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HaloClass: Salt-Tolerant Protein Classification with Protein Language Models.

Authors :
Narang, Kush
Nath, Abhigyan
Hemstrom, William
Chu, Simon K. S.
Source :
Protein Journal. Dec2024, Vol. 43 Issue 6, p1035-1044. 10p.
Publication Year :
2024

Abstract

Salt-tolerant proteins, also known as halophilic proteins, have unique adaptations to function in high-salinity environments. These proteins have naturally evolved in extremophilic organisms, and more recently, are being increasingly applied as enzymes in industrial processes. Due to an abundance of salt-tolerant sequences and a simultaneous lack of experimental structures, most computational methods to predict stability are sequence-based only. These approaches, however, are hindered by a lack of structural understanding of these proteins. Here, we present HaloClass, an SVM classifier that leverages ESM-2 protein language model embeddings to accurately identify salt-tolerant proteins. On a newer and larger test dataset, HaloClass outperforms existing approaches when predicting the stability of never-before-seen proteins that are distal to its training set. Finally, on a mutation study that evaluated changes in salt tolerance based on single- and multiple-point mutants, HaloClass outperforms existing approaches, suggesting applications in the guided design of salt-tolerant enzymes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15723887
Volume :
43
Issue :
6
Database :
Academic Search Index
Journal :
Protein Journal
Publication Type :
Academic Journal
Accession number :
180734851
Full Text :
https://doi.org/10.1007/s10930-024-10236-7