Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/173974
Title: Structome: a tool for the rapid assembly of datasets for structural phylogenetics
Authors: Malik, Ashar J.
Langer, Desiree
Verma, Chandra Shekhar
Poole, Anthony M.
Allison, Jane R.
Keywords: Medicine, Health and Life Sciences
Issue Date: 2023
Source: Malik, A. J., Langer, D., Verma, C. S., Poole, A. M. & Allison, J. R. (2023). Structome: a tool for the rapid assembly of datasets for structural phylogenetics. Bioinformatics Advances, 3(1), vbad134-. https://dx.doi.org/10.1093/bioadv/vbad134
Journal: Bioinformatics Advances 
Abstract: Protein structures carry signal of common ancestry and can therefore aid in reconstructing their evolutionary histories. To expedite the structure-informed inference process, a web server, Structome, has been developed that allows users to rapidly identify protein structures similar to a query protein and to assemble datasets useful for structure-based phylogenetics. Structome was created by clustering ∼94% of the structures in RCSB PDB using 90% sequence identity and representing each cluster by a centroid structure. Structure similarity between centroid proteins was calculated, and annotations from PDB, SCOP, and CATH were integrated. To illustrate utility, an H3 histone was used as a query, and results show that the protein structures returned by Structome span both sequence and structural diversity of the histone fold. Additionally, the pre-computed nexus-formatted distance matrix, provided by Structome, enables analysis of evolutionary relationships between proteins not identifiable using searches based on sequence similarity alone. Our results demonstrate that, beginning with a single structure, Structome can be used to rapidly generate a dataset of structural neighbours and allows deep evolutionary history of proteins to be studied.
URI: https://hdl.handle.net/10356/173974
ISSN: 2635-0041
DOI: 10.1093/bioadv/vbad134
Schools: School of Biological Sciences 
Organisations: Bioinformatics Institute, A*STAR 
National University of Singapore 
Rights: © 2023 The Author(s). Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SBS Journal Articles

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