Evidence map›Paper›PMID 25275445›Full record

ArticlePLoS computational biology2014

Evidence of conformational selection driving the formation of ligand binding sites in protein-protein interfaces.

Tanggis Bohnuud, Dima Kozakov, Sandor Vajda

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. In Silico Druggability Assessment ofAntibiotics (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Predicting multiple conformations of ligand binding sites in proteins suggests that AlphaFold2 may remember too much.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Article
  5. BioMed research international · 2021
    Article
  6. Article
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  8. Review
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  11. Article
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  14. New Frontiers in Druggability.Journal of medicinal chemistry · 2015
    Article
  15. Review
  16. Review
  17. Article
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

3 authors.

Tanggis BohnuudProgram in Bioinformatics, Boston University, Boston, Massachusetts, United States of America.
Dima KozakovDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.
Sandor VajdaDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America; Department of Chemistry, Boston University, Boston, Massachusetts, United States of America.

Funding

Computational mapping of proteins for the binding of ligandsR01GM064700 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI VAJDA, SANDOR · 2003 to 2015
$4.3M
A MULTISTAGE APPROACH TO PROTEIN-PROTEIN DOCKINGR01GM061867 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI VAJDA, SANDOR · 2000 to 2016
$4.0M
Refinement Methods for Protein Docking based on Exploring Multi-Dimensional EnergR01GM093147 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI KOZAKOV, DMYTRO, PASCHALIDIS, IOANNIS · 2011 to 2014
$1.2M
NIGMS NIH HHS 1R01GM061867NIGMS NIH HHS 1R01GM064700NIGMS NIH HHS 1R01GM093147NIGMS NIH HHS R01 GM061867NIGMS NIH HHS R01 GM064700NIGMS NIH HHS R01 GM093147
6 · The paper itself

Abstract

Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small "probe" molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.

Indexed as

Binding SitesProtein BindingProtein ConformationComputational BiologyDatabases, ProteinModels, MolecularNuclear Magnetic Resonance, BiomolecularProteinsProteins

Identifiers

PMID25275445
PMCPMC4183424

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Registered trials

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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.