Lessons from application of the UNRES force field to predictions of structures of CASP10 targets - Wikidata - awgldk - TriplyDB

Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

http://www.wikidata.org/entity/Q30353196

about

My 65 years in protein chemistry Protein folding and de novo protein design for biotechnological applications WeFold: a coopetition for protein structure prediction Peierls-Nabarro barrier and protein loop propagation.Performance of protein-structure predictions with the physics-based UNRES force field in CASP11.Molecular dynamics of protein A and a WW domain with a united-residue model including hydrodynamic interaction Revised Backbone-Virtual-Bond-Angle Potentials to Treat the l- and d-Amino Acid Residues in the Coarse-Grained United Residue (UNRES) Force Field A unified coarse-grained model of biological macromolecules based on mean-field multipole-multipole interactions.Physics-based potentials for the coupling between backbone- and side-chain-local conformational states in the UNited RESidue (UNRES) force field for protein simulations.Physics-Based Potentials for Coarse-Grained Modeling of Protein-DNA Interactions Molecular modeling of the binding modes of the iron-sulfur protein to the Jac1 co-chaperone from Saccharomyces cerevisiae by all-atom and coarse-grained approaches Folding and self-assembly of a small heterotetramer Studies of conformational changes of an arginine-binding protein from Thermotoga maritima in the presence and absence of ligand via molecular dynamics simulations with the coarse-grained UNRES force field.Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information.Ergodicity and model quality in template-restrained canonical and temperature/Hamiltonian replica exchange coarse-grained molecular dynamics simulations of proteins.A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. I. Backbone potentials of coarse-grained polypeptide chains.A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. II. Backbone-local potentials of coarse-grained O1→4-bonded polyglucose chains.Protein homology model refinement by large-scale energy optimization.Extension of coarse-grained UNRES force field to treat carbon nanotubes.UNRES server for physics-based coarse-grained simulations and prediction of protein structure, dynamics and thermodynamics.

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Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

http://www.wikidata.org/entity/Q30353196

description

2013 nî lūn-bûn

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2013 թուականի Օգոստոսին հրատարակուած գիտական յօդուած

@hyw

2013 թվականի օգոստոսին հրատարակված գիտական հոդված

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2013年の論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年论文

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PNAS.1313316110

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Proceedings of the National Academy of Sciences of the United States of America

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Lessons from application of th ...... f structures of CASP10 targets

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Adam K Sieradzan

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Cezary R Czaplewski

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Dawid Jagiela

http://www.w3.org/2001/XMLSchema#string

Khatuna Kachlishvili

http://www.w3.org/2001/XMLSchema#string

Magdalena A Mozolewska

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Pawel Krupa

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Rafał Ślusarz

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Shalom Rackovsky

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Tomasz K Wirecki

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Yi He

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P2860

The protein structure prediction problem could be solved using the current PDB library

Progress and challenges in protein structure prediction

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

Accelerating molecular dynamic simulation on graphics processing units

Mutational Tipping Points for Switching Protein Folds and Functions

The PSIPRED protein structure prediction server

Rosetta in CASP4: progress in ab initio protein structure prediction

Principles that govern the folding of protein chains

Protein structure prediction using Rosetta

Protein structure prediction by global optimization of a potential energy function.

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10.1073/PNAS.1313316110

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37

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Harold A. Scheraga

Stanislaw Oldziej

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2013-08-26T00:00:00Z

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256120386

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