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* Department of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University in St. Louis, St. Louis, Missouri;
Institute for Computational Engineering and Sciences, Center for Computational Visualization, The University of Texas at Austin, Austin, Texas;
Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, California;
Department of Computer Sciences and Institute for Computational Engineering and Sciences, Center for Computational Visualization, The University of Texas at Austin, Austin, Texas; and ¶ Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, Department of Pharmacology, Howard Hughes Medical Institute, University of California at San Diego, La Jolla, California
Correspondence: Address reprint requests to Nathan A. Baker, Dept. of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University in St. Louis, 700 S. Euclid Ave., Campus Box 8036, St. Louis, MO 63110. Tel.: 314-362-2040; Fax: 314-362-0234; E-mail: baker{at}biochem.wustl.edu.
This article describes the development and implementation of algorithms to study diffusion in biomolecular systems using continuum mechanics equations. Specifically, finite element methods have been developed to solve the steady-state Smoluchowski equation to calculate ligand binding rate constants for large biomolecules. The resulting software has been validated and applied to mouse acetylcholinesterase. Rates for inhibitor binding to mAChE were calculated at various ionic strengths with several different reaction criteria. The calculated rates were compared with experimental data and show very good agreement when the correct reaction criterion is used. Additionally, these finite element methods require significantly less computational resources than existing particle-based Brownian dynamics methods.
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