Scoring ligand similarity in structure-based virtual screening.
Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds.
Zavodszky
Maria I
MI
Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824-1319, USA.
Rohatgi
Anjali
A
Van Voorst
Jeffrey R
JR
Yan
Honggao
H
Kuhn
Leslie A
LA
D001681:Biological Assay; D004353:Drug Evaluation, Preclinical / Q000379:methods; D004791:Enzyme Inhibitors / Q000032:analysis* / Q000737:chemistry* / Q000494:pharmacology; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D054547:National Cancer Institute (U.S.); D012015:Reference Standards; D013329:Structure-Activity Relationship; D013917:Thrombin / Q000037:antagonists & inhibitors; D014481:United States
D004791:Enzyme Inhibitors; D008024:Ligands; D013917:Thrombin