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AN EFFICIENT HIGHER-ORDER FAST MULTIPOLE BOUNDARY ELEMENT SOLUTION FOR POISSON-BOLTZMANN BASED MOLECULAR

Chandrajit Bajaj, Shun-Chuan Chen, Alexander Rand

SIAM Journal on Scientific Computing : a Publication of the Society for Industrial and Applied Mathematics

|June 11, 2011

Summary

We present a boundary element method to calculate biomolecular polarization energy. This efficient approach accurately computes polarization for proteins, aiding molecular docking simulations.

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Area of Science:

Computational biology
Biophysics
Theoretical chemistry

Background:

Accurate computation of biomolecular polarization energy is crucial for understanding molecular interactions.
The linearized Poisson-Boltzmann equation is a standard model, but its numerical solution can be challenging.
Existing methods may lack efficiency or require complex approximations of molecular surfaces.

Purpose of the Study:

To develop and validate an efficient boundary element method (BEM) for solving the linearized Poisson-Boltzmann equation.
To accurately compute the polarization energy of biomolecules, particularly proteins.
To provide a robust computational tool for applications in molecular docking and drug design.

Main Methods:

A derivative boundary formulation of the linearized Poisson-Boltzmann equation.
A smooth approximation of the molecular surface using algebraic spline surfaces.
Implementation leveraging state-of-the-art numerical linear algebra and the kernel-independent fast multipole method (FMM).

Main Results:

The developed BEM solver demonstrates high efficiency and simplicity in implementation.
Computational experiments on actual proteins involved in molecular docking show the method's effectiveness.
Accurate calculation of molecular polarization energy was achieved.

Conclusions:

The described boundary element approach offers an effective and efficient solution for computing biomolecular polarization energy.
This method provides a valuable tool for computational studies in biophysics and molecular modeling.
The approach is well-suited for analyzing proteins and facilitating molecular docking predictions.