Literature DB >> 19044803

An analytical approach to computing biomolecular electrostatic potential. II. Validation and applications.

John C Gordon1, Andrew T Fenley, Alexey Onufriev.   

Abstract

An ability to efficiently compute the electrostatic potential produced by molecular charge distributions under realistic solvation conditions is essential for a variety of applications. Here, the simple closed-form analytical approximation to the Poisson equation rigorously derived in Part I for idealized spherical geometry is tested on realistic shapes. The effects of mobile ions are included at the Debye-Huckel level. The accuracy of the resulting closed-form expressions for electrostatic potential is assessed through comparisons with numerical Poisson-Boltzmann (NPB) reference solutions on a test set of 580 representative biomolecular structures under typical conditions of aqueous solvation. For each structure, the deviation from the reference is computed for a large number of test points placed near the dielectric boundary (molecular surface). The accuracy of the approximation, averaged over all test points in each structure, is within 0.6 kcal/mol/mid R:emid R: approximately kT per unit charge for all structures in the test set. For 91.5% of the individual test points, the deviation from the NPB potential is within 0.6 kcal/mol/mid R:emid R:. The deviations from the reference decrease with increasing distance from the dielectric boundary: The approximation is asymptotically exact far away from the source charges. Deviation of the overall shape of a structure from ideal spherical does not, by itself, appear to necessitate decreased accuracy of the approximation. The largest deviations from the NPB reference are found inside very deep and narrow indentations that occur on the dielectric boundaries of some structures. The dimensions of these pockets of locally highly negative curvature are comparable to the size of a water molecule; the applicability of a continuum dielectric models in these regions is discussed. The maximum deviations from the NPB are reduced substantially when the boundary is smoothed by using a larger probe radius (3 A) to generate the molecular surface. A detailed accuracy analysis is presented for several proteins of various shapes, including lysozyme whose surface features a functionally relevant region of negative curvature. The proposed analytical model is computationally inexpensive; this strength of the approach is demonstrated by computing and analyzing the electrostatic potential generated by a full capsid of the tobacco ring spot virus at atomic resolution (500 000 atoms). An analysis of the electrostatic potential of the inner surface of the capsid reveals what might be a RNA binding pocket. These results are generated with the modest computational power of a desktop personal computer.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 19044803      PMCID: PMC2671192          DOI: 10.1063/1.2956499

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  28 in total

1.  Tanford-Kirkwood electrostatics for protein modeling.

Authors:  J J Havranek; P B Harbury
Journal:  Proc Natl Acad Sci U S A       Date:  1999-09-28       Impact factor: 11.205

2.  pH dependence of stability of staphylococcal nuclease: evidence of substantial electrostatic interactions in the denatured state.

Authors:  S T Whitten; B García-Moreno E
Journal:  Biochemistry       Date:  2000-11-21       Impact factor: 3.162

3.  Electrostatics of nanosystems: application to microtubules and the ribosome.

Authors:  N A Baker; D Sept; S Joseph; M J Holst; J A McCammon
Journal:  Proc Natl Acad Sci U S A       Date:  2001-08-21       Impact factor: 11.205

4.  Accelerated Poisson-Boltzmann calculations for static and dynamic systems.

Authors:  Ray Luo; Laurent David; Michael K Gilson
Journal:  J Comput Chem       Date:  2002-10       Impact factor: 3.376

5.  pKa's of ionizable groups in proteins: atomic detail from a continuum electrostatic model.

Authors:  D Bashford; M Karplus
Journal:  Biochemistry       Date:  1990-11-06       Impact factor: 3.162

6.  Calculations of enzymatic reactions: calculations of pKa, proton transfer reactions, and general acid catalysis reactions in enzymes.

Authors:  A Warshel
Journal:  Biochemistry       Date:  1981-05-26       Impact factor: 3.162

7.  Similar structure and reactivity of satellite tobacco ringspot virus RNA obtained from infected tissue and by in vitro transcription.

Authors:  B K Passmore; G Bruening
Journal:  Virology       Date:  1993-11       Impact factor: 3.616

8.  Analysis of integral expressions for effective Born radii.

Authors:  John Mongan; W Andreas Svrcek-Seiler; Alexey Onufriev
Journal:  J Chem Phys       Date:  2007-11-14       Impact factor: 3.488

9.  Expression of tobacco ringspot virus capsid protein and satellite RNA in insect cells and three-dimensional structure of tobacco ringspot virus-like particles.

Authors:  S Singh; R Rothnagel; B V Prasad; B Buckley
Journal:  Virology       Date:  1995-11-10       Impact factor: 3.616

10.  Electrostatic properties of cowpea chlorotic mottle virus and cucumber mosaic virus capsids.

Authors:  Robert Konecny; Joanna Trylska; Florence Tama; Deqiang Zhang; Nathan A Baker; Charles L Brooks; J A McCammon
Journal:  Biopolymers       Date:  2006-06-05       Impact factor: 2.505

View more
  11 in total

1.  Accelerating electrostatic surface potential calculation with multi-scale approximation on graphics processing units.

Authors:  Ramu Anandakrishnan; Tom R W Scogland; Andrew T Fenley; John C Gordon; Wu-chun Feng; Alexey V Onufriev
Journal:  J Mol Graph Model       Date:  2010-06       Impact factor: 2.518

Review 2.  Progress in the prediction of pKa values in proteins.

Authors:  Emil Alexov; Ernest L Mehler; Nathan Baker; António M Baptista; Yong Huang; Francesca Milletti; Jens Erik Nielsen; Damien Farrell; Tommy Carstensen; Mats H M Olsson; Jana K Shen; Jim Warwicker; Sarah Williams; J Michael Word
Journal:  Proteins       Date:  2011-10-15

3.  A Fast and Robust Poisson-Boltzmann Solver Based on Adaptive Cartesian Grids.

Authors:  Alexander H Boschitsch; Marcia O Fenley
Journal:  J Chem Theory Comput       Date:  2011-05-10       Impact factor: 6.006

4.  PB-AM: An open-source, fully analytical linear poisson-boltzmann solver.

Authors:  Lisa E Felberg; David H Brookes; Eng-Hui Yap; Elizabeth Jurrus; Nathan A Baker; Teresa Head-Gordon
Journal:  J Comput Chem       Date:  2016-11-02       Impact factor: 3.376

5.  A strategy for reducing gross errors in the generalized Born models of implicit solvation.

Authors:  Alexey V Onufriev; Grigori Sigalov
Journal:  J Chem Phys       Date:  2011-04-28       Impact factor: 3.488

6.  Bluues: a program for the analysis of the electrostatic properties of proteins based on generalized Born radii.

Authors:  Federico Fogolari; Alessandra Corazza; Vijaylakshmi Yarra; Anusha Jalaru; Paolo Viglino; Gennaro Esposito
Journal:  BMC Bioinformatics       Date:  2012-03-28       Impact factor: 3.169

7.  Multi-dimensional characterization of electrostatic surface potential computation on graphics processors.

Authors:  Mayank Daga; Wu-Chun Feng
Journal:  BMC Bioinformatics       Date:  2012-04-12       Impact factor: 3.169

8.  Active site detection by spatial conformity and electrostatic analysis--unravelling a proteolytic function in shrimp alkaline phosphatase.

Authors:  Sandeep Chakraborty; Renu Minda; Lipika Salaye; Swapan K Bhattacharjee; Basuthkar J Rao
Journal:  PLoS One       Date:  2011-12-08       Impact factor: 3.240

9.  Why double-stranded RNA resists condensation.

Authors:  Igor S Tolokh; Suzette A Pabit; Andrea M Katz; Yujie Chen; Aleksander Drozdetski; Nathan Baker; Lois Pollack; Alexey V Onufriev
Journal:  Nucleic Acids Res       Date:  2014-08-14       Impact factor: 16.971

10.  Point charges optimally placed to represent the multipole expansion of charge distributions.

Authors:  Ramu Anandakrishnan; Charles Baker; Saeed Izadi; Alexey V Onufriev
Journal:  PLoS One       Date:  2013-07-04       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.