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Journal Abstract Search

178 related items for PubMed ID: 10081959

  • 1. A new Hybrid Monte Carlo algorithm for protein potential function test and structure refinement.
    Zhang H.
    Proteins; 1999 Mar 01; 34(4):464-71. PubMed ID: 10081959
    [Abstract] [Full Text] [Related]

  • 2. Study of the Villin headpiece folding dynamics by combining coarse-grained Monte Carlo evolution and all-atom molecular dynamics.
    De Mori GM, Colombo G, Micheletti C.
    Proteins; 2005 Feb 01; 58(2):459-71. PubMed ID: 15521059
    [Abstract] [Full Text] [Related]

  • 3. Local moves: an efficient algorithm for simulation of protein folding.
    Elofsson A, Le Grand SM, Eisenberg D.
    Proteins; 1995 Sep 01; 23(1):73-82. PubMed ID: 8539252
    [Abstract] [Full Text] [Related]

  • 4. Monte Carlo vs molecular dynamics for all-atom polypeptide folding simulations.
    Ulmschneider JP, Ulmschneider MB, Di Nola A.
    J Phys Chem B; 2006 Aug 24; 110(33):16733-42. PubMed ID: 16913813
    [Abstract] [Full Text] [Related]

  • 5. Ab initio computational modeling of loops in G-protein-coupled receptors: lessons from the crystal structure of rhodopsin.
    Mehler EL, Hassan SA, Kortagere S, Weinstein H.
    Proteins; 2006 Aug 15; 64(3):673-90. PubMed ID: 16729264
    [Abstract] [Full Text] [Related]

  • 6. Local energy landscape flattening: parallel hyperbolic Monte Carlo sampling of protein folding.
    Zhang Y, Kihara D, Skolnick J.
    Proteins; 2002 Aug 01; 48(2):192-201. PubMed ID: 12112688
    [Abstract] [Full Text] [Related]

  • 7. Optimizing physical energy functions for protein folding.
    Fujitsuka Y, Takada S, Luthey-Schulten ZA, Wolynes PG.
    Proteins; 2004 Jan 01; 54(1):88-103. PubMed ID: 14705026
    [Abstract] [Full Text] [Related]

  • 8. Structural mining: self-consistent design on flexible protein-peptide docking and transferable binding affinity potential.
    Liu Z, Dominy BN, Shakhnovich EI.
    J Am Chem Soc; 2004 Jul 14; 126(27):8515-28. PubMed ID: 15238009
    [Abstract] [Full Text] [Related]

  • 9. Protein tertiary structure prediction using a branch and bound algorithm.
    Eyrich VA, Standley DM, Felts AK, Friesner RA.
    Proteins; 1999 Apr 01; 35(1):41-57. PubMed ID: 10090285
    [Abstract] [Full Text] [Related]

  • 10. SPICKER: a clustering approach to identify near-native protein folds.
    Zhang Y, Skolnick J.
    J Comput Chem; 2004 Apr 30; 25(6):865-71. PubMed ID: 15011258
    [Abstract] [Full Text] [Related]

  • 11. Use of residual dipolar couplings as restraints in ab initio protein structure prediction.
    Haliloglu T, Kolinski A, Skolnick J.
    Biopolymers; 2003 Dec 30; 70(4):548-62. PubMed ID: 14648765
    [Abstract] [Full Text] [Related]

  • 12. Generalized-ensemble algorithms: enhanced sampling techniques for Monte Carlo and molecular dynamics simulations.
    Okamoto Y.
    J Mol Graph Model; 2004 May 30; 22(5):425-39. PubMed ID: 15099838
    [Abstract] [Full Text] [Related]

  • 13. Biased fragment distribution in MC simulation of protein folding.
    Martineau E, L'Heureux PJ, Gunn JR.
    J Comput Chem; 2004 Nov 30; 25(15):1895-903. PubMed ID: 15378533
    [Abstract] [Full Text] [Related]

  • 14. Lattice models of peptide aggregation: evaluation of conformational search algorithms.
    Oakley MT, Garibaldi JM, Hirst JD.
    J Comput Chem; 2005 Nov 30; 26(15):1638-46. PubMed ID: 16170797
    [Abstract] [Full Text] [Related]

  • 15. On the multiple-minima problem in the conformational analysis of polypeptides. V. Application of the self-consistent electrostatic field and the electrostatically driven Monte Carlo methods to bovine pancreatic trypsin inhibitor.
    Ripoll DR, Piela L, Vásquez M, Scheraga HA.
    Proteins; 1991 Nov 30; 10(3):188-98. PubMed ID: 1715563
    [Abstract] [Full Text] [Related]

  • 16. Structural refinement of protein segments containing secondary structure elements: Local sampling, knowledge-based potentials, and clustering.
    Zhu J, Xie L, Honig B.
    Proteins; 2006 Nov 01; 65(2):463-79. PubMed ID: 16927337
    [Abstract] [Full Text] [Related]

  • 17. Native atomic burials, supplemented by physically motivated hydrogen bond constraints, contain sufficient information to determine the tertiary structure of small globular proteins.
    Pereira de Araújo AF, Gomes AL, Bursztyn AA, Shakhnovich EI.
    Proteins; 2008 Feb 15; 70(3):971-83. PubMed ID: 17847091
    [Abstract] [Full Text] [Related]

  • 18. Assembly of protein structure from sparse experimental data: an efficient Monte Carlo model.
    Kolinski A, Skolnick J.
    Proteins; 1998 Sep 01; 32(4):475-94. PubMed ID: 9726417
    [Abstract] [Full Text] [Related]

  • 19. Exploration of compact protein conformations using the guided replication Monte Carlo method.
    Solomon JE, Liney D.
    Biopolymers; 1995 Nov 01; 36(5):579-97. PubMed ID: 7578950
    [Abstract] [Full Text] [Related]

  • 20. Progress in protein-protein docking: atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side-chain flexibility.
    Schueler-Furman O, Wang C, Baker D.
    Proteins; 2005 Aug 01; 60(2):187-94. PubMed ID: 15981249
    [Abstract] [Full Text] [Related]

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