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Pharmacophore alignment search tool: Influence of canonical atom labeling on similarity searching
Author(s) -
Hähnke Volker,
Rupp Matthias,
Krier Mireille,
Rippmann Friedrich,
Schneider Gisbert
Publication year - 2010
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.21574
Subject(s) - pharmacophore , similarity (geometry) , computer science , atom (system on chip) , information retrieval , chemistry , computational biology , artificial intelligence , pattern recognition (psychology) , computational chemistry , data mining , stereochemistry , biology , image (mathematics) , embedded system
Previously, (Hähnke et al., J Comput Chem 2009, 30, 761) we presented the Pharmacophore Alignment Search Tool (PhAST), a ligand‐based virtual screening technique representing molecules as strings coding pharmacophoric features and comparing them by global pairwise sequence alignment. To guarantee unambiguity during the reduction of two‐dimensional molecular graphs to one‐dimensional strings, PhAST employs a graph canonization step. Here, we present the results of the comparison of 11 different algorithms for graph canonization with respect to their impact on virtual screening. Retrospective screenings of a drug‐like data set were evaluated using the BEDROC metric, which yielded averaged values between 0.4 and 0.14 for the best‐performing and worst‐performing canonization technique. We compared five scoring schemes for the alignments and found preferred combinations of canonization algorithms and scoring functions. Finally, we introduce a performance index that helps prioritize canonization approaches without the need for extensive retrospective evaluation. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010