• Media type: E-Article
  • Title: SBILib: a handle for protein modeling and engineering
  • Contributor: Gohl, Patrick; Bonet, Jaume; Fornes, Oriol; Planas-Iglesias, Joan; Fernandez-Fuentes, Narcís; Oliva, Baldo
  • imprint: Oxford University Press (OUP), 2023
  • Published in: Bioinformatics
  • Language: English
  • DOI: 10.1093/bioinformatics/btad613
  • ISSN: 1367-4811
  • Keywords: Computational Mathematics ; Computational Theory and Mathematics ; Computer Science Applications ; Molecular Biology ; Biochemistry ; Statistics and Probability
  • Origination:
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  • Description: <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Summary</jats:title> <jats:p>The SBILib Python library provides an integrated platform for the analysis of macromolecular structures and interactions. It combines simple 3D file parsing and workup methods with more advanced analytical tools. SBILib includes modules for macromolecular interactions, loops, super-secondary structures, and biological sequences, as well as wrappers for external tools with which to integrate their results and facilitate the comparative analysis of protein structures and their complexes. The library can handle macromolecular complexes formed by proteins and/or nucleic acid molecules (i.e. DNA and RNA). It is uniquely capable of parsing and calculating protein super-secondary structure and loop geometry. We have compiled a list of example scenarios which SBILib may be applied to and provided access to these within the library.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and implementation</jats:title> <jats:p>SBILib is made available on Github at https://github.com/structuralbioinformatics/SBILib.</jats:p> </jats:sec>
  • Access State: Open Access