Evidence map›Paper›PMID 25166865›Full record

ArticlePLoS computational biology2014

VASP-E: specificity annotation with a volumetric analysis of electrostatic isopotentials.

Brian Y Chen

Open access · goldAbstract 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

11 citing papers in PubMed, 20 citations in OpenAlex.

  1. Automatic Explanation of Protein-Protein Binding Mechanism: A Preliminary Study.Computational structural bioinformatics : international workshop, CSBW 2024, Boston, MA, USA, November 16, 2024, proceedings. Computational Structural Bioinformatics Workshop (2024 : Boston, Mass.) · 2025
    Article
  2. Article
  3. Article
  4. A Conical Representation of Hydrogen Bond Geometry for Quantifying Bond Interactions.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2021
    Article
  5. DiffBond: A Method for Predicting Intermolecular Bond Formation.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2021
    Article
  6. Article
  7. Review
  8. Article
  9. Exploring Protein Cavities through Rigidity Analysis.Molecules (Basel, Switzerland) · 2018
    Article
  10. Article
  11. 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

1 author at 1 institution in 1 country.

Brian Y ChenDepartment of Computer Science and Engineering, P.C. Rossin College of Engineering and Applied Sciences, Lehigh University, Bethlehem, Pennsylvania, United States of America.
Lehigh University · US

Funding

University of Georgia ProjectU54GM094597 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI ROST, BURKHARD · 2010 to 2014
$36.9M
COMPUTER STUDIES OF PROTEIN STRUCTURE AND FUNCTIONR01GM030518 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI HONIG, BARRY H · 1985 to 2020
$4.5M
COMPUTER STUDIES OF PROTEIN STRUCTURE AND FUNCTIONR37GM030518 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HONIG, BARRY H · 1995 to 2004
$1.5M
NIGMS NIH HHS GM030518NIGMS NIH HHS GM094597NIGMS NIH HHS R01 GM030518NIGMS NIH HHS R37 GM030518NIGMS NIH HHS U54 GM094597
6 · The paper itself

Abstract

Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity annotation, where the identification of subtle differences among very similar proteins can assist in finding small structural variations that create differences in binding specificity. Few specificity annotation methods consider electrostatic fields, which play a critical role in molecular recognition. To fill this gap, this paper describes VASP-E (Volumetric Analysis of Surface Properties with Electrostatics), a novel volumetric comparison tool based on the electrostatic comparison of protein-ligand and protein-protein binding sites. VASP-E exploits the central observation that three dimensional solids can be used to fully represent and compare both electrostatic isopotentials and molecular surfaces. With this integrated representation, VASP-E is able to dissect the electrostatic environments of protein-ligand and protein-protein binding interfaces, identifying individual amino acids that have an electrostatic influence on binding specificity. VASP-E was used to examine a nonredundant subset of the serine and cysteine proteases as well as the barnase-barstar and Rap1a-raf complexes. Based on amino acids established by various experimental studies to have an electrostatic influence on binding specificity, VASP-E identified electrostatically influential amino acids with 100% precision and 83.3% recall. We also show that VASP-E can accurately classify closely related ligand binding cavities into groups with different binding preferences. These results suggest that VASP-E should prove a useful tool for the characterization of specific binding and the engineering of binding preferences in proteins.

Indexed as

AlgorithmsAmino AcidsAnimalsCattleCluster AnalysisComputational BiologyHumansMolecular Sequence AnnotationProtein BindingProteinsSequence Analysis, ProteinSoftwareStatic ElectricitySurface PropertiesAmino AcidsProteins

Identifiers

PMID25166865
PMCPMC4148194
OpenAlexW2056043162

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.