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Scoria: a Python module for manipulating 3D molecular data

Ropp, Patrick and Friedman, Aaron and Durrant, Jacob D. (2017) Scoria: a Python module for manipulating 3D molecular data. Journal of Cheminformatics, 9 (52). ISSN 1758-2946

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Abstract

Third-party packages have transformed the Python programming language into a powerful computational-biology tool. Package installation is easy for experienced users, but novices sometimes struggle with dependencies and compilers. This presents a barrier that can hinder the otherwise broad adoption of new tools. We present Scoria, a Python package for manipulating three-dimensional molecular data. Unlike similar packages, Scoria requires no dependencies, compilation, or system-wide installation. One can incorporate the Scoria source code directly into their own programs. But Scoria is not designed to compete with other similar packages. Rather, it complements them. Our package leverages others (e.g. NumPy, SciPy), if present, to speed and extend its own functionality. To show its utility, we use Scoria to analyze a molecular dynamics trajectory. Our FootPrint script colors the atoms of one chain by the frequency of their contacts with a second chain. We are hopeful that Scoria will be a useful tool for the computational-biology community. A copy is available for download free of charge (Apache License 2.0) at http://durrantlab.com/scoria/ .


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ropp, Patrick
Friedman, Aaron
Durrant, Jacob D.durrantj@pitt.edu
Date: 2017
Date Type: Publication
Journal or Publication Title: Journal of Cheminformatics
Volume: 9
Number: 52
Publisher: BMC
DOI or Unique Handle: 10.1186/s13321-017-0237-8
Schools and Programs: Dietrich School of Arts and Sciences > Biological Sciences
Refereed: Yes
Uncontrolled Keywords: molecular modeling, structural biology, computational biology, Python
ISSN: 1758-2946
Official URL: https://jcheminf.biomedcentral.com/articles/10.118...
Date Deposited: 13 May 2020 14:59
Last Modified: 13 May 2020 14:59
URI: http://d-scholarship.pitt.edu/id/eprint/38983

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