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ProMod3-A versatile homology modelling toolbox
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4615143
Author(s) Studer, Gabriel; Tauriello, Gerardo; Bienert, Stefan; Biasini, Marco; Johner, Niklaus; Schwede, Torsten
Author(s) at UniBasel Schwede, Torsten
Studer, Gabriel
Tauriello, Gerardo
Bienert, Stefan
Biasini, Marco
Johner, Niklaus
Year 2021
Title ProMod3-A versatile homology modelling toolbox
Journal PLoS Computational Biology
Volume 17
Number 1
Pages / Article-Number e1008667
Keywords protein structure modelling; homology modelling;
Mesh terms Algorithms; Computational Biology, methods; Databases, Protein; Internet; Models, Molecular; Protein Conformation; Proteins, chemistry; Software; Structural Homology, Protein
Abstract Computational methods for protein structure modelling are routinely used to complement experimental structure determination, thus they help to address a broad spectrum of scientific questions in biomedical research. The most accurate methods today are based on homology modelling, i.e. detecting a homologue to the desired target sequence that can be used as a template for modelling. Here we present a versatile open source homology modelling toolbox as foundation for flexible and computationally efficient modelling workflows. ProMod3 is a fully scriptable software platform that can perform all steps required to generate a protein model by homology. Its modular design aims at fast prototyping of novel algorithms and implementing flexible modelling pipelines. Common modelling tasks, such as loop modelling, sidechain modelling or generating a full protein model by homology, are provided as production ready pipelines, forming the starting point for own developments and enhancements. ProMod3 is the central software component of the widely used SWISS-MODEL web-server.
Publisher Library of Science
ISSN/ISBN 1553-734X ; 1553-7358
edoc-URL https://edoc.unibas.ch/81614/
Full Text on edoc No
Digital Object Identifier DOI 10.1371/journal.pcbi.1008667
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/33507980
ISI-Number WOS:000613893300008
Document type (ISI) Journal Article
 
   

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01/05/2024