論文

基本情報

氏名 児島 一州
氏名(カナ) コジマ イッシュウ
氏名(英語) Kojima Isshu
所属 獣医学部 獣医学科
職名 助教
researchmap研究者コード R000055330
researchmap機関 岡山理科大学

題名

A protein language model for exploring viral fitness landscapes

単著・共著の別

共著

著者

Ito J, Strange A, Liu W, Joas G, Lytras S; Genotype to Phenotype Japan (G2P-Japan) Consortium; Sato K.

概要

Successively emerging SARS-CoV-2 variants lead to repeated epidemic surges through escalated fitness (i.e., relative effective reproduction number between variants). Modeling the genotype-fitness relationship enables us to pinpoint the mutations boosting viral fitness and flag high-risk variants immediately after their detection. Here, we present CoVFit, a protein language model adapted from ESM-2, designed to predict variant fitness based solely on spike protein sequences. CoVFit was trained on genotype-fitness data derived from viral genome surveillance and functional mutation assays related to immune evasion. CoVFit successively ranked the fitness of unknown future variants harboring nearly 15 mutations with informative accuracy. CoVFit identified 959 fitness elevation events throughout SARS-CoV-2 evolution until late 2023. Furthermore, we show that CoVFit is applicable for predicting viral evolution through single amino acid mutations. Our study gives insight into the SARS-CoV-2 fitness landscape and provides a tool for efficiently identifying SARS-CoV-2 variants with higher epidemic risk.

発表雑誌等の名称

Nature communication

出版者

13

16

開始ページ

1

終了ページ

発行又は発表の年月

2025/05

査読の有無

有り

招待の有無

無し

記述言語

英語

掲載種別

研究論文(学術雑誌)

ISSN

ID:DOI

10.1038/s41467-025-59422-w.

ID:NAID(CiNiiのID)

ID:PMID

40360496

URL

JGlobalID

arXiv ID

ORCIDのPut Code

DBLP ID