Evidence map›Paper›PMID 27510546›Full record

ArticleJournal of computational chemistry2016

Calculating protein-ligand binding affinities with MMPBSA: Method and error analysis.

Changhao Wang, Peter H Nguyen, Kevin Pham, Danielle Huynh, Thanh-Binh Nancy Le, Hongli Wang, Pengyu Ren, Ray Luo

Abstract read
In one paragraph

Article in Journal of computational chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

102 citing papers in PubMed.

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  14. Harnessing AlphaFold to reveal hERG channel conformational state secrets.bioRxiv : the preprint server for biology · 2025
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42 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Changhao WangChemical and Materials Physics Graduate Program, Irvine, California, 92697.
Peter H NguyenDepartment of Molecular Biology and Biochemistry, Irvine, California, 92697.
Kevin PhamDepartment of Molecular Biology and Biochemistry, Irvine, California, 92697.
Danielle HuynhDepartment of Molecular Biology and Biochemistry, Irvine, California, 92697.
Thanh-Binh Nancy LeDepartment of Molecular Biology and Biochemistry, Irvine, California, 92697.
Hongli WangDepartment of Molecular Biology and Biochemistry, Irvine, California, 92697.
Pengyu RenDepartment of Biomedical Engineering, University of Texas, Austin, Texas, 78712.
Ray LuoChemical and Materials Physics Graduate Program, Irvine, California, 92697. rluo@uci.edu.

Funding

AMBER force field consortium: a coherent biomolecular simulation platformR01GM079383 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CIEPLAK, PIOTR, DUAN, YONG · 2007 to 2017
$4.7M
Specificity and Selectivity in Protein-Ion BindingR01GM114237 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI PONDER, JAY, REN, PENGYU · 2015 to 2023
$2.6M
AMBER/PBSA: An Open-Source Computer Program for Accurate and Scalable Solvation Analysis ofBiomoleculesR01GM093040 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LUO, RAY · 2010 to 2018
$2.2M
NIGMS NIH HHS R01 GM079383NIGMS NIH HHS R01 GM093040NIGMS NIH HHS R01 GM114237
6 · The paper itself

Abstract

Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) methods have become widely adopted in estimating protein-ligand binding affinities due to their efficiency and high correlation with experiment. Here different computational alternatives were investigated to assess their impact to the agreement of MMPBSA calculations with experiment. Seven receptor families with both high-quality crystal structures and binding affinities were selected. First the performance of nonpolar solvation models was studied and it was found that the modern approach that separately models hydrophobic and dispersion interactions dramatically reduces RMSD's of computed relative binding affinities. The numerical setup of the Poisson-Boltzmann methods was analyzed next. The data shows that the impact of grid spacing to the quality of MMPBSA calculations is small: the numerical error at the grid spacing of 0.5 Å is already small enough to be negligible. The impact of different atomic radius sets and different molecular surface definitions was further analyzed and weak influences were found on the agreement with experiment. The influence of solute dielectric constant was also analyzed: a higher dielectric constant generally improves the overall agreement with experiment, especially for highly charged binding pockets. The data also showed that the converged simulations caused slight reduction in the agreement with experiment. Finally the direction of estimating absolute binding free energies was briefly explored. Upon correction of the binding-induced rearrangement free energy and the binding entropy lost, the errors in absolute binding affinities were also reduced dramatically when the modern nonpolar solvent model was used, although further developments were apparently necessary to further improve the MMPBSA methods. © 2016 Wiley Periodicals, Inc.

Indexed as

LigandsMolecular Dynamics SimulationThermodynamicsProtein BindingProteinsSolventsSurface PropertiesLigandsProteinsSolventsmolecular dynamicsnonpolar solvent modelsPoisson-Boltzmann implicit solvent models

Identifiers

PMID27510546
PMCPMC5018451

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.