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A grid-based algorithm in conjunction with a gaussian-based model of atoms for describing molecular geometry.
Chakravorty, Arghya; Gallicchio, Emilio; Alexov, Emil.
Affiliation
  • Chakravorty A; Department of Physics and Astronomy, Clemson University, Clemson, South Carolina 29634.
  • Gallicchio E; Department of Chemistry, CUNY Brooklyn College, Brooklyn, New York.
  • Alexov E; Department of Physics and Astronomy, Clemson University, Clemson, South Carolina 29634.
J Comput Chem ; 40(12): 1290-1304, 2019 May 05.
Article in En | MEDLINE | ID: mdl-30698861
ABSTRACT
A novel grid-based method is presented, which in conjunction with a smooth Gaussian-based model of atoms, is used to compute molecular volume (MV) and surface area (MSA). The MV and MSA are essential for computing nonpolar component of free energies. The objective of our grid-based approach is to identify solute atom pairs that share overlapping volumes in space. Once completed, this information is used to construct a rooted tree using depth-first method to yield the final volume and SA by using the formulations of the Gaussian model described by Grant and Pickup (J. Phys Chem, 1995, 99, 3503). The method is designed to function uninterruptedly with the grid-based finite-difference method implemented in Delphi, a popular and open-source package used for solving the Poisson-Boltzmann equation (PBE). We demonstrate the time efficacy of the method while also validating its performance in terms of the effect of grid-resolution, positioning of the solute within the grid-map and accuracy in identification of overlapping atom pairs. We also explore and discuss different aspects of the Gaussian model with key emphasis on its physical meaningfulness. This development and its future release with the Delphi package are intended to provide a physically meaningful, fast, robust and comprehensive tool for MM/PBSA based free energy calculations. © 2019 Wiley Periodicals, Inc.
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Full text: 1 Database: MEDLINE Type of study: Prognostic_studies Language: En Year: 2019 Type: Article

Full text: 1 Database: MEDLINE Type of study: Prognostic_studies Language: En Year: 2019 Type: Article