In pursuit of virtual lead optimization: The role of the receptor structure and ensembles in accurate docking

Abstract

Accurate ranking during in silico lead optimization is critical to drive the generation of new ligands with higher affinity, yet it is especially difficult because of the subtle changes between analogs. In order to assess the role of the structure of the receptor in delivering accurate lead ranking results, we docked a set of forty related inhibitors to structures of one species of dihydrofolate reductase (DHFR) derived from crystallographic, NMR solution data, and homology models. In this study, the crystal structures yielded the superior results: the compounds were placed in the active site in the conserved orientation and the docking scores for 80% percent of the compounds clustered into the same bins as the measured affinity. Single receptor structures derived from NMR data or homology models did not serve as accurate docking receptors. To our knowledge, these are the first experiments that assess ranking of homologous lead compounds using a variety of receptor structures. We then extended the study to investigate whether ensembles, either computationally or experimentally derived, of all of the single starting structures aid, hinder or have no effect on the performance of the starting template. Impressively, when ensembles of receptor structures derived from NMR data or homology models were employed, docking accuracy improved to a level equal to that of the high resolution crystal structures. The same experiments using a second species of DHFR and set of ligands confirm the results. A comparison of the structures of the individual ensemble members to the starting structures shows that the effect of the ensembles can be ascribed to protein flexibility in addition to absorption of computational error.

Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge

“…It has already been reported previously that use of multiple receptor conformation improves the virtual screening performance if receptor ensemble is chosen carefully among the available crystal structures or molecular dynamics generated conformers [50,51]. We observed that if top five receptors that performed best in single receptor docking are chosen, the AUC value goes up.…”

Virtual Screening and Biological Characterization of Novel Histone Arginine Methyltransferase PRMT1 Inhibitors

“…This may be largely due to the fortunate result of relatively minor induced-fit adaptations of proteins upon ligand binding. [27] It is surprising that homology models often provide significant enrichment of actives against a background of decoys. A variety of successful VS studies based [19,[28][29][30] In a retrospective study, Gilson and co-workers [31] analyzed five drug targets for which the crystal structure was available.…”

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description

“…The "right' conformations should be able to provide the best results in terms of quantity and quality, where quantity corresponds to the percentage of active molecules identified in the early screening stage, and quality to the chemical diversity of these first ranked molecules. Both single-and multiple receptor conformation approaches [24] are significantly affected by the chosen binding site architecture, so that the key point is often represented by the capability of the conformational sampling to select the most representative states [145,190]. Some strategies were recently proposed to guide this conformational sampling.…”

“…In silico methodologies able to deal implicitly or explicitly with protein flexibility in drug design include soft docking [135,136], docking with libraries of side-chain rotamers [136], algorithms accounting for induced-fit adjustments [70,137], Monte Carlo sampling [62,138] and MD simulations [139]. More recently docking into multiple conformations coming from X-ray [140][141][142], NMR [143,144], a combination of both [145,146] or computationally generated by MD simulations [147,148], normal-mode analysis [63,66,149], Monte Carlo [62,150], or homology models [83] have been successfully applied.…”