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Key interaction networks: Identifying evolutionarily conserved non-covalent interaction networks across protein families
Georgia Inst Technol, Sch Chem & Biochem, Atlanta, GA 30332 USA..
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Biochemistry.ORCID iD: 0000-0003-4709-5353
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular biophysics. Univ Virginia, Dept Mol Physiol, Charlottesville, VA 22903 USA; Univ Virginia, Dept Biomed Engn, Charlottesville, VA USA.ORCID iD: 0000-0002-3111-8103
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Biochemistry. Georgia Inst Technol, Sch Chem & Biochem, Atlanta, GA 30332 USA.ORCID iD: 0000-0002-3190-1173
2024 (English)In: Protein Science, ISSN 0961-8368, E-ISSN 1469-896X, Vol. 33, no 3, article id e4911Article in journal (Refereed) Published
Abstract [en]

Protein structure (and thus function) is dictated by non-covalent interaction networks. These can be highly evolutionarily conserved across protein families, the members of which can diverge in sequence and evolutionary history. Here we present KIN, a tool to identify and analyze conserved non-covalent interaction networks across evolutionarily related groups of proteins. KIN is available for download under a GNU General Public License, version 2, from https://www.github.com/kamerlinlab/KIN. KIN can operate on experimentally determined structures, predicted structures, or molecular dynamics trajectories, providing insight into both conserved and missing interactions across evolutionarily related proteins. This provides useful insight both into protein evolution, as well as a tool that can be exploited for protein engineering efforts. As a showcase system, we demonstrate applications of this tool to understanding the evolutionary-relevant conserved interaction networks across the class A β-lactamases.

Place, publisher, year, edition, pages
John Wiley & Sons, 2024. Vol. 33, no 3, article id e4911
Keywords [en]
protein interaction networks, class A beta-lactamases, protein contact analysis, protein engineering
National Category
Biochemistry Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-524605DOI: 10.1002/pro.4911ISI: 001162377000001PubMedID: 38358258OAI: oai:DiVA.org:uu-524605DiVA, id: diva2:1844042
Part of project
Understanding how Nature harnesses ligand-gated conformational changes to drive enzyme catalysis and evolution, Swedish Research Council
Funder
Swedish Research Council, 2019-03499National Academic Infrastructure for Supercomputing in Sweden (NAISS)NIH (National Institutes of Health), GM138444Swedish National Infrastructure for Computing (SNIC), 2020/5-250Swedish National Infrastructure for Computing (SNIC), 2019/3-258Swedish National Infrastructure for Computing (SNIC), 2019/2-1Available from: 2024-03-12 Created: 2024-03-12 Last updated: 2025-02-20Bibliographically approved

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Crean, Rory M.Kasson, Peter M.Kamerlin, Shina C. L.

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