarity, ForbesSimilarity, + FossumSimilarity, HamannSimilarity, JacardSimilarity, + Kulczynski1Similarity, Kulczynski2Similarity, MatchingSimilarity, + McConnaugheySimilarity, OchiaiSimilarity, PearsonSimilarity, + RogersTanimotoSimilarity, RussellRaoSimilarity, SimpsonSimilarity, + SkoalSneath1Similarity, SkoalSneath2Similarity, + SkoalSneath3Similarity, TanimotoSimilarity, TverskySimilarity, + YuleSimilarity, WeightedTanimotoSimilarity, + WeightedTverskySimilarity*. These similarity coefficients are + described below. + + For two fingerprint bit-vectors A and B of same size, let: + + Na = Number of bits set to "1" in A + Nb = Number of bits set to "1" in B + Nc = Number of bits set to "1" in both A and B + Nd = Number of bits set to "0" in both A and B + + Nt = Number of bits set to "1" or "0" in A or B (Size of A or B) + Nt = Na + Nb - Nc + Nd + + Na - Nc = Number of bits set to "1" in A but not in B + Nb - Nc = Number of bits set to "1" in B but not in A + + Then, various similarity coefficients [ Ref. 40 - 42 ] for a pair of + bit-vectors A and B are defined as follows: + + *BaroniUrbaniSimilarity*: ( SQRT( Nc * Nd ) + Nc ) / ( SQRT ( Nc * + Nd ) + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as Buser ) + + *BuserSimilarity*: ( SQRT ( Nc * Nd ) + Nc ) / ( SQRT ( Nc * Nd ) + + Nc + ( Na - Nc ) + ( Nb - Nc ) ) ( same as BaroniUrbani ) + + *CosineSimilarity*: Nc / SQRT ( Na * Nb ) (same as Ochiai) + + *DiceSimilarity*: (2 * Nc) / ( Na + Nb ) + + *DennisSimilarity*: ( Nc * Nd - ( ( Na - Nc ) * ( Nb - Nc ) ) ) / + SQRT ( Nt * Na * Nb) + + *ForbesSimilarity*: ( Nt * Nc ) / ( Na * Nb ) + + *FossumSimilarity*: ( Nt * ( ( Nc - 1/2 ) ** 2 ) / ( Na * Nb ) + + *HamannSimilarity*: ( ( Nc + Nd ) - ( Na - Nc ) - ( Nb - Nc ) ) / Nt + + *JaccardSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / ( + Na + Nb - Nc ) (same as Tanimoto) + + *Kulczynski1Similarity*: Nc / ( ( Na - Nc ) + ( Nb - Nc) ) = Nc / ( + Na + Nb - 2Nc ) + + *Kulczynski2Similarity*: ( ( Nc / 2 ) * ( 2 * Nc + ( Na - Nc ) + ( + Nb - Nc) ) ) / ( ( Nc + ( Na - Nc ) ) * ( Nc + ( Nb - Nc ) ) ) = 0.5 + * ( Nc / Na + Nc / Nb ) + + *MatchingSimilarity*: ( Nc + Nd ) / Nt + + *McConnaugheySimilarity*: ( Nc ** 2 - ( Na - Nc ) * ( Nb - Nc) ) / ( + Na * Nb ) + + *OchiaiSimilarity*: Nc / SQRT ( Na * Nb ) (same as Cosine) + + *PearsonSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) / + SQRT ( Na * Nb * ( Na - Nc + Nd ) * ( Nb - Nc + Nd ) ) + + *RogersTanimotoSimilarity*: ( Nc + Nd ) / ( ( Na - Nc) + ( Nb - Nc) + + Nt) = ( Nc + Nd ) / ( Na + Nb - 2Nc + Nt) + + *RussellRaoSimilarity*: Nc / Nt + + *SimpsonSimilarity*: Nc / MIN ( Na, Nb) + + *SkoalSneath1Similarity*: Nc / ( Nc + 2 * ( Na - Nc) + 2 * ( Nb - + Nc) ) = Nc / ( 2 * Na + 2 * Nb - 3 * Nc ) + + *SkoalSneath2Similarity*: ( 2 * Nc + 2 * Nd ) / ( Nc + Nd + Nt ) + + *SkoalSneath3Similarity*: ( Nc + Nd ) / ( ( Na - Nc ) + ( Nb - Nc ) + ) = ( Nc + Nd ) / ( Na + Nb - 2 * Nc ) + + *TanimotoSimilarity*: Nc / ( ( Na - Nc) + ( Nb - Nc ) + Nc ) = Nc / + ( Na + Nb - Nc ) (same as Jaccard) + + *TverskySimilarity*: Nc / ( alpha * ( Na - Nc ) + ( 1 - alpha) * ( + Nb - Nc) + Nc ) = Nc / ( alpha * ( Na - Nb ) + Nb) + + *YuleSimilarity*: ( ( Nc * Nd ) - ( ( Na - Nc ) * ( Nb - Nc ) ) ) / + ( ( Nc * Nd ) + ( ( Na - Nc ) * ( Nb - Nc ) ) ) + + Values of Tanimoto/Jaccard and Tversky coefficients are dependent on + only those bit which are set to "1" in both A and B. In order to + take into account all bit positions, modified versions of Tanimoto [ + Ref. 42 ] and Tversky [ Ref. 43 ] have been developed. + + Let: + + Na' = Number of bits set to "0" in A + Nb' = Number of bits set to "0" in B + Nc' = Number of bits set to "0" in both A and B + + Tanimoto': Nc' / ( ( Na' - Nc') + ( Nb' - Nc' ) + Nc' ) = Nc' / ( + Na' + Nb' - Nc' ) + + Tversky': Nc' / ( alpha * ( Na' - Nc' ) + ( 1 - alpha) * ( Nb' - Nc' + ) + Nc' ) = Nc' / ( alpha * ( Na' - Nb' ) + Nb') + + Then: + + *WeightedTanimotoSimilarity* = beta * Tanimoto + (1 - beta) * + Tanimoto' + + *WeightedTverskySimilarity* = beta * Tversky + (1 - beta) * Tversky' + + --DatabaseColMode *ColNum | ColLabel* + Specify how columns are identified in database fingerprints + *TextFile*: using column number or column label. Possible values: + *ColNum or ColLabel*. Default value: *ColNum*. + + --DatabaseCompoundIDCol *col number | col name* + This value is --DatabaseColMode mode specific. It specifies column + to use for retrieving compound ID from database fingerprints + *TextFile* during similarity and dissimilarity search for output SD + and CSV/TSV text files. Possible values: *col number or col label*. + Default value: *first column containing the word compoundID in its + column label or sequentially generated IDs*. + + This is only used for *CompoundID* value of --DatabaseDataColsMode + option. + + --DatabaseCompoundIDPrefix *text* + Specify compound ID prefix to use during sequential generation of + compound IDs for database fingerprints *SDFile* and *TextFile*. + Default value: *Cmpd*. The default value generates compound IDs + which look like Cmpd<Number>. + + For database fingerprints *SDFile*, this value is only used during + *LabelPrefix | MolNameOrLabelPrefix* values of + --DatabaseCompoundIDMode option; otherwise, it's ignored. + + Examples for *LabelPrefix* or *MolNameOrLabelPrefix* value of + --DatabaseCompoundIDMode: + + Compound + + The values specified above generates compound IDs which correspond + to Compound<Number> instead of default value of Cmpd<Number>. + + --DatabaseCompoundIDField *DataFieldName* + Specify database fingerprints *SDFile* datafield label for + generating compound IDs. This value is only used during *DataField* + value of --DatabaseCompoundIDMode option. + + Examples for *DataField* value of --DatabaseCompoundIDMode: + + MolID + ExtReg + + --DatabaseCompoundIDMode *DataField | MolName | LabelPrefix | + MolNameOrLabelPrefix* + Specify how to generate compound IDs from database fingerprints + *SDFile* during similarity and dissimilarity search for output SD + and CSV/TSV text files: use a *SDFile* datafield value; use molname + line from *SDFile*; generate a sequential ID with specific prefix; + use combination of both MolName and LabelPrefix with usage of + LabelPrefix values for empty molname lines. + + Possible values: *DataField | MolName | LabelPrefix | + MolNameOrLabelPrefix*. Default: *LabelPrefix*. + + For *MolNameAndLabelPrefix* value of --DatabaseCompoundIDMode, + molname line in *SDFile* takes precedence over sequential compound + IDs generated using *LabelPrefix* and only empty molname values are + replaced with sequential compound IDs. + + This is only used for *CompoundID* value of --DatabaseDataFieldsMode + option. + + --DatabaseDataCols *"DataColNum1,DataColNum2,... " | + DataColLabel1,DataCoLabel2,... "* + This value is --DatabaseColMode mode specific. It is a comma + delimited list of database fingerprints *TextFile* data column + numbers or labels to extract and write to SD and CSV/TSV text files + along with other information for *SD | text | both* values of + --output option. + + This is only used for *Specify* value of --DatabaseDataColsMode + option. + + Examples: + + 1,2,3 + CompoundName,MolWt + + --DatabaseDataColsMode *All | Specify | CompoundID* + Specify how data columns from database fingerprints *TextFile* are + transferred to output SD and CSV/TSV text files along with other + information for *SD | text | both* values of --output option: + transfer all data columns; extract specified data columns; generate + a compound ID database compound prefix. Possible values: *All | + Specify | CompoundID*. Default value: *CompoundID*. + + --DatabaseDataFields *"FieldLabel1,FieldLabel2,... "* + Comma delimited list of database fingerprints *SDFile* data fields + to extract and write to SD and CSV/TSV text files along with other + information for *SD | text | both* values of --output option. + + This is only used for *Specify* value of --DatabaseDataFieldsMode + option. + + Examples: + + Extreg + MolID,CompoundName + + --DatabaseDataFieldsMode *All | Common | Specify | CompoundID* + Specify how data fields from database fingerprints *SDFile* are + transferred to output SD and CSV/TSV text files along with other + information for *SD | text | both* values of --output option: + transfer all SD data field; transfer SD data files common to all + compounds; extract specified data fields; generate a compound ID + using molname line, a compound prefix, or a combination of both. + Possible values: *All | Common | specify | CompoundID*. Default + value: *CompoundID*. + + --DatabaseFingerprintsCol *col number | col name* + This value is --DatabaseColMode specific. It specifies fingerprints + column to use during similarity and dissimilarity search for + database fingerprints *TextFile*. Possible values: *col number or + col label*. Default value: *first column containing the word + Fingerprints in its column label*. + + --DatabaseFingerprintsField *FieldLabel* + Fingerprints field label to use during similarity and dissimilarity + search for database fingerprints *SDFile*. Default value: *first + data field label containing the word Fingerprints in its label* + + --DistanceCutoff *number* + Distance cutoff value to use during comparison of distance value + between a pair of database and reference molecule calculated by + distance comparison methods for fingerprints vector string data + values. Possible values: *Any valid number*. Default value: *10*. + + The comparison value between a pair of database and reference + molecule must meet the cutoff criterion as shown below: + + SeachMode CutoffCriterion ComparisonValues + + Similarity <= Lower value implies high similarity + Dissimilarity >= Higher value implies high dissimilarity + + This option is only used during distance coefficients values of -v, + --VectorComparisonMode option. + + This option is ignored during *No* value of --GroupFusionApplyCutoff + for *MultipleReferences* -m, --mode. + + -d, --detail *InfoLevel* + Level of information to print about lines being ignored. Default: + *1*. Possible values: *1, 2 or 3*. + + -f, --fast + In this mode, fingerprints columns specified using --FingerprintsCol + for reference and database fingerprints *TextFile(s)*, and + --FingerprintsField for reference and database fingerprints + *SDFile(s)* are assumed to contain valid fingerprints data and no + checking is performed before performing similarity and dissimilarity + search. By default, fingerprints data is validated before computing + pairwise similarity and distance coefficients. + + --FingerprintsMode *AutoDetect | FingerprintsBitVectorString | + FingerprintsVectorString* + Format of fingerprint strings data in reference and database + fingerprints *SD, FP, or Text (CSV/TSV)* files: automatically detect + format of fingerprints string created by MayaChemTools fingerprints + generation scripts or explicitly specify its format. Possible + values: *AutoDetect | FingerprintsBitVectorString | + FingerprintsVectorString*. Default value: *AutoDetect*. + + -g, --GroupFusionRule *Max, Min, Mean, Median, Sum, Euclidean* + Specify what group fusion [ Ref 94-97, Ref 100, Ref 105 ] rule to + use for calculating similarity of a database molecule against a set + of reference molecules during *MultipleReferences* value of + similarity search -m, --mode. Possible values: *Max, Min, Mean, + Median, Sum, Euclidean*. Default value: *Max*. *Mean* value + corresponds to average or arithmetic mean. The group fusion rule is + also referred to as data fusion of consensus scoring in the + literature. + + For a reference molecules set and a database molecule, let: + + N = Number of reference molecules in a set + + i = ith reference reference molecule in a set + n = Nth reference reference molecule in a set + + d = dth database molecule + + Crd = Fingerprints comparison value between rth reference and dth database + molecule - similarity/dissimilarity comparison using similarity or + distance coefficient + + Then, various group fusion rules to calculate fused similarity + between a database molecule and reference molecules set are defined + as follows: + + Max: MAX ( C1d, C2d, ..., Cid, ..., Cnd ) + + Min: MIN ( C1d, C2d, ..., Cid, ..., Cnd ) + + Mean: SUM ( C1d, C2d, ..., Cid, ..., Cnd ) / N + + Median: MEDIAN ( C1d, C2d, ..., Cid, ..., Cnd ) + + Sum: SUM ( C1d, C2d, ..., Cid, ..., Cnd ) + + Euclidean: SQRT( SUM( C1d ** 2, C2d ** 2, ..., Cid ** 2, ..., Cnd + *** 2) ) + + The fingerprints bit-vector or vector string of each reference + molecule in a set is compared with a database molecule using a + similarity or distance coefficient specified via -b, + --BitVectorComparisonMode or -v, --VectorComparisonMode. The + reference molecules whose comparison values with a database molecule + fall outside specified --SimilarityCutoff or --DistanceCutoff are + ignored during *Yes* value of --GroupFusionApplyCutoff. The + specified -g, --GroupFusionRule is applied to -k, --kNN reference + molecules to calculate final fused similarity value between a + database molecule and reference molecules set. + + During dissimilarity search or usage of distance comparison + coefficient in similarity search, the meaning of fingerprints + comaprison value is automatically reversed as shown below: + + SeachMode ComparisonCoefficient ComparisonValues + + Similarity SimilarityCoefficient Higher value imples high similarity + Similarity DistanceCoefficient Lower value implies high similarity + + Dissimilarity SimilarityCoefficient Lower value implies high + dissimilarity + Dissimilarity DistanceCoefficient Higher value implies high + dissimilarity + + Consequently, *Max* implies highest and lowest comparison value for + usage of similarity and distance coefficient respectively during + similarity search. And it corresponds to lowest and highest + comparison value for usage of similarity and distance coefficient + respectively during dissimilarity search. During *Min* fusion rule, + the highest and lowest comparison values are appropriately reversed. + + --GroupFusionApplyCutoff *Yes | No* + Specify whether to apply --SimilarityCutoff or --DistanceCutoff + values during application of -g, --GroupFusionRule to reference + molecules set. Possible values: *Yes or No*. Default value: *Yes*. + + During *Yes* value of --GroupFusionApplyCutoff, the reference + molecules whose comparison values with a database molecule fall + outside specified --SimilarityCutoff or --DistanceCutoff are not + used to calculate final fused similarity value between a database + molecule and reference molecules set. + + -h, --help + Print this help message. + + --InDelim *comma | semicolon* + Input delimiter for reference and database fingerprints CSV + *TextFile(s)*. Possible values: *comma or semicolon*. Default value: + *comma*. For TSV files, this option is ignored and *tab* is used as + a delimiter. + + -k, --kNN *all | number* + Number of k-nearest neighbors (k-NN) reference molecules to use + during -g, --GroupFusionRule for calculating similarity of a + database molecule against a set of reference molecules. Possible + values: *all | positive integers*. Default: *all*. + + After ranking similarity values between a database molecule and + reference molecules during *MultipleReferences* value of similarity + search -m, --mode option, a top -k, --KNN reference molecule are + selected and used during -g, --GroupFusionRule. + + This option is -s, --SearchMode dependent: It corresponds to + dissimilar molecules during *DissimilaritySearch* value of -s, + --SearchMode option. + + -m, --mode *IndividualReference | MultipleReferences* + Specify how to treat reference molecules in + *ReferenceFingerprintsFile* during similarity search: Treat each + reference molecule individually during similarity search or perform + similarity search by treating multiple reference molecules as a set. + Possible values: *IndividualReference | MultipleReferences*. Default + value: *MultipleReferences*. + + During *IndividualReference* value of -m, --Mode for similarity + search, fingerprints bit-vector or vector string of each reference + molecule is compared with database molecules using specified + similarity or distance coefficients to identify most similar + molecules for each reference molecule. Based on value of + --SimilarCountMode, upto --n, NumOfSimilarMolecules or -p, + --PercentSimilarMolecules at specified <--SimilarityCutoff> or + --DistanceCutoff are identified for each reference molecule. + + During *MultipleReferences* value -m, --mode for similarity search, + all reference molecules are considered as a set and -g, + --GroupFusionRule is used to calculate similarity of a database + molecule against reference molecules set either using all reference + molecules or number of k-nearest neighbors (k-NN) to a database + molecule specified using -k, --kNN. The fingerprints bit-vector or + vector string of each reference molecule in a set is compared with a + database molecule using a similarity or distance coefficient + specified via -b, --BitVectorComparisonMode or -v, + --VectorComparisonMode. The reference molecules whose comparison + values with a database molecule fall outside specified + --SimilarityCutoff or --DistanceCutoff are ignored. The specified + -g, --GroupFusionRule is applied to rest of -k, --kNN reference + molecules to calculate final similarity value between a database + molecule and reference molecules set. + + The meaning of similarity and distance is automatically reversed + during *DissimilaritySearch* value of -s, --SearchMode along with + appropriate handling of --SimilarityCutoff or --DistanceCutoff + values. + + -n, --NumOfSimilarMolecules *number* + Maximum number of most similar database molecules to find for each + reference molecule or set of reference molecules based on + *IndividualReference* or *MultipleReferences* value of similarity + search -m, --mode option. Default: *10*. Valid values: positive + integers. + + This option is ignored during *PercentSimilar* value of + --SimilarCountMode option. + + This option is -s, --SearchMode dependent: It corresponds to + dissimilar molecules during *DissimilaritySearch* value of -s, + --SearchMode option. + + --OutDelim *comma | tab | semicolon* + Delimiter for output CSV/TSV text file. Possible values: *comma, + tab, or semicolon* Default value: *comma*. + + --output *SD | text | both* + Type of output files to generate. Possible values: *SD, text, or + both*. Default value: *text*. + + -o, --overwrite + Overwrite existing files + + -p, --PercentSimilarMolecules *number* + Maximum percent of mosy similar database molecules to find for each + reference molecule or set of reference molecules based on + *IndividualReference* or *MultipleReferences* value of similarity + search -m, --mode option. Default: *1* percent of database + molecules. Valid values: non-zero values in between *0 to 100*. + + This option is ignored during *NumOfSimilar* value of + --SimilarCountMode option. + + During *PercentSimilar* value of --SimilarCountMode option, the + number of molecules in *DatabaseFingerprintsFile* is counted and + number of similar molecules correspond to --PercentSimilarMolecules + of the total number of database molecules. + + This option is -s, --SearchMode dependent: It corresponds to + dissimilar molecules during *DissimilaritySearch* value of -s, + --SearchMode option. + + --precision *number* + Precision of calculated similarity values for comparison and + generating output files. Default: up to *2* decimal places. Valid + values: positive integers. + + -q, --quote *Yes | No* + Put quote around column values in output CSV/TSV text file. Possible + values: *Yes or No*. Default value: *Yes*. + + --ReferenceColMode *ColNum | ColLabel* + Specify how columns are identified in reference fingerprints + *TextFile*: using column number or column label. Possible values: + *ColNum or ColLabel*. Default value: *ColNum*. + + --ReferenceCompoundIDCol *col number | col name* + This value is --ReferenceColMode mode specific. It specifies column + to use for retrieving compound ID from reference fingerprints + *TextFile* during similarity and dissimilarity search for output SD + and CSV/TSV text files. Possible values: *col number or col label*. + Default value: *first column containing the word compoundID in its + column label or sequentially generated IDs*. + + --ReferenceCompoundIDPrefix *text* + Specify compound ID prefix to use during sequential generation of + compound IDs for reference fingerprints *SDFile* and *TextFile*. + Default value: *Cmpd*. The default value generates compound IDs + which looks like Cmpd<Number>. + + For reference fingerprints *SDFile*, this value is only used during + *LabelPrefix | MolNameOrLabelPrefix* values of + --ReferenceCompoundIDMode option; otherwise, it's ignored. + + Examples for *LabelPrefix* or *MolNameOrLabelPrefix* value of + --DatabaseCompoundIDMode: + + Compound + + The values specified above generates compound IDs which correspond + to Compound<Number> instead of default value of Cmpd<Number>. + + --ReferenceCompoundIDField *DataFieldName* + Specify reference fingerprints *SDFile* datafield label for + generating compound IDs. This value is only used during *DataField* + value of --ReferenceCompoundIDMode option. + + Examples for *DataField* value of --ReferenceCompoundIDMode: + + MolID + ExtReg + + --ReferenceCompoundIDMode *DataField | MolName | LabelPrefix | + MolNameOrLabelPrefix* + Specify how to generate compound IDs from reference fingerprints + *SDFile* during similarity and dissimilarity search for output SD + and CSV/TSV text files: use a *SDFile* datafield value; use molname + line from *SDFile*; generate a sequential ID with specific prefix; + use combination of both MolName and LabelPrefix with usage of + LabelPrefix values for empty molname lines. + + Possible values: *DataField | MolName | LabelPrefix | + MolNameOrLabelPrefix*. Default: *LabelPrefix*. + + For *MolNameAndLabelPrefix* value of --ReferenceCompoundIDMode, + molname line in *SDFiles* takes precedence over sequential compound + IDs generated using *LabelPrefix* and only empty molname values are + replaced with sequential compound IDs. + + --ReferenceFingerprintsCol *col number | col name* + This value is --ReferenceColMode specific. It specifies fingerprints + column to use during similarity and dissimilarity search for + reference fingerprints *TextFile*. Possible values: *col number or + col label*. Default value: *first column containing the word + Fingerprints in its column label*. + + --ReferenceFingerprintsField *FieldLabel* + Fingerprints field label to use during similarity and dissimilarity + search for reference fingerprints *SDFile*. Default value: *first + data field label containing the word Fingerprints in its label* + + -r, --root *RootName* + New file name is generated using the root: <Root>.<Ext>. Default for + new file name: <ReferenceFileName>SimilaritySearching.<Ext>. The + output file type determines <Ext> value. The sdf, csv, and tsv <Ext> + values are used for SD, comma/semicolon, and tab delimited text + files respectively. + + -s, --SearchMode *SimilaritySearch | DissimilaritySearch* + Specify how to find molecules from database molecules for individual + reference molecules or set of reference molecules: Find similar + molecules or dissimilar molecules from database molecules. Possible + values: *SimilaritySearch | DissimilaritySearch*. Default value: + *SimilaritySearch*. + + During *DissimilaritySearch* value of -s, --SearchMode option, the + meaning of the following options is switched and they correspond to + dissimilar molecules instead of similar molecules: + --SimilarCountMode, -n, --NumOfSimilarMolecules, + --PercentSimilarMolecules, -k, --kNN. + + --SimilarCountMode *NumOfSimilar | PercentSimilar* + Specify method used to count similar molecules found from database + molecules for individual reference molecules or set of reference + molecules: Find number of similar molecules or percent of similar + molecules from database molecules. Possible values: *NumOfSimilar | + PercentSimilar*. Default value: *NumOfSimilar*. + + The values for number of similar molecules and percent similar + molecules are specified using options -n, NumOfSimilarMolecule and + --PercentSimilarMolecules. + + This option is -s, --SearchMode dependent: It corresponds to + dissimilar molecules during *DissimilaritySearch* value of -s, + --SearchMode option. + + --SimilarityCutoff *number* + Similarity cutoff value to use during comparison of similarity value + between a pair of database and reference molecules calculated by + similarity comparison methods for fingerprints bit-vector vector + strings data values. Possible values: *Any valid number*. Default + value: *0.75*. + + The comparison value between a pair of database and reference + molecule must meet the cutoff criterion as shown below: + + SeachMode CutoffCriterion ComparisonValues + + Similarity >= Higher value implies high similarity + Dissimilarity <= Lower value implies high dissimilarity + + This option is ignored during *No* value of --GroupFusionApplyCutoff + for *MultipleReferences* -m, --mode. + + This option is -s, --SearchMode dependent: It corresponds to + dissimilar molecules during *DissimilaritySearch* value of -s, + --SearchMode option. + + -v, --VectorComparisonMode *SupportedSimilarityName | + SupportedDistanceName* + Specify what similarity or distance coefficient to use for + calculating similarity between fingerprint vector strings data + values in *ReferenceFingerprintsFile* and *DatabaseFingerprintsFile* + during similarity search. Possible values: *TanimotoSimilairy | ... + | ManhattanDistance | ...*. Default value: *TanimotoSimilarity*. + + The value of -v, --VectorComparisonMode, in conjunction with + --VectorComparisonFormulism, decides which type of similarity and + distance coefficient formulism gets used. + + The current releases supports the following similarity and distance + coefficients: *CosineSimilarity, CzekanowskiSimilarity, + DiceSimilarity, OchiaiSimilarity, JaccardSimilarity, + SorensonSimilarity, TanimotoSimilarity, CityBlockDistance, + EuclideanDistance, HammingDistance, ManhattanDistance, + SoergelDistance*. These similarity and distance coefficients are + described below. + + FingerprintsVector.pm module, used to calculate similarity and + distance coefficients, provides support to perform comparison + between vectors containing three different types of values: + + Type I: OrderedNumericalValues + + . Size of two vectors are same + . Vectors contain real values in a specific order. For example: MACCS keys + count, Topological pharmnacophore atom pairs and so on. + + Type II: UnorderedNumericalValues + + . Size of two vectors might not be same + . Vectors contain unordered real value identified by value IDs. For example: + Toplogical atom pairs, Topological atom torsions and so on + + Type III: AlphaNumericalValues + + . Size of two vectors might not be same + . Vectors contain unordered alphanumerical values. For example: Extended + connectivity fingerprints, atom neighborhood fingerprints. + + Before performing similarity or distance calculations between + vectors containing UnorderedNumericalValues or AlphaNumericalValues, + the vectors are transformed into vectors containing unique + OrderedNumericalValues using value IDs for UnorderedNumericalValues + and values itself for AlphaNumericalValues. + + Three forms of similarity and distance calculation between two + vectors, specified using --VectorComparisonFormulism option, are + supported: *AlgebraicForm, BinaryForm or SetTheoreticForm*. + + For *BinaryForm*, the ordered list of processed final vector values + containing the value or count of each unique value type is simply + converted into a binary vector containing 1s and 0s corresponding to + presence or absence of values before calculating similarity or + distance between two vectors. + + For two fingerprint vectors A and B of same size containing + OrderedNumericalValues, let: + + N = Number values in A or B + + Xa = Values of vector A + Xb = Values of vector B + + Xai = Value of ith element in A + Xbi = Value of ith element in B + + SUM = Sum of i over N values + + For SetTheoreticForm of calculation between two vectors, let: + + SetIntersectionXaXb = SUM ( MIN ( Xai, Xbi ) ) + SetDifferenceXaXb = SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN ( Xai, Xbi ) ) + + For BinaryForm of calculation between two vectors, let: + + Na = Number of bits set to "1" in A = SUM ( Xai ) + Nb = Number of bits set to "1" in B = SUM ( Xbi ) + Nc = Number of bits set to "1" in both A and B = SUM ( Xai * Xbi ) + Nd = Number of bits set to "0" in both A and B + = SUM ( 1 - Xai - Xbi + Xai * Xbi) + + N = Number of bits set to "1" or "0" in A or B = Size of A or B = Na + Nb - Nc + Nd + + Additionally, for BinaryForm various values also correspond to: + + Na = | Xa | + Nb = | Xb | + Nc = | SetIntersectionXaXb | + Nd = N - | SetDifferenceXaXb | + + | SetDifferenceXaXb | = N - Nd = Na + Nb - Nc + Nd - Nd = Na + Nb - Nc + = | Xa | + | Xb | - | SetIntersectionXaXb | + + Various similarity and distance coefficients [ Ref 40, Ref 62, Ref + 64 ] for a pair of vectors A and B in *AlgebraicForm, BinaryForm and + SetTheoreticForm* are defined as follows: + + CityBlockDistance: ( same as HammingDistance and ManhattanDistance) + + *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) ) + + *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc + + *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb | + = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) + + CosineSimilarity: ( same as OchiaiSimilarityCoefficient) + + *AlgebraicForm*: SUM ( Xai * Xbi ) / SQRT ( SUM ( Xai ** 2) * SUM ( + Xbi ** 2) ) + + *BinaryForm*: Nc / SQRT ( Na * Nb) + + *SetTheoreticForm*: | SetIntersectionXaXb | / SQRT ( |Xa| * |Xb| ) = + SUM ( MIN ( Xai, Xbi ) ) / SQRT ( SUM ( Xai ) * SUM ( Xbi ) ) + + CzekanowskiSimilarity: ( same as DiceSimilarity and + SorensonSimilarity) + + *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) + + SUM ( Xbi **2 ) ) + + *BinaryForm*: 2 * Nc / ( Na + Nb ) + + *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) = + 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) ) + + DiceSimilarity: ( same as CzekanowskiSimilarity and + SorensonSimilarity) + + *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) + + SUM ( Xbi **2 ) ) + + *BinaryForm*: 2 * Nc / ( Na + Nb ) + + *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) = + 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) ) + + EuclideanDistance: + + *AlgebraicForm*: SQRT ( SUM ( ( ( Xai - Xbi ) ** 2 ) ) ) + + *BinaryForm*: SQRT ( ( Na - Nc ) + ( Nb - Nc ) ) = SQRT ( Na + Nb - + 2 * Nc ) + + *SetTheoreticForm*: SQRT ( | SetDifferenceXaXb | - | + SetIntersectionXaXb | ) = SQRT ( SUM ( Xai ) + SUM ( Xbi ) - 2 * ( + SUM ( MIN ( Xai, Xbi ) ) ) ) + + HammingDistance: ( same as CityBlockDistance and ManhattanDistance) + + *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) ) + + *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc + + *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb | + = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) + + JaccardSimilarity: ( same as TanimotoSimilarity) + + *AlgebraicForm*: SUM ( Xai * Xbi ) / ( SUM ( Xai ** 2 ) + SUM ( Xbi + ** 2 ) - SUM ( Xai * Xbi ) ) + + *BinaryForm*: Nc / ( ( Na - Nc ) + ( Nb - Nc ) + Nc ) = Nc / ( Na + + Nb - Nc ) + + *SetTheoreticForm*: | SetIntersectionXaXb | / | SetDifferenceXaXb | + = SUM ( MIN ( Xai, Xbi ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN + ( Xai, Xbi ) ) ) + + ManhattanDistance: ( same as CityBlockDistance and HammingDistance) + + *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) ) + + *BinaryForm*: ( Na - Nc ) + ( Nb - Nc ) = Na + Nb - 2 * Nc + + *SetTheoreticForm*: | SetDifferenceXaXb | - | SetIntersectionXaXb | + = SUM ( Xai ) + SUM ( Xbi ) - 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) + + OchiaiSimilarity: ( same as CosineSimilarity) + + *AlgebraicForm*: SUM ( Xai * Xbi ) / SQRT ( SUM ( Xai ** 2) * SUM ( + Xbi ** 2) ) + + *BinaryForm*: Nc / SQRT ( Na * Nb) + + *SetTheoreticForm*: | SetIntersectionXaXb | / SQRT ( |Xa| * |Xb| ) = + SUM ( MIN ( Xai, Xbi ) ) / SQRT ( SUM ( Xai ) * SUM ( Xbi ) ) + + SorensonSimilarity: ( same as CzekanowskiSimilarity and + DiceSimilarity) + + *AlgebraicForm*: ( 2 * ( SUM ( Xai * Xbi ) ) ) / ( SUM ( Xai ** 2) + + SUM ( Xbi **2 ) ) + + *BinaryForm*: 2 * Nc / ( Na + Nb ) + + *SetTheoreticForm*: 2 * | SetIntersectionXaXb | / ( |Xa| + |Xb| ) = + 2 * ( SUM ( MIN ( Xai, Xbi ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) ) + + SoergelDistance: + + *AlgebraicForm*: SUM ( ABS ( Xai - Xbi ) ) / SUM ( MAX ( Xai, Xbi ) + ) + + *BinaryForm*: 1 - Nc / ( Na + Nb - Nc ) = ( Na + Nb - 2 * Nc ) / ( + Na + Nb - Nc ) + + *SetTheoreticForm*: ( | SetDifferenceXaXb | - | SetIntersectionXaXb + | ) / | SetDifferenceXaXb | = ( SUM ( Xai ) + SUM ( Xbi ) - 2 * ( + SUM ( MIN ( Xai, Xbi ) ) ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( + MIN ( Xai, Xbi ) ) ) + + TanimotoSimilarity: ( same as JaccardSimilarity) + + *AlgebraicForm*: SUM ( Xai * Xbi ) / ( SUM ( Xai ** 2 ) + SUM ( Xbi + ** 2 ) - SUM ( Xai * Xbi ) ) + + *BinaryForm*: Nc / ( ( Na - Nc ) + ( Nb - Nc ) + Nc ) = Nc / ( Na + + Nb - Nc ) + + *SetTheoreticForm*: | SetIntersectionXaXb | / | SetDifferenceXaXb | + = SUM ( MIN ( Xai, Xbi ) ) / ( SUM ( Xai ) + SUM ( Xbi ) - SUM ( MIN + ( Xai, Xbi ) ) ) + + --VectorComparisonFormulism *AlgebraicForm | BinaryForm | + SetTheoreticForm* + Specify fingerprints vector comparison formulism to use for + calculation similarity and distance coefficients during -v, + --VectorComparisonMode. Possible values: *AlgebraicForm | BinaryForm + | SetTheoreticForm*. Default value: *AlgebraicForm*. + + For fingerprint vector strings containing AlphaNumericalValues data + values - ExtendedConnectivityFingerprints, + AtomNeighborhoodsFingerprints and so on - all three formulism result + in same value during similarity and distance calculations. + + -w, --WorkingDir *DirName* + Location of working directory. Default: current directory. + +EXAMPLES + To perform similarity search using Tanimoto coefficient by treating all + reference molecules as a set to find 10 most similar database molecules + with application of Max group fusion rule and similarity cutoff to + supported fingerprints strings data in SD fingerprints files present in + a data fields with Fingerprint substring in their labels, and create a + ReferenceFPHexSimilaritySearching.csv file containing sequentially + generated database compound IDs with Cmpd prefix, type: + + % SimilaritySearchingFingerprints.pl -o ReferenceSampleFPHex.sdf + DatabaseSampleFPHex.sdf + + To perform similarity search using Tanimoto coefficient by treating all + reference molecules as a set to find 10 most similar database molecules + with application of Max group fusion rule and similarity cutoff to + supported fingerprints strings data in FP fingerprints files, and create + a SimilaritySearchResults.csv file containing database compound IDs + retireved from FP file, type: + + % SimilaritySearchingFingerprints.pl -r SimilaritySearchResults -o + ReferenceSampleFPBin.fpf DatabaseSampleFPBin.fpf + + To perform similarity search using Tanimoto coefficient by treating all + reference molecules as a set to find 10 most similar database database + molecules with application of Max group fusion rule and similarity + cutoff to supported fingerprints strings data in text fingerprints files + present in a column names containing Fingerprint substring in their + names, and create a ReferenceFPHexSimilaritySearching.csv file + containing database compound IDs retireved column name containing + CompoundID substring or sequentially generated compound IDs, type: + + % SimilaritySearchingFingerprints.pl -o ReferenceSampleFPCount.csv + DatabaseSampleFPCount.csv + + To perform similarity search using Tanimoto coefficient by treating + reference molecules as individual molecules to find 10 most similar + database molecules for each reference molecule with application of + similarity cutoff to supported fingerprints strings data in SD + fingerprints files present in a data fields with Fingerprint substring + in their labels, and create a ReferenceFPHexSimilaritySearching.csv file + containing sequentially generated reference and database compound IDs + with Cmpd prefix, type: + + % SimilaritySearchingFingerprints.pl -mode IndividualReference -o + ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf + + To perform similarity search using Tanimoto coefficient by treating + reference molecules as individual molecules to find 10 most similar + database molecules for each reference molecule with application of + similarity cutoff to supported fingerprints strings data in FP + fingerprints files, and create a ReferenceFPHexSimilaritySearching.csv + file containing references and database compound IDs retireved from FP + file, type: + + % SimilaritySearchingFingerprints.pl -mode IndividualReference -o + ReferenceSampleFPHex.fpf DatabaseSampleFPHex.fpf + + To perform similarity search using Tanimoto coefficient by treating + reference molecules as individual molecules to find 10 most similar + database molecules for each reference molecule with application of + similarity cutoff to supported fingerprints strings data in text + fingerprints files present in a column names containing Fingerprint + substring in their names, and create a + ReferenceFPHexSimilaritySearching.csv file containing reference and + database compound IDs retrieved column name containing CompoundID + substring or sequentially generated compound IDs, type: + + % SimilaritySearchingFingerprints.pl -mode IndividualReference -o + ReferenceSampleFPHex.csv DatabaseSampleFPHex.csv + + To perform dissimilarity search using Tanimoto coefficient by treating + all reference molecules as a set to find 10 most dissimilar database + molecules with application of Max group fusion rule and similarity + cutoff to supported fingerprints strings data in SD fingerprints files + present in a data fields with Fingerprint substring in their labels, and + create a ReferenceFPHexSimilaritySearching.csv file containing + sequentially generated database compound IDs with Cmpd prefix, type: + + % SimilaritySearchingFingerprints.pl --mode MultipleReferences --SearchMode + DissimilaritySearch -o ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf + + To perform similarity search using CityBlock distance by treating + reference molecules as individual molecules to find 10 most similar + database molecules for each reference molecule with application of + distance cutoff to supported vector fingerprints strings data in SD + fingerprints files present in a data fields with Fingerprint substring + in their labels, and create a ReferenceFPHexSimilaritySearching.csv file + containing sequentially generated reference and database compound IDs + with Cmpd prefix, type: + + % SimilaritySearchingFingerprints.pl -mode IndividualReference + --VectorComparisonMode CityBlockDistance --VectorComparisonFormulism + AlgebraicForm --DistanceCutoff 10 -o + ReferenceSampleFPCount.sdf DatabaseSampleFPCount.sdf + + To perform similarity search using Tanimoto coefficient by treating all + reference molecules as a set to find 100 most similar database molecules + with application of Mean group fusion rule to to top 10 reference + molecules with in similarity cutoff of 0.75 to supported fingerprints + strings data in FP fingerprints files, and create a + ReferenceFPHexSimilaritySearching.csv file containing database compound + IDs retrieved from FP file, type: + + % SimilaritySearchingFingerprints.pl --mode MultipleReferences --SearchMode + SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity + --GroupFusionRule Mean --GroupFusionApplyCutoff Yes --kNN 10 + --SimilarityCutoff 0.75 --SimilarCountMode NumOfSimilar + --NumOfSimilarMolecules 100 -o + ReferenceSampleFPHex.fpf DatabaseSampleFPHex.fpf + + To perform similarity search using Tanimoto coefficient by treating + reference molecules as individual molecules to find 2 percent of most + similar database molecules for each reference molecule with application + of similarity cutoff of 0.85 to supported fingerprints strings data in + text fingerprints files present in specific columns and create a + ReferenceFPHexSimilaritySearching.csv file containing reference and + database compoundIDs retrieved from specific columns, type: + + % SimilaritySearchingFingerprints.pl --mode IndividualReference --SearchMode + SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity + --ReferenceColMode ColLabel --ReferenceFingerprintsCol Fingerprints + --ReferenceCompoundIDCol CompoundID --DatabaseColMode Collabel + --DatabaseCompoundIDCol CompoundID --DatabaseFingerprintsCol + Fingerprints --SimilarityCutoff 0.85 --SimilarCountMode PercentSimilar + --PercentSimilarMolecules 2 -o + ReferenceSampleFPHex.csv DatabaseSampleFPHex.csv + + To perform similarity search using Tanimoto coefficient by treating + reference molecules as individual molecules to find top 50 most similar + database molecules for each reference molecule with application of + similarity cutoff of 0.85 to supported fingerprints strings data in SD + fingerprints files present in specific data fields and create both + ReferenceFPHexSimilaritySearching.csv and + ReferenceFPHexSimilaritySearching.sdf files containing reference and + database compoundIDs retrieved from specific data fields, type: + + % SimilaritySearchingFingerprints.pl --mode IndividualReference --SearchMode + SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity + --ReferenceFingerprintsField Fingerprints + --DatabaseFingerprintsField Fingerprints + --ReferenceCompoundIDMode DataField --ReferenceCompoundIDField CmpdID + --DatabaseCompoundIDMode DataField --DatabaseCompoundIDField CmpdID + --SimilarityCutoff 0.85 --SimilarCountMode NumOfSimilar + --NumOfSimilarMolecules 50 --output both -o + ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf + + To perform similarity search using Tanimoto coefficient by treating + reference molecules as individual molecules to find 1 percent of most + similar database molecules for each reference molecule with application + of similarity cutoff to supported fingerprints strings data in SD + fingerprints files present in specific data field labels, and create + both ReferenceFPHexSimilaritySearching.csv + ReferenceFPHexSimilaritySearching.sdf files containing reference and + database compound IDs retrieved from specific data field labels along + with other specific data for database molecules, type: + + % SimilaritySearchingFingerprints.pl --mode IndividualReference --SearchMode + SimilaritySearch --BitVectorComparisonMode TanimotoSimilarity + --ReferenceFingerprintsField Fingerprints + --DatabaseFingerprintsField Fingerprints + --ReferenceCompoundIDMode DataField --ReferenceCompoundIDField CmpdID + --DatabaseCompoundIDMode DataField --DatabaseCompoundIDField CmpdID + --DatabaseDataFieldsMode Specify --DatabaseDataFields "TPSA,SLogP" + --SimilarityCutoff 0.75 --SimilarCountMode PercentSimilar + --PercentSimilarMolecules 1 --output both --OutDelim comma --quote Yes + --precision 3 -o ReferenceSampleFPHex.sdf DatabaseSampleFPHex.sdf + +AUTHOR + Manish Sud <msud@san.rr.com> + +SEE ALSO + InfoFingerprintsFiles.pl, SimilarityMatricesFingerprints.pl, + AtomNeighborhoodsFingerprints.pl, ExtendedConnectivityFingerprints.pl, + MACCSKeysFingerprints.pl, PathLengthFingerprints.pl, + TopologicalAtomPairsFingerprints.pl, + TopologicalAtomTorsionsFingerprints.pl, + TopologicalPharmacophoreAtomPairsFingerprints.pl, + TopologicalPharmacophoreAtomTripletsFingerprints.pl + +COPYRIGHT + Copyright (C) 2015 Manish Sud. All rights reserved. + + This file is part of MayaChemTools. + + MayaChemTools is free software; you can redistribute it and/or modify it + under the terms of the GNU Lesser General Public License as published by + the Free Software Foundation; either version 3 of the License, or (at + your option) any later version. +