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irGPU.proton.Net : Irregular strong charge interaction networks of protonatable groups in protein molecules—a GPU solver using the fast multipole method and statistical thermodynamics
Author(s) -
Kantardjiev Alexander A.
Publication year - 2015
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.23842
Subject(s) - solver , multipole expansion , statistical mechanics , computer science , statistical physics , chemistry , computational science , computational chemistry , physics , quantum mechanics , programming language
Motivation: A cluster of strongly interacting ionization groups in protein molecules with irregular ionization behavior is suggestive for specific structure–function relationship. However, their computational treatment is unconventional (e.g., lack of convergence in naive self‐consistent iterative algorithm). The stringent evaluation requires evaluation of Boltzmann averaged statistical mechanics sums and electrostatic energy estimation for each microstate. Summary: irGPU: Irregular strong interactions in proteins—a GPU solver is novel solution to a versatile problem in protein biophysics—atypical protonation behavior of coupled groups. The computational severity of the problem is alleviated by parallelization (via GPU kernels) which is applied for the electrostatic interaction evaluation (including explicit electrostatics via the fast multipole method) as well as statistical mechanics sums (partition function) estimation. Special attention is given to the ease of the service and encapsulation of theoretical details without sacrificing rigor of computational procedures. irGPU is not just a solution‐in‐principle but a promising practical application with potential to entice community into deeper understanding of principles governing biomolecule mechanisms. © 2015 Wiley Periodicals, Inc.