Literature DB >> 21112303

Brownian dynamics simulation of protein solutions: structural and dynamical properties.

Paolo Mereghetti1, Razif R Gabdoulline, Rebecca C Wade.   

Abstract

The study of solutions of biomacromolecules provides an important basis for understanding the behavior of many fundamental cellular processes, such as protein folding, self-assembly, biochemical reactions, and signal transduction. Here, we describe a Brownian dynamics simulation procedure and its validation for the study of the dynamic and structural properties of protein solutions. In the model used, the proteins are treated as atomically detailed rigid bodies moving in a continuum solvent. The protein-protein interaction forces are described by the sum of electrostatic interaction, electrostatic desolvation, nonpolar desolvation, and soft-core repulsion terms. The linearized Poisson-Boltzmann equation is solved to compute electrostatic terms. Simulations of homogeneous solutions of three different proteins with varying concentrations, pH, and ionic strength were performed. The results were compared to experimental data and theoretical values in terms of long-time self-diffusion coefficients, second virial coefficients, and structure factors. The results agree with the experimental trends and, in many cases, experimental values are reproduced quantitatively. There are no parameters specific to certain protein types in the interaction model, and hence the model should be applicable to the simulation of the behavior of mixtures of macromolecules in cell-like crowded environments.
Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21112303      PMCID: PMC2998633          DOI: 10.1016/j.bpj.2010.10.035

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  51 in total

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2.  Calculation of weak protein-protein interactions: the pH dependence of the second virial coefficient.

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Journal:  Biophys J       Date:  2001-02       Impact factor: 4.033

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Authors:  A P Minton
Journal:  J Biol Chem       Date:  2001-02-15       Impact factor: 5.157

4.  Computer simulation of protein-protein association kinetics: acetylcholinesterase-fasciculin.

Authors:  A H Elcock; R R Gabdoulline; R C Wade; J A McCammon
Journal:  J Mol Biol       Date:  1999-08-06       Impact factor: 5.469

5.  Growth of (101) faces of tetragonal lysozyme crystals: measured growth-rate trends.

Authors:  E L Forsythe; A Nadarajah; M L Pusey
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  1999-05

6.  Measured and calculated effects of mutations in bacteriophage T4 lysozyme on interactions in solution.

Authors:  R C Chang; D Asthagiri; A M Lenhoff
Journal:  Proteins       Date:  2000-10-01

7.  The BPTI decamer observed in acidic pH crystal forms pre-exists as a stable species in solution.

Authors:  C Hamiaux; J Pérez; T Prangé; S Veesler; M Riès-Kautt; P Vachette
Journal:  J Mol Biol       Date:  2000-03-31       Impact factor: 5.469

8.  Decamers observed in the crystals of bovine pancreatic trypsin inhibitor.

Authors:  J Lubkowski; A Wlodawer
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  1999-01-01

9.  The decameric structure of bovine pancreatic trypsin inhibitor (BPTI) crystallized from thiocyanate at 2.7 A resolution.

Authors:  C Hamiaux; T Prangé; M Riès-Kautt; A Ducruix; S Lafont; J P Astier; S Veesler
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  1999-01-01

10.  Effect of glycerol on the interactions and solubility of bovine pancreatic trypsin inhibitor.

Authors:  M Farnum; C Zukoski
Journal:  Biophys J       Date:  1999-05       Impact factor: 4.033

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  33 in total

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Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

4.  The shape of protein crowders is a major determinant of protein diffusion.

Authors:  Jessica Balbo; Paolo Mereghetti; Dirk-Peter Herten; Rebecca C Wade
Journal:  Biophys J       Date:  2013-04-02       Impact factor: 4.033

5.  Perspective: On the importance of hydrodynamic interactions in the subcellular dynamics of macromolecules.

Authors:  Jeffrey Skolnick
Journal:  J Chem Phys       Date:  2016-09-14       Impact factor: 3.488

6.  Fast Method for Computing Chemical Potentials and Liquid-Liquid Phase Equilibria of Macromolecular Solutions.

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Journal:  J Phys Chem B       Date:  2016-07-05       Impact factor: 2.991

7.  A Multiscale Computational Model for Simulating the Kinetics of Protein Complex Assembly.

Authors:  Jiawen Chen; Yinghao Wu
Journal:  Methods Mol Biol       Date:  2018

8.  Protein charge and mass contribute to the spatio-temporal dynamics of protein-protein interactions in a minimal proteome.

Authors:  Yu Xu; Hong Wang; Ruth Nussinov; Buyong Ma
Journal:  Proteomics       Date:  2013-03-18       Impact factor: 3.984

9.  Simulation and Modeling of Crowding Effects on the Thermodynamic and Kinetic Properties of Proteins with Atomic Details.

Authors:  Huan-Xiang Zhou; Sanbo Qin
Journal:  Biophys Rev       Date:  2013-06-01

10.  Polymer crowders and protein crowders act similarly on protein folding stability.

Authors:  Huan-Xiang Zhou
Journal:  FEBS Lett       Date:  2013-01-23       Impact factor: 4.124

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