Rescoring Docking Hit Lists for Model Cavity Sites: Predictions and Experimental Testing

Abstract

Molecular docking computationally screens thousands to millions of organic molecules against protein structures, looking for those with complementary fits. Many approximations are made, often resulting in low "hit rates." A strategy to overcome these approximations is to rescore top-ranked docked molecules using a better but slower method. One such is afforded by molecular mechanics-generalized Born surface area (MM-GBSA) techniques. These more physically realistic methods have improved models for solvation and electrostatic interactions and conformational change compared to most docking programs. To investigate MM-GBSA rescoring, we re-ranked docking hit lists in three small buried sites: a hydrophobic cavity that binds apolar ligands, a slightly polar cavity that binds aryl and hydrogen-bonding ligands, and an anionic cavity that binds cationic ligands. These sites are simple; consequently, incorrect predictions can be attributed to particular errors in the method, and many likely ligands may actually be tested. In retrospective calculations, MM-GBSA techniques with binding-site minimization better distinguished the known ligands for each cavity from the known decoys compared to the docking calculation alone. This encouraged us to test rescoring prospectively on molecules that ranked poorly by docking but that ranked well when rescored by MM-GBSA. A total of 33 molecules highly ranked by MM-GBSA for the three cavities were tested experimentally. Of these, 23 were observed to bind--these are docking false negatives rescued by rescoring. The 10 remaining molecules are true negatives by docking and false positives by MM-GBSA. X-ray crystal structures were determined for 21 of these 23 molecules. In many cases, the geometry prediction by MM-GBSA improved the initial docking pose and more closely resembled the crystallographic result; yet in several cases, the rescored geometry failed to capture large conformational changes in the protein. Intriguingly, rescoring not only rescued docking false positives, but also introduced several new false positives into the top-ranking molecules. We consider the origins of the successes and failures in MM-GBSA rescoring in these model cavity sites and the prospects for rescoring in biologically relevant targets.

A flexible docking scheme to explore the binding selectivity of PDZ domains

“…There are different approaches to overcome this deficiency using empirical scoring functions (DrugScore 61 and XScore 62 ) and more physically realistic methods such as molecular mechanics-generalized Born (GB) surface area (SA) technique. 63 While ROSETTALIGAND is successful in obtaining good RMSD values for best poses, we prefer using a knowledge-based scoring function (DrugScore) 61 to estimate the binding affinities of ligands to a particular receptor with reasonable accuracy. Thus, at the end of Rosetta run, we re-evaluate the binding energy of the ligand bound complex structure with the lowest Rosetta binding score.…”

Integração das técnicas de triagem virtual e triagem biológica automatizada em alta escala: oportunidades e desafios em P&D de fármacos

“…Diversas estratégias levam em conta a flexibilidade proteica, como a utilização de várias estruturas para a docagem, [51][52][53] o emprego de múltiplos rotâmeros para determinados resíduos, 54,55 a simulação do efeito indutivo de ligantes 56 e o emprego de métodos de minimização da estrutura de complexos proteína-ligante após a docagem. 57 A presença de moléculas de água conservadas deve ser investigada nas estruturas dos complexos, uma vez que podem participar de interações intermoleculares cruciais para a formação do complexo proteína-ligante. Por sua vez, os resultados de estudos de docagem molecular são influenciados diretamente pela presença (ou ausência) de moléculas de água, levando a padrões distintos de reconhecimento molecular.…”

Discovery of Lead Compounds Targeting the Bacterial Sliding Clamp Using a Fragment-Based Approach

“…[2][3][4] The bacterial sliding clamp (SC), also known as the DNA polymerase III (Pol III) β subunit, is a torus-shaped homodimeric protein 5 that is conserved across bacterial species. [6][7][8] The SC serves as a protein-protein interaction (PPI) hub during bacterial DNA replication and repair, 9,10 surrounding double-stranded DNA and subsequently recruiting a diverse range of protein binding partners, including the δ and α subunits of DNA Pol III, DNA Pols I, II, IV, V and MutS.…”

“…[6][7][8] The SC serves as a protein-protein interaction (PPI) hub during bacterial DNA replication and repair, 9,10 surrounding double-stranded DNA and subsequently recruiting a diverse range of protein binding partners, including the δ and α subunits of DNA Pol III, DNA Pols I, II, IV, V and MutS. 5,9 The pivotal role it plays in bacterial DNA replication and repair, its conserved structure across bacterial species [6][7][8] and its structural divergence from the equivalent human protein (proliferating cell nuclear antigen, PCNA) 9,11 make the SC a highly attractive target for producing new antibiotics acting via a novel mechanism.…”

“…These protein binding partners interact with the SC using linear motifs (LMs) located on their surfaces. 5,13,14 LMs are short (4-10 residue), intrinsically disordered sequences most often found at the termini of proteins but sometimes in loop regions. [15][16][17] Binding of LMs to rigid protein domains represents a distinct category of protein-protein interactions (PPIs) that generally display weak affinities (K d ~ 1-100 µM).…”