Literature DB >> 20061306

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta.

Sidhartha Chaudhury1, Sergey Lyskov, Jeffrey J Gray.   

Abstract

SUMMARY: PyRosetta is a stand-alone Python-based implementation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. AVAILABILITY: PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20061306      PMCID: PMC2828115          DOI: 10.1093/bioinformatics/btq007

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  15 in total

1.  Native protein sequences are close to optimal for their structures.

Authors:  B Kuhlman; D Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

2.  Design of a novel globular protein fold with atomic-level accuracy.

Authors:  Brian Kuhlman; Gautam Dantas; Gregory C Ireton; Gabriele Varani; Barry L Stoddard; David Baker
Journal:  Science       Date:  2003-11-21       Impact factor: 47.728

3.  Protein structure prediction and analysis using the Robetta server.

Authors:  David E Kim; Dylan Chivian; David Baker
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

4.  Toward high-resolution de novo structure prediction for small proteins.

Authors:  Philip Bradley; Kira M S Misura; David Baker
Journal:  Science       Date:  2005-09-16       Impact factor: 47.728

5.  Improved beta-protein structure prediction by multilevel optimization of nonlocal strand pairings and local backbone conformation.

Authors:  Philip Bradley; David Baker
Journal:  Proteins       Date:  2006-12-01

6.  Structure prediction of domain insertion proteins from structures of individual domains.

Authors:  Monica Berrondo; Marc Ostermeier; Jeffrey J Gray
Journal:  Structure       Date:  2008-04       Impact factor: 5.006

7.  Structure prediction for CASP8 with all-atom refinement using Rosetta.

Authors:  Srivatsan Raman; Robert Vernon; James Thompson; Michael Tyka; Ruslan Sadreyev; Jimin Pei; David Kim; Elizabeth Kellogg; Frank DiMaio; Oliver Lange; Lisa Kinch; Will Sheffler; Bong-Hyun Kim; Rhiju Das; Nick V Grishin; David Baker
Journal:  Proteins       Date:  2009

8.  Three-dimensional structure of a recombinant variant of human pancreatic secretory trypsin inhibitor (Kazal type).

Authors:  H J Hecht; M Szardenings; J Collins; D Schomburg
Journal:  J Mol Biol       Date:  1992-06-20       Impact factor: 5.469

9.  Conformer selection and induced fit in flexible backbone protein-protein docking using computational and NMR ensembles.

Authors:  Sidhartha Chaudhury; Jeffrey J Gray
Journal:  J Mol Biol       Date:  2008-05-24       Impact factor: 5.469

10.  The RosettaDock server for local protein-protein docking.

Authors:  Sergey Lyskov; Jeffrey J Gray
Journal:  Nucleic Acids Res       Date:  2008-04-28       Impact factor: 16.971

View more
  222 in total

1.  InteractiveROSETTA: a graphical user interface for the PyRosetta protein modeling suite.

Authors:  Christian D Schenkelberg; Christopher Bystroff
Journal:  Bioinformatics       Date:  2015-08-26       Impact factor: 6.937

2.  Structural Insight into Specificity of Interactions between Nonconventional Three-finger Weak Toxin from Naja kaouthia (WTX) and Muscarinic Acetylcholine Receptors.

Authors:  Ekaterina N Lyukmanova; Zakhar O Shenkarev; Mikhail A Shulepko; Alexander S Paramonov; Anton O Chugunov; Helena Janickova; Eva Dolejsi; Vladimir Dolezal; Yuri N Utkin; Victor I Tsetlin; Alexander S Arseniev; Roman G Efremov; Dmitry A Dolgikh; Mikhail P Kirpichnikov
Journal:  J Biol Chem       Date:  2015-08-04       Impact factor: 5.157

3.  Protein backbone ensemble generation explores the local structural space of unseen natural homologs.

Authors:  Christian D Schenkelberg; Christopher Bystroff
Journal:  Bioinformatics       Date:  2016-01-18       Impact factor: 6.937

4.  A Unified De Novo Approach for Predicting the Structures of Ordered and Disordered Proteins.

Authors:  John J Ferrie; E James Petersson
Journal:  J Phys Chem B       Date:  2020-06-11       Impact factor: 2.991

Review 5.  A humanized yeast system to analyze cleavage of prelamin A by ZMPSTE24.

Authors:  Eric D Spear; Rebecca F Alford; Tim D Babatz; Kaitlin M Wood; Otto W Mossberg; Kamsi Odinammadu; Khurts Shilagardi; Jeffrey J Gray; Susan Michaelis
Journal:  Methods       Date:  2019-01-06       Impact factor: 3.608

6.  Structural Diversity in the Type IV Pili of Multidrug-resistant Acinetobacter.

Authors:  Kurt H Piepenbrink; Erik Lillehoj; Christian M Harding; Jason W Labonte; Xiaotong Zuo; Chelsea A Rapp; Robert S Munson; Simeon E Goldblum; Mario F Feldman; Jeffrey J Gray; Eric J Sundberg
Journal:  J Biol Chem       Date:  2016-09-15       Impact factor: 5.157

7.  Chimeric peptides as implant functionalization agents for titanium alloy implants with antimicrobial properties.

Authors:  Deniz T Yucesoy; Marketa Hnilova; Kyle Boone; Paul M Arnold; Malcolm L Snead; Candan Tamerler
Journal:  JOM (1989)       Date:  2015-04       Impact factor: 2.471

8.  Expanding the toolkit for membrane protein modeling in Rosetta.

Authors:  Julia Koehler Leman; Benjamin K Mueller; Jeffrey J Gray
Journal:  Bioinformatics       Date:  2017-03-01       Impact factor: 6.937

9.  Peptide backbone circularization enhances antifreeze protein thermostability.

Authors:  Corey A Stevens; Joanna Semrau; Dragos Chiriac; Morgan Litschko; Robert L Campbell; David N Langelaan; Steven P Smith; Peter L Davies; John S Allingham
Journal:  Protein Sci       Date:  2017-07-25       Impact factor: 6.725

10.  Rosetta Machine Learning Models Accurately Classify Positional Effects of Thioamides on Proteolysis.

Authors:  Sam Giannakoulias; Sumant R Shringari; Chunxiao Liu; Hoang Anh T Phan; Taylor M Barrett; John J Ferrie; E James Petersson
Journal:  J Phys Chem B       Date:  2020-09-01       Impact factor: 2.991

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.