Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases.
This paper reports an evaluation of both graph-based and fingerprint-based measures of structural similarity, when used for virtual screening of sets of 2D molecules drawn from the MDDR and ID Alert databases. The graph-based measures employ a new maximum common edge subgraph isomorphism algorithm, called RASCAL, with several similarity coefficients described previously for quantifying the similarity between pairs of graphs. The effectiveness of these graph-based searches is compared with that resulting from similarity searches using BCI, Daylight and Unity 2D fingerprints. Our results suggest that graph-based approaches provide an effective complement to existing fingerprint-based approaches to virtual screening.
Pfizer Global Research and Development, Ann Arbor Laboratories, Michigan 48105, USA.
John W
JW
Raymond
Peter
P
Willett
D000465:Algorithms; D003198:Computer Simulation; D016208:Databases, Factual; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods* / Q000706:statistics & numerical data; D015394:Molecular Structure