Structure Based Drug Designing of Histone Deacetylase-2 inhibitors as an Anticancer Agents

Background and purpose- Histone deacetylase 2 (HDAC2) in tumour development and carcinogenesis as a promising therapeutic target for cancer treatment. HDAC-2 belongs to class I histone deacetylase and acts as a transcriptional repressor through the deacetylation of lysine residues present at the N-terminal tail of histone proteins (H2A, H2B, H3 and H4). They are overexpressed in various solid tumours like cutaneous t cell lymphoma, colorectal, prostate cancer, lung cancer, breast cancer, gastric cancer, liver cancer and medulloblastoma. Hence, targeting HDAC-2 could be rewarding strategy to combat cancer. The goal of the research is to design, develop and identification of molecules through docking, Ligplot, ADMET properties and dynamic studies. Objective- To update HDAC-2 databases as a resource for Structure based drug designing. Validation of model by understanding the interaction pattern with known inhibitors. To identify selective and trapping HDAC-2 inhibitors by targeting the catalytic domain through structure-based pharmacophore study. To design novel HDAC inhibitors (HDACi) analogues for further generation of new compounds through software. Molecular dynamics simulations for most active compound.Methods- In the present study HDAC-2 protein (PDB-4LY1) from RCSB PDB screened and retrieved. The different set of data for ligand preparation were downloaded from CHEMBL, NCI, Anticancer databases and FDA approved drugs of HDACi were downloaded from PubChem. The compounds were screened with two software Schrodinger and gold. The multiset framework combining ligand preparation, protein preparation, grid generation, ADMET prediction, molecular docking, Ligplot analysis and molecular dynamics (MD) simulation studies was performed to find the potential compound with HDAC-2 binding affinity.Result- The optimised compound shows high docking score from ChEMBL (-14.078) and NCI library it shows (-12.083) as compared to reference drug Panobinostat (-9.157).  binding energy, hydrogen bonding and hydrophobic interaction against the reference compound. 20 compounds were selected as the best HDAC2 inhibitors based on the glide score, binding energy, hydrogen bonding, hydrophobic interaction. Top two compound show Ligplot analysis. Then the one highest docked compound shows dynamic study at 50ns shows binding stability with the inhibitor. Finally find its ADMET property.Conclusion- The virtual screening of drugs through software is ongoing process and 20 modified analogues those which satisfied all the screening results have been found to be better than the conventional drugs available. Further, synthesis, in vivo and cytotoxic studies of synthesised molecules are under process.KEYWORDS- Histone acetylase, histone deacetylase, histone deacetylase-2, molecular dynamics, 4LY1, ADME property, histone deacetylase inhibitor, Optimized Potential for Liquid Simulation 3e, high throughput virtual screening, standard precision, extra precision

Elimination of Endogenous Toxin, Creatinine from Blood Plasma Depends on Albumin Conformation: Site Specific Uremic Toxicity & Impaired Drug Binding

Uremic syndrome results from malfunctioning of various organ systems due to the retention of uremic toxins which, under normal conditions, would be excreted into the urine and/or metabolized by the kidneys. The aim of this study was to elucidate the mechanisms underlying the renal elimination of uremic toxin creatinine that accumulate in chronic renal failure. Quantitative investigation of the plausible correlations was performed by spectroscopy, calorimetry, molecular docking and accessibility of surface area. Alkalinization of normal plasma from pH 7.0 to 9.0 modifies the distribution of toxin in the body and therefore may affect both the accumulation and the rate of toxin elimination. The ligand loading of HSA with uremic toxin predicts several key side chain interactions of site I that presumably have the potential to impact the specificity and impaired drug binding. These findings provide useful information for elucidating the complicated mechanism of toxin disposition in renal disease state

Stereo-Selectivity of Human Serum Albumin to Enantiomeric and Isoelectronic Pollutants Dissected by Spectroscopy, Calorimetry and Bioinformatics

1–naphthol (1N), 2–naphthol (2N) and 8–quinolinol (8H) are general water pollutants. 1N and 2N are the configurational enantiomers and 8H is isoelectronic to 1N and 2N. These pollutants when ingested are transported in the blood by proteins like human serum albumin (HSA). Binding of these pollutants to HSA has been explored to elucidate the specific selectivity of molecular recognition by this multiligand binding protein. The association constants (Kb) of these pollutants to HSA were moderate (104–105 M−1). The proximity of the ligands to HSA is also revealed by their average binding distance, r, which is estimated to be in the range of 4.39–5.37 nm. The binding free energy (ΔG) in each case remains effectively the same for each site because of enthalpy–entropy compensation (EEC). The difference observed between ΔCpexp and ΔCpcalc are suggested to be caused by binding–induced flexibility changes in the HSA. Efforts are also made to elaborate the differences observed in binding isotherms obtained through multiple approaches of calorimetry, spectroscopy and bioinformatics. We suggest that difference in dissociation constants of pollutants by calorimetry, spectroscopic and computational approaches could correspond to occurrence of different set of populations of pollutants having different molecular characteristics in ground state and excited state. Furthermore, our observation of enhanced binding of pollutants (2N and 8H) in the presence of hemin signifies that ligands like hemin may enhance the storage period of these pollutants in blood that may even facilitate the ill effects of these pollutants

Development of a deep learning-based quantitative structure–activity relationship model to identify potential inhibitors against the 3C-like protease of SARS-CoV-2 - Supplementary material

   Hydrogen bond interaction Plot    6lu7-NPACT106-complex at 0ns    6lu7-NPACT106-complex at 25ns    6lu7-NPACT106-complex at 50ns  6lu7-NPACT106-complex at 75ns     6lu7-NSC5159-complex at 0ns    6lu7-NSC5159-complex at 25ns    6lu7-NSC5159-complex at 50ns    6lu7-NSC5159-complex at 75ns    6lu7-NSC5159-complex at 100ns    6lu7-Db8995-complex at 0ns    6lu7-Db8995-complex at 25ns    6lu7-Db8995-complex at 50ns    6lu7-Db8995-complex at 75ns    6lu7-Db8995-complex at 100ns </p

Structure-based drug designing of histone deacetylase-2 inhibitors as anticancer agents

976-988Histone deacetylase 2 (HDAC-2) in tumor development and carcinogenesis is a promising therapeutic target for cancer treatment. HDAC-2 belongs to class I histone deacetylase and acts as a transcriptional repressor through the deacetylation of lysine residues present at the N-terminal tail of histone proteins (H2A, H2B, H3, and H4). They are overexpressed in various solid tumors like cutaneous T cell lymphoma, colorectal cancer, prostate cancer, lung cancer, breast cancer, gastric cancer, liver cancer, and medulloblastoma. Hence, targeting HDAC-2 could be a rewarding strategy to combat cancer. The goal of the research is to design, develop, and identify molecules through docking, Ligplot, ADMET properties, and molecular dynamic studies. The compound CHEMBL4087539 has been observed to be a top scoring inhibitor against HDAC-2. The molecular dynamics simulation shows the convergence of ligand protein interaction. In the 100 ns, the ligand strongly interacts with HDAC-2. Furthermore, the ADME studies show the suitability of predicted inhibitor as a drug like molecule