Journal of Chemical Theory and Computation · 2013 · 20 citations · 71 references
Natural SciencesBiophysicsComputational BiophysicsComputational ChemistryStructural BiologyComputational Structural BiologyMacromolecular Structure DeterminationMolecular DynamicsProtein DynamicsProtein StructureProtein Structure ModelingElastic Network ModelsMolecular Dynamics Of ProteinsNormal ModesProtein Conformational DynamicsProtein Dynamics AnalysisProtein Dynamics ModelingRoot-mean-square DeviationStructure-based Models
A computational method called the progressive fluctuation matching (PFM) is developed for constructing robust heterogeneous anisotropic network models (HANMs) for biomolecular systems. An HANM derived through the PFM approach consists of harmonic springs with realistic positive force constants, and yields the calculated B-factors that are basically identical to the experimental ones. For the four tested protein systems including crambin, trypsin inhibitor, HIV-1 protease, and lysozyme, the root-mean-square deviations between the experimental and the computed B-factors are only 0.060, 0.095, 0.247, and 0.049 Å(2), respectively, and the correlation coefficients are 0.99 for all. By comparing the HANM/ANM normal modes to their counterparts derived from both an atomistic force field and an NMR structure ensemble, it is found that HANM may provide more accurate results on protein dynamics.
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The Amber biomolecular simulation programs
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