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Simulating chalcogen bonding using molecular mechanics: a pseudoatom approach to model ebselen.
Fellowes, Thomas; White, Jonathan M.
Afiliação
  • Fellowes T; Bio21 Institute and School of Chemistry, University of Melbourne, Parkville, Australia. fellowes@student.unimelb.edu.au.
  • White JM; Bio21 Institute and School of Chemistry, University of Melbourne, Parkville, Australia.
J Mol Model ; 28(3): 66, 2022 Feb 24.
Article em En | MEDLINE | ID: mdl-35201444
ABSTRACT
The organoselenium compound ebselen has recently been investigated as a treatment for COVID-19; however, efforts to model ebselen in silico have been hampered by the lack of an efficient and accurate method to assess its binding to biological macromolecules. We present here a Generalized Amber Force Field modification which incorporates classical parameters for the selenium atom in ebselen, as well as a positively charged pseudoatom to simulate the σ-hole, a quantum mechanical phenomenon that dominates the chemistry of ebselen. Our approach is justified using an energy decomposition analysis of a number of density functional theory-optimized structures, which shows that the σ-hole interaction is primarily electrostatic in origin. Finally, our model is verified by conducting molecular dynamics simulations on a number of simple complexes, as well as the clinically relevant enzyme SOD1 (superoxide dismutase), which is known to bind to ebselen. Graphical Abstract Ebselen is an organoselenium drug that has shown promise for the treatment of a number of conditions. Computational modelling of drug-target complexes is commonly performed to determine the likely mechanism of action, however this is difficult in the case of ebselen, as an important mode of interaction is not simulated using current techniques. We present here an extension to common methods, which accurately captures this interaction.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article