Literature DB >> 17280090

Equilibration of experimentally determined protein structures for molecular dynamics simulation.

Emily B Walton1, Krystyn J Vanvliet.   

Abstract

Preceding molecular dynamics simulations of biomolecular interactions, the molecule of interest is often equilibrated with respect to an initial configuration. This so-called equilibration stage is required because the input structure is typically not within the equilibrium phase space of the simulation conditions, particularly in systems as complex as proteins, which can lead to artifactual trajectories of protein dynamics. The time at which nonequilibrium effects from the initial configuration are minimized-what we will call the equilibration time-marks the beginning of equilibrium phase-space exploration. Note that the identification of this time does not imply exploration of the entire equilibrium phase space. We have found that current equilibration methodologies contain ambiguities that lead to uncertainty in determining the end of the equilibration stage of the trajectory. This results in equilibration times that are either too long, resulting in wasted computational resources, or too short, resulting in the simulation of molecular trajectories that do not accurately represent the physical system. We outline and demonstrate a protocol for identifying the equilibration time that is based on the physical model of Normal Mode Analysis. We attain the computational efficiency required of large-protein simulations via a stretched exponential approximation that enables an analytically tractable and physically meaningful form of the root-mean-square deviation of atoms comprising the protein. We find that the fitting parameters (which correspond to physical properties of the protein) fluctuate initially but then stabilize for increased simulation time, independently of the simulation duration or sampling frequency. We define the end of the equilibration stage--and thus the equilibration time--as the point in the simulation when these parameters attain constant values. Compared to existing methods, our approach provides the objective identification of the time at which the simulated biomolecule has entered an energetic basin. For the representative protein considered, bovine pancreatic trypsin inhibitor, existing methods indicate a range of 0.2-10 ns of simulation until a local minimum is attained. Our approach identifies a substantially narrower range of 4.5-5.5 ns , which will lead to a much more objective choice of equilibration time.

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Year:  2006        PMID: 17280090     DOI: 10.1103/PhysRevE.74.061901

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  12 in total

1.  Construction, MD simulation, and hydrodynamic validation of an all-atom model of a monoclonal IgG antibody.

Authors:  J Paul Brandt; Thomas W Patapoff; Sergio R Aragon
Journal:  Biophys J       Date:  2010-08-04       Impact factor: 4.033

2.  Extending Bell's model: how force transducer stiffness alters measured unbinding forces and kinetics of molecular complexes.

Authors:  Emily B Walton; Sunyoung Lee; Krystyn J Van Vliet
Journal:  Biophys J       Date:  2008-01-04       Impact factor: 4.033

3.  Characterizing rare-event property distributions via replicate molecular dynamics simulations of proteins.

Authors:  Ranjani Krishnan; Emily B Walton; Krystyn J Van Vliet
Journal:  J Mol Model       Date:  2009-05-06       Impact factor: 1.810

4.  Modeling and simulation of chemomechanics at the cell-matrix interface.

Authors:  Ranjani Krishnan; Binu Oommen; Emily B Walton; John M Maloney; Krystyn J Van Vliet
Journal:  Cell Adh Migr       Date:  2008-04-17       Impact factor: 3.405

5.  To Keep or Not to Keep? The Question of Crystallographic Waters for Enzyme Simulations in Organic Solvent.

Authors:  Jayangika N Dahanayake; Devaki N Gautam; Rajni Verma; Katie R Mitchell-Koch
Journal:  Mol Simul       Date:  2016-03-22       Impact factor: 2.178

6.  A protocol for preparing explicitly solvated systems for stable molecular dynamics simulations.

Authors:  Daniel R Roe; Bernard R Brooks
Journal:  J Chem Phys       Date:  2020-08-07       Impact factor: 3.488

7.  Intrinsically disordered inhibitor of glutamine synthetase is a functional protein with random-coil-like pKa values.

Authors:  Concetta Cozza; José L Neira; Francisco J Florencio; M Isabel Muro-Pastor; Bruno Rizzuti
Journal:  Protein Sci       Date:  2017-03-27       Impact factor: 6.725

8.  Efficient calculation of molecular configurational entropies using an information theoretic approximation.

Authors:  Bracken M King; Nathaniel W Silver; Bruce Tidor
Journal:  J Phys Chem B       Date:  2012-02-22       Impact factor: 2.991

9.  A Multiscale Model to Predict Neuronal Cell Deformation with Varying Extracellular Matrix Stiffness and Topography.

Authors:  Mohan Yasodharababu; Arun K Nair
Journal:  Cell Mol Bioeng       Date:  2020-05-04       Impact factor: 2.321

10.  Investigation of the Selectivity of L-Type Voltage-Gated Calcium Channels 1.3 for Pyrimidine-2,4,6-Triones Derivatives Based on Molecular Dynamics Simulation.

Authors:  Qi Ye; Zhenyu Zhang; Wenying Zhang; Yushan Ding; Fan Zhao; Jinghai Zhang; Yongbo Song
Journal:  Molecules       Date:  2020-11-20       Impact factor: 4.411

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