scholarly journals VIRTUAL SCREENING AND MOLECULAR DYNAMICS SIMULATION OF COMPOUNDS FROM THE HERBAL DATABASE OF INDONESIA AGAINST HISTONE DEACETYLASE 2

2018 ◽  
Vol 10 (1) ◽  
pp. 235
Author(s):  
Muhammad Teguh Setiawan ◽  
Arry Yanuar

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 withthe best criteria for molecular dynamics simulations were selected: Boesenbergin B, pongachalcone I, 6,8-diprenylgenistein, marmin, and mangostin.The ΔG values obtained were, respectively, −8.28, −9.15, −7.05, −9.07, and −7.15. The active crystal ligand N-(2-aminophenyl) benzamide was used asa positive control, with ΔG value of −10.27. Molecular dynamic’s simulations showed that the activity of HDAC2 inhibitors was known to interact inthe 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 ofanalysis. Simulation analysis of molecular dynamics from hits compound showed that analysis with MMGBSA gave higher free energy binding valuethan MMPBSA.

Author(s):  
Ye Yang ◽  
Baichun Hu ◽  
Yi Yang ◽  
Kaihua Gong ◽  
Huibin Wang ◽  
...  

The rational design of selective histone deacetylase 2 (HDAC2) inhibitors is beneficial for the therapeutic treatment of liver cancer, though HDAC2 is highly homologous to HDAC8, which may lead to...


Molecules ◽  
2020 ◽  
Vol 25 (14) ◽  
pp. 3171 ◽  
Author(s):  
Vladimir P. Berishvili ◽  
Alexander N. Kuimov ◽  
Andrew E. Voronkov ◽  
Eugene V. Radchenko ◽  
Pradeep Kumar ◽  
...  

Tankyrase enzymes (TNKS), a core part of the canonical Wnt pathway, are a promising target in the search for potential anti-cancer agents. Although several hundreds of the TNKS inhibitors are currently known, identification of their novel chemotypes attracts considerable interest. In this study, the molecular docking and machine learning-based virtual screening techniques combined with the physico-chemical and ADMET (absorption, distribution, metabolism, excretion, toxicity) profile prediction and molecular dynamics simulations were applied to a subset of the ZINC database containing about 1.7 M commercially available compounds. Out of seven candidate compounds biologically evaluated in vitro for their inhibition of the TNKS2 enzyme using immunochemical assay, two compounds have shown a decent level of inhibitory activity with the IC50 values of less than 10 nM and 10 μM. Relatively simple scores based on molecular docking or MM-PBSA (molecular mechanics, Poisson-Boltzmann, surface area) methods proved unsuitable for predicting the effect of structural modification or for accurate ranking of the compounds based on their binding energies. On the other hand, the molecular dynamics simulations and Free Energy Perturbation (FEP) calculations allowed us to further decipher the structure-activity relationships and retrospectively analyze the docking-based virtual screening performance. This approach can be applied at the subsequent lead optimization stages.


RSC Advances ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 5507-5515
Author(s):  
Liang Song ◽  
Feng-Qi Zhao ◽  
Si-Yu Xu ◽  
Xue-Hai Ju

The bimolecular and fused ring compounds are found in the high-temperature pyrolysis of NONA using ReaxFF molecular dynamics simulations.


2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.


2017 ◽  
Vol 890 ◽  
pp. 252-259
Author(s):  
Le Wang ◽  
Guan Cheng Jiang ◽  
Xin Lin ◽  
Xian Min Zhang ◽  
Qi Hui Jiang

Molecular dynamics simulations are used to study the dissociation inhibiting mechanism of lecithin for structure I hydrates. Adsorption characteristics of lecithin and PVP (poly (N-vinylpyrrolidine)) on the hydrate surfaces were performed in the NVT ensemble at temperatures of 277K and the hydrate dissociation process were simulated in the NPT ensemble at same temperature. The results show that hydrate surfaces with lecithin is more stable than the ones with PVP for the lower potential energy. The conformation of lecithin changes constantly after the balanced state is reached while the PVP molecular dose not. Lecithin molecule has interaction with lecithin nearby and hydrocarbon-chains of lecithin molecules will form a network to prevent the diffusion of water and methane molecules, which will narrow the available space for hydrate methane and water movement. Compared with PVP-hydrate simulation, analysis results (snapshots and mass density profile) of the dissociation simulations show that lecithin-hydrate dissociates more slowly.


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