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On-the-fly Numerical Surface Integration for Finite-Difference Poisson-Boltzmann Methods.

Qin Cai1, Xiang Ye2, Jun Wang3

  • 1Department of Biomedical Engineering, University of California, Irvine, California ; Department of Molecular Biology and Biochemistry, University of California, Irvine, California.

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|April 29, 2014
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This study introduces an efficient algorithm for calculating solvent excluded surface (SES) and solvent accessible surface (SAS) areas, crucial for biomolecular simulations using Poisson-Boltzmann methods. The new physics-inspired approach offers high accuracy and broad applicability to biomolecules.

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Area of Science:

  • Computational chemistry
  • Biophysics
  • Molecular modeling

Background:

  • Implicit solvation models rely on defining molecular surfaces like solvent accessible surface (SAS) and solvent excluded surface (SES).
  • Accurate calculation of these surfaces is vital for biomolecular simulations using Poisson-Boltzmann methods.

Purpose of the Study:

  • To develop an efficient numerical algorithm for computing SES and SAS areas.
  • To integrate this algorithm with finite-difference Poisson-Boltzmann methods for enhanced biomolecular simulations.

Main Methods:

  • A novel, physics-inspired numerical algorithm for SES and SAS area computation.
  • Coupling the algorithm with existing finite-difference Poisson-Boltzmann data structures.
  • Validation against analytical methods and systematic correction analysis for coarse-grid calculations.

Main Results:

  • The algorithm demonstrates high accuracy, with average unsigned relative errors of 0.27% for SES and 1.05% for SAS at 1/2Å grid spacing.
  • Systematic corrections further reduce SES area errors to 0.13% on coarse grids.
  • The method is validated across 1,555 molecules of varying sizes and structures.

Conclusions:

  • The proposed algorithm efficiently and accurately computes SES and SAS areas for biomolecular simulations.
  • It is adaptable for evaluating surface integrals for solvation energetics and force calculations.
  • The method facilitates broader applications of Poisson-Boltzmann methods in studying biomolecules.