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Targeting Protein Pockets with Halogen Bonds: The Role of the Halogen Environment.

María Lucrecia BogadoRoxana Noelia VillafañeJosé Leonardo Gómez ChavezEmilio Luis AngelinaGladis Laura SosaNélida María Peruchena
Published in: Journal of chemical information and modeling (2022)
Protein pockets that form a halogen bond (X-bond) with a halogenated ligand molecule simultaneously form other (mainly hydrophobic) interactions with the halogen atom that can be considered as its "X-bond environment" (XBenv). Most studies in the field have focused on the X-bond, with the properties of the XBenv usually overlooked. In this work, we derived a protocol that evaluates the XBenv strength as a measure of the propensity of a protein pocket to host an X-bond. The charge density-based topological descriptors in combination with machine learning tools were employed to predict formation and strength of the interactions that conform the XBenv as a function of their geometrical parameters. On the basis of these results, we propose that the XBenv can be used as a footprint to judge the chance of a protein pocket to form an X-bond.
Keyphrases
  • machine learning
  • protein protein
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  • amino acid
  • binding protein
  • molecular dynamics
  • deep learning
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