Prediction of virus-host associations using protein language models and multiple instance learning.

ABSTRACT: Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep learning method that predicts the host species for viruses from viral sequences only. It also identifies important viral proteins that significantly contribute to host prediction. The method combines a pre-trained large protein language model (ESM) and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than sequence composition features, including amino acids, physiochemical

SUBMITTER: Liu D 

PROVIDER: S-EPMC11614202 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature