Literature DB >> 32504755

Identification of novel class I and class IIb histone deacetylase inhibitor for Alzheimer's disease therapeutics.

Rohan Gupta1, Rashmi K Ambasta1, Pravir Kumar2.   

Abstract

Histone deacetylase enzymes were prominent chromatin remodeling drug that targets in the pathophysiology of Alzheimer's disease associated with transcriptional dysregulation. In vitro and in vivo models of AD have demonstrated overexpression of HDAC activity. Non-specificity and non-selectivity of HDAC are the major problems of existing HDAC inhibitors. Hence, we aim to set up a methodology describing the rational development of isoform-selective HDAC inhibitor targeting class, I and class IIb. A convenient multistage virtual screening followed by machine learning and IC50 screenings were used to classify the 5064 compounds into inhibitors and non-inhibitors classes retrieved from the ChEMBL database. ADMET analysis identified the pharmacokinetics and pharmacodynamics properties of selected compounds. Molecular docking, along with mutational analysis of eleven compounds, characterized the inhibiting potency. Herein, for the first time, we reported ChEMBL1834473 (2-[[5-(4-chlorophenyl)-1,3,4-thiadiazol-2-yl]amino]-N-hydroxypyrimidine-5-carboxamide) as the isoform-selective HDAC inhibitor, which interact central Zn2+ atom. The negative energy and interacting residue of the ChEMBL1834473 with six HDAC isoform has also been tabulated and mapped. Moreover, our findings concluded histidine, glycine, phenylalanine, and aspartic acid as key residues in protein-ligand interaction and classify 2347 compounds as HDAC inhibitors. Later, a protein-protein interaction network of six HDAC with the key proteins involved in the progression of an AD and signaling pathway, which describes the relationship between ChEMBL1834473 and AD, has been demonstrated using PPI network where the chosen inhibitor will work. Altogether, we conclude that the compound ChEMBL1834473 may be capable of inhibiting all isoforms of class I and class IIb HDAC based on computational analysis for AD therapeutics.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alzheimer's disease; ChEMBL database; HDAC inhibitor; Histone deacetylase; IC(50) value; Machine learning; Neurodegenerative disease; Virtual screening

Year:  2020        PMID: 32504755     DOI: 10.1016/j.lfs.2020.117912

Source DB:  PubMed          Journal:  Life Sci        ISSN: 0024-3205            Impact factor:   5.037


  3 in total

Review 1.  Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system.

Authors:  Vertika Gautam; Anand Gaurav; Neeraj Masand; Vannajan Sanghiran Lee; Vaishali M Patil
Journal:  Mol Divers       Date:  2022-07-11       Impact factor: 3.364

Review 2.  The role of histone modifications: from neurodevelopment to neurodiseases.

Authors:  Jisu Park; Kyubin Lee; Kyunghwan Kim; Sun-Ju Yi
Journal:  Signal Transduct Target Ther       Date:  2022-07-06

3.  Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.

Authors:  Kushagra Kashyap; Mohammad Imran Siddiqi
Journal:  Mol Divers       Date:  2021-07-19       Impact factor: 3.364

  3 in total

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