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The Histone Deacetylase Family: Structural Features and Application of Combined Computational Methods.
Curcio, Antonio; Rocca, Roberta; Alcaro, Stefano; Artese, Anna.
Afiliação
  • Curcio A; Dipartimento di Scienze della Salute, Campus "S. Venuta", Università degli Studi "Magna Græcia" di Catanzaro, Viale Europa, 88100 Catanzaro, Italy.
  • Rocca R; Dipartimento di Scienze della Salute, Campus "S. Venuta", Università degli Studi "Magna Græcia" di Catanzaro, Viale Europa, 88100 Catanzaro, Italy.
  • Alcaro S; Net4Science S.r.l., Università degli Studi "Magna Græcia" di Catanzaro, Viale Europa, 88100 Catanzaro, Italy.
  • Artese A; Dipartimento di Scienze della Salute, Campus "S. Venuta", Università degli Studi "Magna Græcia" di Catanzaro, Viale Europa, 88100 Catanzaro, Italy.
Pharmaceuticals (Basel) ; 17(5)2024 May 10.
Article em En | MEDLINE | ID: mdl-38794190
ABSTRACT
Histone deacetylases (HDACs) are crucial in gene transcription, removing acetyl groups from histones. They also influence the deacetylation of non-histone proteins, contributing to the regulation of various biological processes. Thus, HDACs play pivotal roles in various diseases, including cancer, neurodegenerative disorders, and inflammatory conditions, highlighting their potential as therapeutic targets. This paper reviews the structure and function of the four classes of human HDACs. While four HDAC inhibitors are currently available for treating hematological malignancies, numerous others are undergoing clinical trials. However, their non-selective toxicity necessitates ongoing research into safer and more efficient class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches, such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure-activity relationships, and structure-based virtual screening (molecular docking). Moreover, recent developments in the field of molecular dynamics simulations, combined with Poisson-Boltzmann/molecular mechanics generalized Born surface area techniques, have improved the prediction of ligand binding affinity. In this review, we delve into the ways in which these methods have contributed to designing and identifying HDAC inhibitors.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article