Evidence map›Paper›PMID 31298437›Full record

ArticleProteins2020

Discovery of receptor-ligand interfaces in the immunoglobulin superfamily.

Nelson Gil, Eduardo J Fajardo, Andras Fiser

Abstract read
In one paragraph

Article in Proteins, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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.

Nelson GilDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York.
Eduardo J FajardoDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York.
Andras FiserDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York.ORCID 0000-0003-0085-5335

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007288 · NIGMS · YESHIVA UNIVERSITY · PI AKABAS, MYLES H. · 1985 to 2022
$35.6M
Molecular basis of recognition in the Immunological SynapseR35GM136357 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI FISER, ANDRAS · 2020 to 2024
$2.7M
Molecular basis of receptor-ligand recognition in the Immunological SynapseR01GM118709 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI FISER, ANDRAS · 2016 to 2019
$2.3M
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
The molecular basis of receptor-ligand recognition on the immunological synapseF31GM116570 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI GIL, NELSON HOMERO · 2015 to 2017
$131k
NIAID NIH HHS AI141816NIAID NIH HHS R01 AI141816NIGMS NIH HHS F31 GM116570NIGMS NIH HHS F31GM116570NIGMS NIH HHS GM118709NIGMS NIH HHS R01 GM118709NIGMS NIH HHS R35 GM136357NIGMS NIH HHS T32 GM007288
6 · The paper itself

Abstract

Cell-surface-anchored immunoglobulin superfamily (IgSF) proteins are widespread throughout the human proteome, forming crucial components of diverse biological processes including immunity, cell-cell adhesion, and carcinogenesis. IgSF proteins generally function through protein-protein interactions carried out between extracellular, membrane-bound proteins on adjacent cells, known as trans-binding interfaces. These protein-protein interactions constitute a class of pharmaceutical targets important in the treatment of autoimmune diseases, chronic infections, and cancer. A molecular-level understanding of IgSF protein-protein interactions would greatly benefit further drug development. A critical step toward this goal is the reliable identification of IgSF trans-binding interfaces. We propose a novel combination of structure and sequence information to identify trans-binding interfaces in IgSF proteins. We developed a structure-based binding interface prediction approach that can identify broad regions of the protein surface that encompass the binding interfaces and suggests that IgSF proteins possess binding supersites. These interfaces could theoretically be pinpointed using sequence-based conservation analysis, with performance approaching the theoretical upper limit of binding interface prediction accuracy, but achieving this in practice is limited by the current ability to identify an appropriate multiple sequence alignment for conservation analysis. However, an important contribution of combining the two orthogonal methods is that agreement between these approaches can estimate the reliability of the predictions. This approach was benchmarked on the set of 22 IgSF proteins with experimentally solved structures in complex with their ligands. Additionally, we provide structure-based predictions and reliability scores for the 62 IgSF proteins with known structure but yet uncharacterized binding interfaces.

Indexed as

AntibodiesHumansImmunoglobulinsLigandsMembrane ProteinsMultigene FamilyProtein BindingProtein Interaction MapsProteomeSequence AlignmentSurface PropertiesAntibodiesImmunoglobulinsLigandsMembrane ProteinsProteomebinding site conservationimmunoglobulin superfamilystructure-based mapping of binding site

Identifiers

PMID31298437
PMCPMC6901748

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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.