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Author: search.filters.author.Murugesan, SankaranarayananSubject: search.filters.subject.Molecular dynamics simulation (MDS)

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    Discovery of potent DNMT1 inhibitors against sickle cell disease using structural-based virtual screening, MM-GBSA and molecular dynamics simulation-based approaches
    (Taylor & Francis, 2023-04) Murugesan, Sankaranarayanan
    Sickle cell disease (SCD) is an autosomal recessive genetic disorder affecting millions of people worldwide. A reversible and selective DNMT1 inhibitor, GSK3482364, has been known to decrease the overall methylation activity of DNMT1, resulting in the increase of HbF levels and percentage of HbF-expressing erythrocytes in an in vitro and in vivo model. In this study, a structure-based virtual screening was done with GSK3685032, a co-crystalized ligand of DNMT1 (PDB ID: 6X9K) with an IC50 value of 0.036 μM and identified 3988 compounds from three databases (ChEMBL, PubChem and Drug Bank). Using this screening method, we identified around 15 compounds with XP docking scores greater than −8 kcal/mol. Further, prime MM-GBSA calculations have been performed and found compound SCHEMBL19716714 with the highest binding free energy of −83.31 kcal/mol. Finally, four compounds were identified based on glide energy and ΔG bind scores that have the most binding with DG7, DG19, DG20 bases and Lys1535, His1507, Trp1510, Ser1230, which were required for the target enzyme inhibition. Furthermore, molecular dynamics simulation studies of top ligands validate the stability of the docked complexes by examining root mean square deviations, root mean square fluctuations, solvent accessible surface area, and radius of gyration graphs from simulation trajectories. These findings suggest that the top four hit compounds may be capable of inhibiting DNMT1 and that additional in vitro and in vivo studies will be essential to prove the clinical effectiveness of the selected lead compounds.
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    Pharmacoinformatics-Based Approach for Uncovering the Quorum-Quenching Activity of Phytocompounds against the Oral Pathogen, Streptococcus mutans
    (MDPI, 2023-07) Murugesan, Sankaranarayanan
    Streptococcus mutans, a gram-positive oral pathogen, is the primary causative agent of dental caries. Biofilm formation, a critical characteristic of S. mutans, is regulated by quorum sensing (QS). This study aimed to utilize pharmacoinformatics techniques to screen and identify effective phytochemicals that can target specific proteins involved in the quorum sensing pathway of S. mutans. A computational approach involving homology modeling, model validation, molecular docking, and molecular dynamics (MD) simulation was employed. The 3D structures of the quorum sensing target proteins, namely SecA, SMU1784c, OppC, YidC2, CiaR, SpaR, and LepC, were modeled using SWISS-MODEL and validated using a Ramachandran plot. Metabolites from Azadirachta indica (Neem), Morinda citrifolia (Noni), and Salvadora persica (Miswak) were docked against these proteins using AutoDockTools. MD simulations were conducted to assess stable interactions between the highest-scoring ligands and the target proteins. Additionally, the ADMET properties of the ligands were evaluated using SwissADME and pkCSM tools. The results demonstrated that campesterol, meliantrol, stigmasterol, isofucosterol, and ursolic acid exhibited the strongest binding affinity for CiaR, LepC, OppC, SpaR, and Yidc2, respectively. Furthermore, citrostadienol showed the highest binding affinity for both SMU1784c and SecA. Notably, specific amino acid residues, including ASP86, ARG182, ILE179, GLU143, ASP237, PRO101, and VAL84 from CiaR, LepC, OppC, SecA, SMU1784c, SpaR, and YidC2, respectively, exhibited significant interactions with their respective ligands. While the docking study indicated favorable binding energies, the MD simulations and ADMET studies underscored the substantial binding affinity and stability of the ligands with the target proteins. However, further in vitro studies are necessary to validate the efficacy of these top hits against S. mutans.