Using residue interaction networks to understand protein function and evolution and to engineer new proteins
(2024) In Current Opinion in Structural Biology 89.- Abstract
Residue interaction networks (RINs) provide graph-based representations of interaction networks within proteins, providing important insight into the factors driving protein structure, function, and stability relationships. There exists a wide range of tools with which to perform RIN analysis, taking into account different types of interactions, input (crystal structures, simulation trajectories, single proteins, or comparative analysis across proteins), as well as formats, including standalone software, web server, and a web application programming interface (API). In particular, the ability to perform comparative RIN analysis across protein families using "metaRINs" provides a valuable tool with which to dissect protein evolution.... (More)
Residue interaction networks (RINs) provide graph-based representations of interaction networks within proteins, providing important insight into the factors driving protein structure, function, and stability relationships. There exists a wide range of tools with which to perform RIN analysis, taking into account different types of interactions, input (crystal structures, simulation trajectories, single proteins, or comparative analysis across proteins), as well as formats, including standalone software, web server, and a web application programming interface (API). In particular, the ability to perform comparative RIN analysis across protein families using "metaRINs" provides a valuable tool with which to dissect protein evolution. This, in turn, highlights hotspots to avoid (or target) for in vitro evolutionary studies, providing a powerful framework that can be exploited to engineer new proteins.
(Less)
- author
- Yehorova, Dariia ; Di Geronimo, Bruno ; Robinson, Michael ; Kasson, Peter M and Kamerlin, Shina C L
- publishing date
- 2024-12
- type
- Contribution to journal
- publication status
- published
- keywords
- Proteins/chemistry, Protein Engineering/methods, Evolution, Molecular, Software, Models, Molecular, Humans, Protein Interaction Maps, Protein Conformation
- in
- Current Opinion in Structural Biology
- volume
- 89
- article number
- 102922
- publisher
- Elsevier
- external identifiers
-
- pmid:39332048
- scopus:85204906169
- ISSN
- 1879-033X
- DOI
- 10.1016/j.sbi.2024.102922
- language
- English
- LU publication?
- no
- additional info
- Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.
- id
- 1569850a-d06a-4fb8-b2e1-f2a8600ff8af
- date added to LUP
- 2025-01-11 17:58:58
- date last changed
- 2025-07-14 07:50:48
@article{1569850a-d06a-4fb8-b2e1-f2a8600ff8af,
abstract = {{<p>Residue interaction networks (RINs) provide graph-based representations of interaction networks within proteins, providing important insight into the factors driving protein structure, function, and stability relationships. There exists a wide range of tools with which to perform RIN analysis, taking into account different types of interactions, input (crystal structures, simulation trajectories, single proteins, or comparative analysis across proteins), as well as formats, including standalone software, web server, and a web application programming interface (API). In particular, the ability to perform comparative RIN analysis across protein families using "metaRINs" provides a valuable tool with which to dissect protein evolution. This, in turn, highlights hotspots to avoid (or target) for in vitro evolutionary studies, providing a powerful framework that can be exploited to engineer new proteins.</p>}},
author = {{Yehorova, Dariia and Di Geronimo, Bruno and Robinson, Michael and Kasson, Peter M and Kamerlin, Shina C L}},
issn = {{1879-033X}},
keywords = {{Proteins/chemistry; Protein Engineering/methods; Evolution, Molecular; Software; Models, Molecular; Humans; Protein Interaction Maps; Protein Conformation}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Current Opinion in Structural Biology}},
title = {{Using residue interaction networks to understand protein function and evolution and to engineer new proteins}},
url = {{http://dx.doi.org/10.1016/j.sbi.2024.102922}},
doi = {{10.1016/j.sbi.2024.102922}},
volume = {{89}},
year = {{2024}},
}