Evidence map›Paper›PMID 24277997›Full record

ArticlePLoS computational biology2013

Exploring the composition of protein-ligand binding sites on a large scale.

Nickolay A Khazanov, Heather A Carlson

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
5.6field-weighted citation impact, top 4% of its field
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

41 citing papers in PubMed, 91 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Databases of ligand-binding pockets and protein-ligand interactions.Computational and structural biotechnology journal · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. SiteFerret: Beyond Simple Pocket Identification in Proteins.Journal of chemical theory and computation · 2023
    Article
  16. Article
  17. Article
  18. Structural evolution of Delta lineage of SARS-CoV-2.International journal of biological macromolecules · 2023
    Article
  19. Article
  20. 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

2 authors at 2 institutions in 1 country.

Nickolay A KhazanovBioinformatics Graduate Program, University of Michigan, Ann Arbor, Michigan, United States of America.
Heather A Carlson
Michigan United · USUniversity of Michigan–Ann Arbor · US

Funding

Training Program in BioinformaticsT32GM070449 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ATHEY, BRIAN DAVID, BURMEISTER, MARGIT · 2005 to 2020
$3.6M
NIGMS NIH HHS NIH GM070449NIGMS NIH HHS T32 GM070449
6 · The paper itself

Abstract

The residue composition of a ligand binding site determines the interactions available for diffusion-mediated ligand binding, and understanding general composition of these sites is of great importance if we are to gain insight into the functional diversity of the proteome. Many structure-based drug design methods utilize such heuristic information for improving prediction or characterization of ligand-binding sites in proteins of unknown function. The Binding MOAD database if one of the largest curated sets of protein-ligand complexes, and provides a source of diverse, high-quality data for establishing general trends of residue composition from currently available protein structures. We present an analysis of 3,295 non-redundant proteins with 9,114 non-redundant binding sites to identify residues over-represented in binding regions versus the rest of the protein surface. The Binding MOAD database delineates biologically-relevant "valid" ligands from "invalid" small-molecule ligands bound to the protein. Invalids are present in the crystallization medium and serve no known biological function. Contacts are found to differ between these classes of ligands, indicating that residue composition of biologically relevant binding sites is distinct not only from the rest of the protein surface, but also from surface regions capable of opportunistic binding of non-functional small molecules. To confirm these trends, we perform a rigorous analysis of the variation of residue propensity with respect to the size of the dataset and the content bias inherent in structure sets obtained from a large protein structure database. The optimal size of the dataset for establishing general trends of residue propensities, as well as strategies for assessing the significance of such trends, are suggested for future studies of binding-site composition.

Indexed as

Binding SitesDatabases, ProteinAmino Acid SequenceComputational BiologyHydrogen BondingLigandsProtein BindingProteinsSurface PropertiesLigandsProteins

Identifiers

PMID24277997
PMCPMC3836696
OpenAlexW2060886672

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.