Computational function prediction of bacteria and phage proteins.

Authors

Susanna R Grigson, George Bouras, Bas E Dutilh, Robert D Olson, Robert A Edwards

Published in

Microbiology and molecular biology reviews : MMBR. Volume 89. Issue 3. Pages e0002225. Sep 25, 2025. Epub Aug 18, 2025.

Abstract

SUMMARYUnderstanding protein functions is crucial for interpreting microbial life; however, reliable function annotation remains a major challenge in computational biology. Despite significant advances in bioinformatics methods, ~30% of all bacterial and ~65% of all bacteriophage (phage) protein sequences cannot be confidently annotated. In this review, we examine state-of-the-art bioinformatics tools and methodologies for annotating bacterial and phage proteins, particularly those of unknown or poorly characterized function. We describe the process of identifying protein-coding regions and the systems to classify protein functionalities. Additionally, we explore a range of protein annotation methods, from traditional homology-based methods to cutting-edge machine learning models. In doing so, we provide a toolbox for confidently annotating previously unknown bacterial and phage proteins, advancing the discovery of novel functions and our understanding of microbial systems.

PMID:
40824055
Bibliographic data and abstract were imported from PubMed on 13 Oct 2026.

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