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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

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Order N algorithm for computation of electrostatic interactions in biomolecular systems.

Benzhuo Lu¹, Xiaolin Cheng, Jingfang Huang

¹Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA 92093-0365, USA. blu@mccammon.ucsd.edu

Proceedings of the National Academy of Sciences of the United States of America

|December 7, 2006

Summary

This study introduces an efficient computational method for Poisson-Boltzmann electrostatics, improving the analysis of large biomolecular systems like protein interactions. The new approach offers optimal performance in speed and memory usage.

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Area of Science:

Biophysics
Computational Biology
Electrostatics

Background:

Poisson-Boltzmann electrostatics is crucial for biophysics but faces computational limits for large biomolecular systems.
Existing numerical techniques struggle with efficiency and memory for complex protein-protein interactions.

Purpose of the Study:

To develop an efficient and accurate computational scheme for Poisson-Boltzmann electrostatics.
To overcome the limitations of current numerical methods for large-scale biomolecular simulations.

Main Methods:

Discretization of the linearized Poisson-Boltzmann equation using a boundary integral equation approach.
Acceleration of the solution process with Krylov subspace methods and a fast multipole method.
Interpolation procedures for rapid calculation of electrostatic energy, forces, and torques.

Main Results:

The developed algorithm achieves asymptotically optimal O(N) performance in CPU time and memory.
The scheme is applicable to systems with an arbitrary number of biomolecules.
Demonstrated application to the acetylcholinesterase-fasciculin complex.

Conclusions:

The new computational scheme significantly enhances the ability to model large-scale biomolecular electrostatic interactions.
This advancement facilitates more efficient and accurate studies of protein-protein encounters and other complex biological processes.