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Integrating Structure‐ and Ligand‐Based Virtual Screening: Comparison of Individual, Parallel, and Fused Molecular Docking and Similarity Search Calculations on Multiple Targets
Author(s) -
Tan Lu,
Geppert Hanna,
Sisay Mihiret T.,
Gütschow Michael,
Bajorath Jürgen
Publication year - 2008
Publication title -
chemmedchem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.817
H-Index - 100
eISSN - 1860-7187
pISSN - 1860-7179
DOI - 10.1002/cmdc.200800129
Subject(s) - docking (animal) , virtual screening , computer science , similarity (geometry) , computational biology , protein–ligand docking , similitude , artificial intelligence , data mining , bioinformatics , biology , drug discovery , medicine , nursing , image (mathematics)
Similarity searching is often used to preselect compounds for docking, thereby decreasing the size of screening databases. However, integrated structure‐ and ligand‐based screening schemes are rare at present. Docking and similarity search calculations using 2D fingerprints were carried out in a comparative manner on nine target enzymes, for which significant numbers of diverse inhibitors could be obtained. In the absence of knowledge‐based docking constraints and target‐directed parameter optimisation, fingerprint searching displayed a clear preference over docking calculations. Alternative combinations of docking and similarity search results were investigated and found to further increase compound recall of individual methods in a number of instances. When the results of similarity searching and docking were combined, parallel selection of candidate compounds from individual rankings was generally superior to rank fusion. We suggest that complementary results from docking and similarity searching can be captured by integrated compound selection schemes.