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Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR-Bench dataset

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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.

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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

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 chemokine receptor type 4

DRD3:

Dopamine 3 receptor

GPCR:

G protein-coupled receptor

GPR40:

Free fatty acid receptor 1

EF:

Enrichment factor

HRH1:

Histamine 1 receptor

MD:

Molecular dynamics

MGLUR1:

Metabotropic glutamate receptor 1

MGLUR5:

Metabotropic glutamate receptor 5

MM/GBSA:

Molecular Mechanics/Generalized Born Surface Area

MM/PBSA:

Molecular Mechanics/Poisson-Boltzmann Surface Area

OPRD:

Delta opioid receptor

OPRK:

Kappa opioid receptor

OPRM:

Mu opioid receptor

OPRX:

Nociceptin receptor

OX2R:

Orexin receptor type 2

PAR1:

Proteinase-activated receptor 1

P2Y12:

P2Y purinoceptor 12

S1PR1:

Sphingosine 1-phosphate receptor 1

SMO:

Smoothened receptor

TM:

Transmembrane

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Funding

This research was supported by Taylor’s University through its Taylor’s University Flagship Research Grant Scheme under grant number TUFR/2017/002/10 and Taylor’s PhD Scholarship Program.

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Authors and Affiliations

  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

    Mei Qian Yau & Jason S. E. Loo

  2. School of Pharmacy, Faculty of Health and Medical Sciences, Taylor’s University, No. 1 Jalan Taylor’s, 47500, Subang Jaya, Selangor, Malaysia

    Mei Qian Yau & Jason S. E. Loo

  3. School of Pharmacy, The University of Nottingham Malaysia Campus, Jalan Broga, 43500, Semenyih, Selangor, Malaysia

    Abigail L. Emtage

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  1. Mei Qian Yau
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  2. Abigail L. Emtage
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Yau, M.Q., Emtage, A.L. & Loo, J.S.E. Benchmarking the performance of MM/PBSA in virtual screening enrichment using the GPCR-Bench dataset. J Comput Aided Mol Des 34, 1133–1145 (2020). https://doi.org/10.1007/s10822-020-00339-5

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