Developing similarity matrices for antibody-protein binding interactions.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 16 05 2023
accepted: 17 10 2023
medline: 30 10 2023
pubmed: 26 10 2023
entrez: 26 10 2023
Statut: epublish

Résumé

The inventions of AlphaFold and RoseTTAFold are revolutionizing computational protein science due to their abilities to reliably predict protein structures. Their unprecedented successes are due to the parallel consideration of several types of information, one of which is protein sequence similarity information. Sequence homology has been studied for many decades and depends on similarity matrices to define how similar or different protein sequences are to one another. A natural extension of predicting protein structures is predicting the interactions between proteins, but similarity matrices for protein-protein interactions do not exist. This study conducted a mutational analysis of 384 non-redundant antibody-protein antigen complexes to calculate antibody-protein interaction similarity matrices. Every important residue in each antibody and each antigen was mutated to each of the other 19 commonly occurring amino acids and the percentage changes in interaction energies were calculated using three force fields: CHARMM, Amber, and Rosetta. The data were used to construct six interaction similarity matrices, one for antibodies and another for antigens using each force field. The matrices exhibited both commonalities, such as mutations of aromatic and charged residues being the most detrimental, and differences, such as Rosetta predicting mutations of serines to be better tolerated than either Amber or CHARMM. A comparison to nine previously published similarity matrices for protein sequences revealed that the new interaction matrices are more similar to one another than they are to any of the previous matrices. The created similarity matrices can be used in force field specific applications to help guide decisions regarding mutations in protein-protein binding interfaces.

Identifiants

pubmed: 37883504
doi: 10.1371/journal.pone.0293606
pii: PONE-D-23-14979
pmc: PMC10602319
doi:

Substances chimiques

Amber 0
Proteins 0
Amino Acids 0
Antigen-Antibody Complex 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0293606

Subventions

Organisme : NIGMS NIH HHS
ID : R35 GM138220
Pays : United States

Informations de copyright

Copyright: © 2023 Islam, Pantazes. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Sumaiya Islam (S)

Department of Chemical Engineering, Auburn University, Auburn, Alabama, United States of America.

Robert J Pantazes (RJ)

Department of Chemical Engineering, Auburn University, Auburn, Alabama, United States of America.

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Classifications MeSH