Comparison of Topological, Shape, and Docking Methods in Virtual Screening

TLDR

Benchmarking on 11 targets compared 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein‑structure docking (FLOG, FRED, Glide) using active/decoy sets from the MDDR and Merck databases. Ligand‑based methods outperformed docking overall, with 3D ligand‑based methods only better when chemical typing was included; Glide was the best docking method, FRED close second, and performance varied by database and target.

Abstract

Virtual screening benchmarking studies were carried out on 11 targets to evaluate the performance of three commonly used approaches: 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein structure-based docking (FLOG, FRED, Glide). Active and decoy compound sets were assembled from both the MDDR and the Merck compound databases. Averaged over multiple targets, ligand-based methods outperformed docking algorithms. This was true for 3D ligand-based methods only when chemical typing was included. Using mean enrichment factor as a performance metric, Glide appears to be the best docking method among the three with FRED a close second. Results for all virtual screening methods are database dependent and can vary greatly for particular targets.