Literature DB >> 23619610

PHAISTOS: a framework for Markov chain Monte Carlo simulation and inference of protein structure.

Wouter Boomsma1, Jes Frellsen, Tim Harder, Sandro Bottaro, Kristoffer E Johansson, Pengfei Tian, Kasper Stovgaard, Christian Andreetta, Simon Olsson, Jan B Valentin, Lubomir D Antonov, Anders S Christensen, Mikael Borg, Jan H Jensen, Kresten Lindorff-Larsen, Jesper Ferkinghoff-Borg, Thomas Hamelryck.   

Abstract

We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force-fields are available within the framework: PROFASI and OPLS-AA/L, the latter including the generalized Born surface area solvent model. A flexible command-line and configuration-file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net. The software is implemented in C++ and has been tested on Linux and OSX platforms.
Copyright © 2013 Wiley Periodicals, Inc.

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Year:  2013        PMID: 23619610     DOI: 10.1002/jcc.23292

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  18 in total

1.  Structure of the Bacterial Cytoskeleton Protein Bactofilin by NMR Chemical Shifts and Sequence Variation.

Authors:  Maher M Kassem; Yong Wang; Wouter Boomsma; Kresten Lindorff-Larsen
Journal:  Biophys J       Date:  2016-06-07       Impact factor: 4.033

2.  Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts.

Authors:  Wouter Boomsma; Pengfei Tian; Jes Frellsen; Jesper Ferkinghoff-Borg; Thomas Hamelryck; Kresten Lindorff-Larsen; Michele Vendruscolo
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-05       Impact factor: 11.205

3.  Native State of Complement Protein C3d Analysed via Hydrogen Exchange and Conformational Sampling.

Authors:  Didier Devaurs; Malvina Papanastasiou; Dinler A Antunes; Jayvee R Abella; Mark Moll; Daniel Ricklin; John D Lambris; Lydia E Kavraki
Journal:  Int J Comput Biol Drug Des       Date:  2018-03-24

4.  Bayesian inference of protein structure from chemical shift data.

Authors:  Lars A Bratholm; Anders S Christensen; Thomas Hamelryck; Jan H Jensen
Journal:  PeerJ       Date:  2015-03-24       Impact factor: 2.984

5.  Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics.

Authors:  Anders S Christensen; Troels E Linnet; Mikael Borg; Wouter Boomsma; Kresten Lindorff-Larsen; Thomas Hamelryck; Jan H Jensen
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

6.  An efficient algorithm to perform local concerted movements of a chain molecule.

Authors:  Stefano Zamuner; Alex Rodriguez; Flavio Seno; Antonio Trovato
Journal:  PLoS One       Date:  2015-03-31       Impact factor: 3.240

7.  Transcribing Genes the Hard Way: In Vitro Reconstitution of Nanoarchaeal RNA Polymerase Reveals Unusual Active Site Properties.

Authors:  Sven Nottebaum; Robert O J Weinzierl
Journal:  Front Mol Biosci       Date:  2021-05-11

Review 8.  Atomistic Monte Carlo simulation of lipid membranes.

Authors:  Daniel Wüstner; Heinz Sklenar
Journal:  Int J Mol Sci       Date:  2014-01-24       Impact factor: 5.923

9.  Inference of structure ensembles of flexible biomolecules from sparse, averaged data.

Authors:  Simon Olsson; Jes Frellsen; Wouter Boomsma; Kanti V Mardia; Thomas Hamelryck
Journal:  PLoS One       Date:  2013-11-07       Impact factor: 3.240

10.  A Monte Carlo Study of the Early Steps of Functional Amyloid Formation.

Authors:  Pengfei Tian; Kresten Lindorff-Larsen; Wouter Boomsma; Mogens Høgh Jensen; Daniel Erik Otzen
Journal:  PLoS One       Date:  2016-01-08       Impact factor: 3.240

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