Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR-Bench dataset
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Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR‑Bench dataset Mei Qian Yau1,2 · Abigail L. Emtage3 · Jason S. E. Loo1,2 Received: 24 April 2020 / Accepted: 19 August 2020 © Springer Nature Switzerland AG 2020
Abstract Recent breakthroughs in G protein-coupled receptor (GPCR) crystallography and the subsequent increase in number of solved GPCR structures has allowed for the unprecedented opportunity to utilize their experimental structures for structure-based drug discovery applications. As virtual screening represents one of the primary computational methods used for the discovery of novel leads, the GPCR-Bench dataset was created to facilitate comparison among various virtual screening protocols. In this study, we have benchmarked the performance of Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) in improving virtual screening enrichment in comparison to docking with Glide, using the entire GPCR-Bench dataset of 24 GPCR targets and 254,646 actives and decoys. Reranking the top 10% of the docked dataset using MM/PBSA resulted in improvements for six targets at EF1% and nine targets at EF5%, with the gains in enrichment being more pronounced at the EF1% level. We additionally assessed the utility of rescoring the top ten poses from docking and the ability of short MD simulations to refine the binding poses prior to MM/PBSA calculations. There was no clear trend of the benefit observed in both cases, suggesting that utilizing a single energy minimized structure for MM/PBSA calculations may be the most computationally efficient approach in virtual screening. Overall, the performance of MM/PBSA rescoring in improving virtual screening enrichment obtained from docking of the GPCR-Bench dataset was found to be relatively modest and target-specific, highlighting the need for validation of MM/PBSA-based protocols prior to prospective use. Keywords GPCR · Virtual screening · MM/PBSA Abbreviations 5HT1B 5-Hydroxytryptamine 1B receptor 5HT2B 5-Hydroxytryptamine 2B receptor AA2AR Adenosine A2A receptor ACM2 Muscarinic acetylcholine 2 receptor ACM3 Muscarinic acetylcholine 3 receptor ADRB1 Beta-1 adrenergic receptor Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10822-020-00339-5) contains supplementary material, which is available to authorized users. * Jason S. E. Loo [email protected] 1
Center for Drug Discovery and Molecular Pharmacology, Faculty of Health and Medical Sciences, Taylor’s University, No. 1 Jalan Taylor’s, 47500 Subang Jaya, Selangor, Malaysia
2
School of Pharmacy, Faculty of Health and Medical Sciences, Taylor’s University, No. 1 Jalan Taylor’s, 47500 Subang Jaya, Selangor, Malaysia
3
School of Pharmacy, The University of Nottingham Malaysia Campus, Jalan Broga, 43500 Semenyih, Selangor, Malaysia
ADRB2 Beta-2 adrenergic receptor BEAR Binding Estimation After Refinement CCR5 C-C chemokine receptor type 5 CRFR1 Corticotropin releasing factor receptor 1 CXCR4 C-X-C
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