Analysis, Modeling, and Target-Specific Predictions of Linear Peptides Inhibiting Virus Entry.

ABSTRACT: Antiviral peptides (AVPs) are bioactive peptides that exhibit the inhibitory activity against viruses through a range of mechanisms. Virus entry inhibitory peptides (VEIPs) make up a specific class of AVPs that can prevent envelope viruses from entering cells. With the growing number of experimentally verified VEIPs, there is an opportunity to use machine learning to predict peptides that inhibit the virus entry. In this paper, we have developed the first target-specific prediction model for the identification of new VEIPs using, along with the peptide sequence characteristics, the attributes of the envelope proteins of the target virus, which overcomes the problem of insufficient data for particular viral strains and improves the predictive ability. The model's performance was evaluated t

SUBMITTER: Vishnepolsky B 

PROVIDER: S-EPMC10701718 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature