TY - JOUR
T1 - Computational function prediction of bacteria and phage proteins
AU - Grigson, Susanna R.
AU - Bouras, George
AU - Dutilh, Bas E.
AU - Olson, Robert D.
AU - Edwards, Robert A.
PY - 2025/9
Y1 - 2025/9
N2 - SUMMARY: 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.
AB - SUMMARY: 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.
KW - bioinformatics
KW - function prediction
KW - machine learning
KW - microbial proteins
UR - http://www.scopus.com/inward/record.url?scp=105017092999&partnerID=8YFLogxK
UR - http://purl.org/au-research/grants/ARC/DP250103825
UR - http://purl.org/au-research/grants/ARC/DP220102915
UR - http://purl.org/au-research/grants/ARC/FL250100019
U2 - 10.1128/mmbr.00022-25
DO - 10.1128/mmbr.00022-25
M3 - Article
C2 - 40824055
AN - SCOPUS:105017092999
SN - 1092-2172
VL - 89
SP - 1
EP - 30
JO - Microbiology and molecular biology reviews : MMBR
JF - Microbiology and molecular biology reviews : MMBR
IS - 3
M1 - e0002225
ER -