| Literature DB >> 35664289 |
Alexander Thomas Julian1, Anne Caroline Mascarenhas Dos Santos1, Jean-François Pombert1.
Abstract
Motivation: Inferring protein function is an integral part of genome annotation and analysis. This process is usually performed in silico, and most in silico inferences are based on sequence homology approaches, which can fail when in presence of divergent sequences. However, because protein structures and their biological roles are intertwined, protein function can also be inferred by searching for structural homology. Many excellent tools have been released in recent years with regards to protein structure prediction, structural homology searches and protein visualization. Unfortunately, these tools are disconnected from each other and often use a web server-based approach that is ill-suited to high-throughput genome-wide analyses. To help assist genome annotation, we built a structural homology-based pipeline called 3DFI (for tridimensional functional inference) leveraging some of the best structural homology tools. This pipeline was built with simplicity of use in mind and enables genome-wide structural homology inferences. Availability and implementation: 3DFI is available on GitHub https://github.com/PombertLab/3DFI under the permissive MIT license. The pipeline is written in Perl and Python.Entities:
Keywords: Computational genomics; Genome annotation; Protein function prediction; Protein structure prediction; Structural bioinformatics
Year: 2021 PMID: 35664289 PMCID: PMC9162058 DOI: 10.1093/bioadv/vbab030
Source DB: PubMed Journal: Bioinform Adv ISSN: 2635-0041