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Family-wide analysis of integrin structures predicted by AlphaFold2

Authors :
Heng Zhang
Daniel S. Zhu
Jieqing Zhu
Source :
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 4497-4507 (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Recent advances in protein structure prediction using AlphaFold2, known for its high efficiency and accuracy, have opened new avenues for comprehensive analysis of all structures within a single protein family. In this study, we evaluated the capabilities of AphaFold2 in analyzing integrin structures. Integrins are heterodimeric cell surface receptors composed of a combination of 18 α and 8 β subunits, resulting in a family of 24 different members. Both α and β subunits consist of a large extracellular domain, a short transmembrane domain, and typically, a short cytoplasmic tail. Integrins play a pivotal role in a wide range of cellular functions by recognizing diverse ligands. Despite significant advances in integrin structural studies in recent decades, high-resolution structures have only been determined for a limited subsets of integrin members, thus limiting our understanding of the entire integrin family. Here, we first analyzed the single-chain structures of 18 α and 8 β integrins in the AlphaFold2 protein structure database. We then employed the newly developed AlphaFold2-multimer program to predict the α/β heterodimer structures of all 24 human integrins. The predicted structures show a high level of accuracy for the subdomains of both α and β subunits, offering high-resolution structure insights for all integrin heterodimers. Our comprehensive structural analysis of the entire integrin family unveils a potentially diverse range of conformations among the 24 members, providing a valuable structure database for studies related to integrin structure and function. We further discussed the potential applications and limitations of the AlphaFold2-derived integrin structures.

Details

Language :
English
ISSN :
20010370
Volume :
21
Issue :
4497-4507
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.7a1627377412425ba1fea642df0e94c0
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2023.09.022