VIRTUAL SCREENING AND MOLECULAR DYNAMICS SIMULATION OF COMPOUNDS FROM THE HERBAL DATABASE OF INDONESIA AGAINST HISTONE DEACETYLASE 2
Objective: This study aimed to find the herbal compounds from the database of Indonesian herbs with potential for use as histone deacetylase 2 (HDAC2)
enzyme inhibitors through virtual screening using the LigandScout program.
Methods: Virtual screening was conducted using LigandScout 4.09.3, AutodockZN, and AutoDockTools.
Results: The virtual screening process resulted in 10 compounds with the highest pharmacophore fit score rating, from which five compounds with
the best criteria for molecular dynamics simulations were selected: Boesenbergin B, pongachalcone I, 6,8-diprenylgenistein, marmin, and mangostin.
The Î”G values obtained were, respectively, âˆ’8.28, âˆ’9.15, âˆ’7.05, âˆ’9.07, and âˆ’7.15. The active crystal ligand N-(2-aminophenyl) benzamide was used as
a positive control, with Î”G value of âˆ’10.27. Molecular dynamic's simulations showed that the activity of HDAC2 inhibitors was known to interact in
the amino acid residues His145C, Tyr308C, Zn379C, Leu276C, Phe155C, Phe210C, Leu144C, and Met35C.
Conclusions: Based on virtual screening and the molecular dynamics simulations, marmin was considered to provide the best overall activity of
analysis. Simulation analysis of molecular dynamics from hits compound showed that analysis with MMGBSA gave higher free energy binding value
2. Phamte H, Lethithu H. Integrating structure and ligand-base approaches
for modelling the histone deacetylase inhibition activity of hydroxamic
acid derivatives. Asian J Pharm Clin Res 2018;11:198-206.
3. Christensen DP, DahllÃ¶f M, Lundh M, Rasmussen DN, Nielsen MD,
Billestrup N, et al. Histone deacetylase (HDAC) inhibition as a novel
treatment for diabetes mellitus. Mol Med 2011;17:378-90.
4. Patil SV, Mandare AP, Pandurang GB. Study of total cholesterol (TC),
tryacylglycerols (TG), high density lipoprotein cholesterol (HDL-C) in
Type II diabetes mellitus. Asian J Pharm Clin Res 2017;10:116-8.
5. Ministry of Health, Republic of Indonesia. Situation and Diabetes
Analysis. Jakarta: Data Center and Information, Ministry of Health,
Republic of Indonesia; 2014.
6. Al-Haddad R, Karnib N, Assaad RA, Bilen Y, Emmanuel N, Ghanem A,
et al. Epigenetic changes in diabetes. Neurosci Lett 2016;625:64-9.
7. Tanisa AA, Riadhi R, Yanuar A. Virtual screening of beta-secretase 1 (BASE1)
inhibitors in the Indonesian herbal database as using autodock and autodock
VNA. Asian J Pharm Clin Res 2017;10:148-52.
8. Fogolari F, Brigo A, Molinari H. Protocol for MM/PBSA molecular
dynamics simulations of proteins. Biophys J 2003;85:159-66.
9. Wolber G, Langer T. LigandScout: 3-D pharmacophores derived from
protein-bound ligands and their use as virtual screening filters. J Chem
Inf Model 2005;45:160-9.
10. KÃ¤stner J, Loeffler HH, Roberts SK, Martin-Fernandez ML, Winn MD.
Ectodomain orientation, conformational plasticity and oligomerization
of erbB1 receptors investigated by molecular dynamics. J Struct Biol
11. Desheng L, Jian G, Yuanhua C, Wei C, Huai Z, Mingjuan J,
et al. Molecular dynamics simulations and MM/GBSA methods to
investigate binding mechanisms of aminomethylpyrimidine inhibitors
with DPP-IV. Bioorg Med Chem Lett 2011;21:6630-5.