Evidence map›Paper›PMID 25835573›Full record

ReviewExpert opinion on drug discovery2015

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities.

Samuel Genheden, Ulf Ryde

Abstract readReview
In one paragraph

Review in Expert opinion on drug discovery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2,194 papers.

0numbers the graph read from it
0cells of the map it votes in
2,194citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2,194 citing papers in PubMed.

  1. Article
  2. α-Mangostin attenuatesVirulence · 2026
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2,134 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

2 authors.

Samuel GenhedenUniversity of Southampton, School of Chemistry , Highfield, SO17 1BJ, Southampton , UK.
Ulf Ryde

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe molecular mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success. AREAS COVERED: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. EXPERT OPINION: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results.

Indexed as

Drug DesignMolecular Dynamics SimulationBinding SitesEntropyHumansLigandsPharmaceutical PreparationsProtein BindingWaterLigandsPharmaceutical PreparationsWaterdrug designelectrostaticsentropyfree energy perturbationlinear interaction energynon-polar solvationsolvation

Identifiers

PMID25835573
PMCPMC4487606

What OpenQuestion holds

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Registered trials

None linked

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.