Back to Search Start Over

Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach.

Authors :
Zeb A
Park C
Son M
Rampogu S
Alam SI
Park SJ
Lee KW
Source :
Journal of bioinformatics and computational biology [J Bioinform Comput Biol] 2018 Jun; Vol. 16 (3), pp. 1840015.
Publication Year :
2018

Abstract

Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115.63, highest cost difference of 135.00, lowest RMSD of 0.70 and the highest correlation of 0.98. The pharmacophore was validated by Fischer's Randomization and Test Set validation, and used as screening tool for chemical databases. The screened compounds were filtered by fit value ([Formula: see text]), estimated Inhibitory Concentration (IC[Formula: see text]) ([Formula: see text]), Lipinski's Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Descriptors to identify drug-like compounds. Furthermore, the drug-like compounds were docked into the active site of HDAC6. The best docked compounds were selected having goldfitness score [Formula: see text] and [Formula: see text], and hydrogen bond interaction with catalytic active residues. Finally, three inhibitors having sulfamoyl group were selected by Molecular Dynamic (MD) simulation, which showed stable root mean square deviation (RMSD) (1.6-1.9[Formula: see text]Å), lowest potential energy ([Formula: see text][Formula: see text]kJ/mol), and hydrogen bonding with catalytic active residues of HDAC6.

Details

Language :
English
ISSN :
1757-6334
Volume :
16
Issue :
3
Database :
MEDLINE
Journal :
Journal of bioinformatics and computational biology
Publication Type :
Academic Journal
Accession number :
29945500
Full Text :
https://doi.org/10.1142/S0219720018400152