Consensus scoring evaluated using the GPCR-Bench dataset: Reconsidering the role of MM/GBSA

Yau, Mei Qian; Loo, Jason Siau Ee

doi:10.1007/s10822-022-00456-3

Cited by 5 publications

(3 citation statements)

References 92 publications

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“…With MM/PSBA demonstrating a majority decline in correlations for both datasets and MM/GBSA showing only improvements in the agonist dataset in comparison to Glide (Fig. 3), this emphasizes the superior performance of Glide rather than the subpar performance of MM/PBSA and MM/GBSA, as re ected in prior studies [40,41]. While the accuracy of the initial docking pose may play a role in binding free energy estimations using MM/PB(GB)SA [36], both the datasets utilized in this study have demonstrated excellent agreement between the docked ligands and the crystallographic ligands [34], hence providing an equitable basis for binding free energy predictions.…”

Section: Resultssupporting

confidence: 64%

“…The utility of both MM/PBSA and MM/GBSA in structure-based drug design applications such as binding free energy prediction, rescoring docked poses, virtual screening, and consensus scoring, has been widely demonstrated [36,[40][41][42][43][44][45]. A prior study has calculated MM/PBSA and MM/GBSA binding free energies for a set of CB 1 agonists and antagonists [34].…”

Section: Introductionmentioning

confidence: 99%

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A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands

Yau,

Liew,

Toh

et al. 2024

Preprint

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The substantial increase in the number of active and inactive-state CB1 receptor experimental structures has provided opportunities for CB1 drug discovery using various structure-based drug design methods, including the popular end-point methods for predicting binding free energies – Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA). In this study, we have therefore evaluated the performance of MM/PBSA and MM/GBSA in calculating binding free energies for CB1 receptor. Additionally, with both MM/PBSA and MM/GBSA being known for their highly individualized performance, we have evaluated the effects of various simulation parameters including the use of energy minimized structures, choice of solute dielectric constant, inclusion of entropy, and the effects of the five GB models. Generally, MM/GBSA provided higher correlations than MM/PBSA (rMM/GBSA = 0.433 – 0.652 vs. rMM/PBSA = 0.100 – 0.486) regardless of the simulation parameters, while also offering faster calculations. Improved correlations were observed with the use of molecular dynamics ensembles compared with energy-minimized structures and larger solute dielectric constants. Incorporation of entropic terms led to unfavorable results for both MM/PBSA and MM/GBSA for a majority of the dataset, while the evaluation of the various GB models exerted a varying effect on both the datasets. The findings obtained in this study demonstrate the utility of MM/PBSA and MM/GBSA in predicting binding free energies for the CB1 receptor, hence providing a useful benchmark for their applicability in the endocannabinoid system as well as other G protein-coupled receptors.

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Section: Resultssupporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands

Yau,

Liew,

Toh

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

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“…The normal mode approximation has been widely used in various cases such as static quantum mechanics calculations and protein-protein binding. [91][92][93][94][95][96][97][98][99] Due to the popularity of NMA in end-point free energy analysis of protein-ligand and host-guest systems, in the current benchmark calculation, we select this 'standard' method to estimate the entropic contribution to the binding free energy. As the computational cost of NMA calculations (specifically the calculation of the Hessian matrix) is quite high in complex systems and the entropic changes from NMA are similar for different configurations, often only several or tens of snapshots are used to compute this term.…”

Section: End-point Free Energy Calculationmentioning

confidence: 99%

Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host-guest Binding: I. Standard Procedure

Liu

Zheng

Qin

et al. 2022

Preprint

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Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Finally, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods.

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A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands

Yau,

Liew,

Toh

et al. 2024

J Mol Model

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Consensus scoring evaluated using the GPCR-Bench dataset: Reconsidering the role of MM/GBSA

Cited by 5 publications

References 92 publications

A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands

A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands

Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host-guest Binding: I. Standard Procedure

A head-to-head comparison of MM/PBSA and MM/GBSA in predicting binding affinities for the CB1 cannabinoid ligands

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