MM-GB/SA Rescoring of Docking Poses in Structure-Based Lead Optimization

Abstract

The critical issues in docking include the prediction of the correct binding pose and the accurate estimation of the corresponding binding affinity. Different docking methodologies have all been successful in reproducing the crystallographic binding modes but struggle when predicting the corresponding binding affinities. The aim of this work is to evaluate the performance of the MM-GB/SA rescoring of docking poses in structure-based lead optimization. To accomplish that, a diverse set of pharmaceutically relevant targets, including CDK2, FactorXa, Thrombin, and HIV-RT were selected. The correlation between the MM-GB/SA results and experimental data in all cases is remarkable. It even qualifies this approach as a more attractive alternative for rank-ordering than the Free Energy Perturbation and Thermodynamic Integration methodologies because, while as accurate, it can handle more structurally dissimilar ligands and provides results at a fraction of the computational cost. On the technical side, the benefit of performing a conformational analysis and having an ensemble of conformers to represent each ligand in the unbound state during the MM-GB/SA rescoring procedure was investigated. In addition, the estimation of conformational entropy penalties for the ligands upon binding, computed from the Boltzmann distribution in water, was evaluated and compared to a commonly used approach employed by many docking scoring functions.

Locating a Plausible Binding Site for an Open-Channel Blocker, GlyH-101, in the Pore of the Cystic Fibrosis Transmembrane Conductance Regulator

“…Blockade by GlyH-101 was determined with concentrations ranging from 1 nM to 100 M. The EC 50 was determined for each voltage through fitting of a dose-response curve. The voltage dependence of the EC 50 was analyzed by using a modified version of the Woodhull model (Woodhull, 1973;Tikhonov and Magazanik, 1998) (Guimarã es and Cardozo, 2008). Similar MM-GB/SA techniques were used to investigate the effects of protein mutations on ligand binding affinity (Carra et al, 2012).…”

Identification of HIV Inhibitors Guided by Free Energy Perturbation Calculations

“…The past several years have been witness to many great successes in developing HIV-1 inhibitors with computer-aided approaches, e.g., virtual screening [41][42][43][44], molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) [45][46][47], molecular mechanics generalized Born surface area (MM-GB/SA) [48][49][50], and linear interaction energy (LIE) [51][52][53]. However, in keeping with the theme of this review, i.e., free energy perturbation calculations, not all studies can be highlighted.…”

Prediction of estrogen receptor β ligands potency and selectivity by docking and MM-GBSA scoring methods using three different scaffolds

“…When compared to docking scoring functions, the MM-GB/SA procedure provided improved enrichment of active ligands and better correlation between calculated binding affinities and experimental data in earlier studies 6,7 . However, in the present study, MM-GBSA rescoring of docked poses does not improve the correlation with the experimental IC 50 (r 2 = 0.491) when compared to GScore.…”

“…In an earlier study, MM-GBSA approach was evaluated to rank the relative potencies of anilinoquinazoline, anilinopyrimidine chemical classes against kinases, with the potencies range from micromolar to nanomolar potency (IC 50 ) values 6 . MM-GBSA approach has also been applied to a range of pharmaceutically relevant targets, which include CDK-2, factor Xa, thrombin, and HIV-RT 7 . For the ERα receptor, scoring methods like MD simulations and LIE approaches were employed in the prediction of ligand binding affinity.…”