Evidence map›Paper›PMID 38757384›Full record

ArticleProtein science : a publication of the Protein Society2024

Assessing the functional impact of protein binding site definition.

Prithviraj Nandigrami, Andras Fiser

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Assessing the functional impact of protein binding site definition.Protein science : a publication of the Protein Society · 2024
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Prithviraj NandigramiDepartments of Systems and Computational Biology, and Biochemistry, Albert Einstein College of Medicine, Bronx, New York, USA.
Andras FiserDepartments of Systems and Computational Biology, and Biochemistry, Albert Einstein College of Medicine, Bronx, New York, USA.ORCID 0000-0003-0085-5335

Funding

Molecular basis of recognition in the Immunological SynapseR35GM136357 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI FISER, ANDRAS · 2020 to 2024
$2.7M
Interdisciplinary protein engineering approach to design high affinity antibodies for flavivirusesR01AI141816 · NIAID · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI FISER, ANDRAS · 2019 to 2023
$2.1M
National Institute of Allergy and Infectious Diseases AI141816NIAID NIH HHS R01 AI141816NIGMS NIH HHS GM136357NIGMS NIH HHS R35 GM136357
6 · The paper itself

Abstract

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data, this approach also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also shows that methods for protein binding interface predictions should perform above approximately F-score = 0.7 accuracy level to capture the biological function of a protein.

Indexed as

Protein BindingProteinsBinding SitesLigandsModels, MolecularLigandsProteinspharmacophore modelingprotein interfaceprotein–protein interactionPROTLID

Identifiers

PMID38757384
PMCPMC11099757

What OpenQuestion holds

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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.