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BION-2: Predicting Positions of Non-Specifically Bound Ions on Protein Surface by a Gaussian-Based Treatment of Electrostatics.
Shashikala, H B Mihiri; Chakravorty, Arghya; Panday, Shailesh Kumar; Alexov, Emil.
Afiliación
  • Shashikala HBM; Department of Physics, Clemson University, Clemson, SC 29634, USA.
  • Chakravorty A; Department of Physics, Clemson University, Clemson, SC 29634, USA.
  • Panday SK; Department of Chemistry, University of Michigan, Ann Arbor, MI 48109, USA.
  • Alexov E; Department of Physics, Clemson University, Clemson, SC 29634, USA.
Int J Mol Sci ; 22(1)2020 Dec 29.
Article en En | MEDLINE | ID: mdl-33383946
Ions play significant roles in biological processes-they may specifically bind to a protein site or bind non-specifically on its surface. Although the role of specifically bound ions ranges from actively providing structural compactness via coordination of charge-charge interactions to numerous enzymatic activities, non-specifically surface-bound ions are also crucial to maintaining a protein's stability, responding to pH and ion concentration changes, and contributing to other biological processes. However, the experimental determination of the positions of non-specifically bound ions is not trivial, since they may have a low residential time and experience significant thermal fluctuation of their positions. Here, we report a new release of a computational method, the BION-2 method, that predicts the positions of non-specifically surface-bound ions. The BION-2 utilizes the Gaussian-based treatment of ions within the framework of the modified Poisson-Boltzmann equation, which does not require a sharp boundary between the protein and water phase. Thus, the predictions are done by the balance of the energy of interaction between the protein charges and the corresponding ions and the de-solvation penalty of the ions as they approach the protein. The BION-2 is tested against experimentally determined ion's positions and it is demonstrated that it outperforms the old BION and other available tools.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Proteínas / Fenómenos Biofísicos / Electricidad Estática / Iones / Modelos Teóricos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Int J Mol Sci Año: 2020 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Proteínas / Fenómenos Biofísicos / Electricidad Estática / Iones / Modelos Teóricos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Int J Mol Sci Año: 2020 Tipo del documento: Article