Computational function prediction of bacteria and phage proteins
Date
2025
Authors
Grigson, S.R.
Bouras, G.
Dutilh, B.E.
Olson, R.D.
Edwards, R.A.
Editors
van der Meer, J.R.
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Journal article
Citation
Microbiology and Molecular Biology Reviews, 2025; 89(3):e0002225-1-e0002225-30
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Susanna R. Grigson, George Bouras, Bas E. Dutilh, Robert D. Olson, Robert A. Edwards
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Abstract
Understanding 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.
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© 2025 American Society for Microbiology. All Rights Reserved.