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Article

Predicting Natural Evolution in the RBD Region of the Spike Glycoprotein of SARS-CoV-2 by Machine Learning.

Viruses - 20 Mar 2024

Liu Yiheng, He Zitong, Jia Liyiyang, Xue Yiwei, Du Yuxuan, Tan Huiwen, Zhang Xianzhi, Ji Yu, Tong Yigang, Xu Haijun, Liu Luo

Abstract excerpt

Machine learning (ML) is a key focus in predicting protein mutations and aiding directed evolution. Research on potential virus variants is crucial for vaccine development. In this study, the machine learning software PyPEF was employed to conduct mutation analysis within the receptor-binding domain (RBD) of the Spike glycoprotein of SARS-CoV-2. Over 48,960,000 variants were predicted. Eight prospective variants...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 38543841
DOI: 10.3390/v16030477
PMCID: PMC10974066

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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