Electrostatic-field and surface-shape similarity for virtual screening and pose prediction

Ann E Cleves,Stephen R Johnson,Ajay N Jain

doi:10.1007/s10822-019-00236-6

Abstract

We introduce a new method for rapid computation of 3D molecular similarity that combines electrostatic field comparison with comparison of molecular surface-shape and directional hydrogen-bonding preferences (called “eSim”). Rather than employing heuristic “colors” or user-defined molecular feature types to represent conformation-dependent molecular electrostatics, eSim calculates the similarity of the electrostatic fields of two molecules (in addition to shape and hydrogen-bonding). We present detailed virtual screening performance data on the standard 102 target DUD-E set. In its moderately fast screening mode, eSim running on a single computing core is capable of processing over 60 molecules per second. In this mode, eSim performed significantly better than all alternate methods for which full DUD-E data were available (mean ROC area of 0.74, p < 10^{-9}, by paired t-test, compared with the best performing alternate method). In addition, for 92 targets of the DUD-E set where multiple ligand-bound crystal structures were available, screening performance was assessed using alternate ligands or sets thereof (in their bound poses) as similarity targets. Using the joint alignment of five ligands for each protein target, mean ROC area exceeded 0.82 for the 92 targets. Design-focused application of ligand similarity methods depends on accurate predictions of geometric molecular relationships. We comprehensively assessed pose prediction accuracy by curating nearly 400,000 bound ligand pose pairs across the DUD-E targets. Overall, beginning from agnostic initial poses, we observed an 80% success rate for RMSD le 2.0 Å among the top 20 predicted eSim poses. These examples were split roughly 50/50 into cases with high direct atomic overlap (where a shared scaffold exists between a pair) and low direct atomic overlap (where where a ligand pair has dissimilar scaffolds but largely occupies the same space). Within the high direct atomic overlap subset, the pose prediction success rate was 93%. For the more challenging subset (where dissimilar scaffolds are to be aligned), the success rate was 70%. The eSim approach enables both large-scale screening and rational design of ligands and is rooted in physically meaningful, non-heuristic, molecular comparisons.

Highlights

Calculation of 3D ligand similarity has become a widely used approach within computer-aided drug design, especially for virtual screening and for pose prediction and Princeton, NJ, USA 3 Dept. of Bioengineering and Therapeutic Sciences, University of California, San Francisco, USA multiple ligand alignment
In order to thoroughly analyze the effects of query ligand choice and to comprehensively assess pose prediction, we identified all PDB structures for each DUD-E target that had a matching UniProt identifier
For ROCS-color, pose prediction performance was assessed on the DUD-E+ benchmark

Summary

Introduction

Calculation of 3D ligand similarity has become a widely used approach within computer-aided drug design, especially for virtual screening and for pose prediction and Princeton, NJ, USA 3 Dept. of Bioengineering and Therapeutic Sciences, University of California, San Francisco, USA multiple ligand alignment. Calculation of 3D ligand similarity has become a widely used approach within computer-aided drug design, especially for virtual screening and for pose prediction and Princeton, NJ, USA 3 Dept. Many different methods have been developed, based on aspects of volumetric overlap, surface concordance, or matching of electrostatic or other ligand features such as aromatic rings. We refer interested readers to the perspective from Nicholls et al for a review [1] and the collection of papers published here in 2008 [2], which address numerous aspects of virtual screening assessment, pose prediction, statistical evaluation approaches, and benchmark construction [3,4,5,6,7,8,9,10,11,12,13]. Six values are computed: 1. stericdist : The distance in Angstroms from the point to the atom surface, which corresponds to the minimum over the distances to each atom less that atom’s VdW radius

Methods

Results

Conclusion