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. 2018 Nov 15;34(22):3942-3944.
doi: 10.1093/bioinformatics/bty474.

BioStructMap: a Python tool for integration of protein structure and sequence-based features

Affiliations

BioStructMap: a Python tool for integration of protein structure and sequence-based features

Andrew J Guy et al. Bioinformatics. .

Abstract

Summary: A sliding window analysis over a protein or genomic sequence is commonly performed, and we present a Python tool, BioStructMap, that extends this concept to three-dimensional (3D) space, allowing the application of a 3D sliding window analysis over a protein structure. BioStructMap is easily extensible, allowing the user to apply custom functions to spatially aggregated data. BioStructMap also allows mapping of underlying genomic sequences to protein structures, allowing the user to perform genetic-based analysis over spatially linked codons-this has applications when selection pressures arise at the level of protein structure.

Availability and implementation: The Python BioStructMap package is available at https://github.com/andrewguy/biostructmap and released under the MIT License. An online server implementing standard functionality is available at https://biostructmap.burnet.edu.au.

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
Tajima’s D calculation applied as a 3D sliding window over the protein structure of P. falciparum EBA-175 RII. The F1 and F2 domains are indicated on the monomeric structure. Nucleotide sequences were obtained from P. falciparum isolates from (a) Thailand (n = 48) and (b) Kenya (n = 39) (Verra et al., 2006). The BioStructMap Python package was used to apply Tajima’s D calculations using a 3D sliding window with a radius of 15 Å. The structural model is available via ModBase, accession number: ed998157a605f5e58ed66e198e0ae1ab. Structures were visualized with PyMOL

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