Structural-based virtual screening and identification of novel potent antimicrobial compounds against YsxC of Staphylococcus aureus

Design, Molecular Modeling, MD Simulations, Essential Dynamics, ADMET, DFT, Synthesis, Anti-proliferative, and Apoptotic Evaluations of a New Anti-VEGFR-2 Nicotinamide Analogue

OBJECTIVES

This study aims to design and evaluate (in silico and in vitro) a new nicotinamide derivative as an inhibitor of VEGFR-2, a major mediator of angiogenesis Methods: The following in silico studies were performed; DFT calculations, molecular modelling, MD simulations, MM-GBSA, PLIP, and PCAT studies. The compound's in silico (ADMET) analysis was also conducted. Subsequently, the compound ((E)-N-(4-(1-(2-(4-(4-Chlorobenzamido)benzoyl)hydrazono)ethyl) phenyl)nicotinamide) was successfully synthesized and designated as compound X. In vitro, VEGFR-2 inhibition and cytotoxicity of compound X against HCT-116 and A549 cancer cell lines and normal Vero cell lines were conducted. Apoptosis induction and migration assay of HCT-116 cell lines after treatment with compound X were also evaluated.

RESULTS

DFT calculations assigned stability and reactivity of compound X. Molecular docking and MD simulations indicated its excellent binding against VEGFR-2. Furthermore, MM-GBSA analysis, PLIP experiments, and PCAT studies confirmed compound X's correct binding with optimal dynamics and energy. ADMET analysis expressed its general likeness and safety. The in vitro assays demonstrated that compound X effectively inhibited VEGFR-2, with an IC50 value of 0.319 ± 0.013 μM and displayed cytotoxicity against HCT-116 and A549 cancer cell lines, with IC50 values of 57.93 and 78.82 μM, respectively. Importantly, compound X exhibited minimal toxicity towards the non-cancerous Vero cell lines, (IC50 = 164.12 μM). Additionally, compound X significantly induced apoptosis of HCT-116 cell lines and inhibited their potential to migrate and heal.

CONCLUSION

In summary, the presented study has identified compound X as a promising candidate for the development of a novel apoptotic lead anticancer drug.

Molecular modeling, simulation and docking of Rv1250 protein from Mycobacterium tuberculosis

Computational prediction and protein structure modeling have come to the aid of various biological problems in determining the structure of proteins. These technologies have revolutionized the biological world of research, allowing scientists and researchers to gain insights into their biological questions and design experimental research much more efficiently. Pathogenic Mycobacterium spp. is known to stay alive within the macrophages of its host. Mycobacterium tuberculosis is an acid-fast bacterium that is the most common cause of tuberculosis and is considered to be the main cause of resistance of tuberculosis as a leading health issue. The genome of Mycobacterium tuberculosis contains more than 4,000 genes, of which the majority are of unknown function. An attempt has been made to computationally model and dock one of its proteins, Rv1250 (MTV006.22), which is considered as an apparent drug-transporter, integral membrane protein, and member of major facilitator superfamily (MFS). The most widely used techniques, i.e., homology modeling, molecular docking, and molecular dynamics (MD) simulation in the field of structural bioinformatics, have been used in the present work to study the behavior of Rv1250 protein from M. tuberculosis. The structure of unknown TB protein, i.e., Rv1250 was retrived using homology modeling with the help of I-TASSER server. Further, one of the sites responsible for infection was identified and docking was done by using the specific Isoniazid ligand which is an inhibitor of this protein. Finally, the stability of protein model and analysis of stable and static interaction between protein and ligand molecular dynamic simulation was performed at 100 ns The designing of novel Rv1250 enzyme inhibitors is likely achievable with the use of proposed predicted model, which could be helpful in preventing the pathogenesis caused by M. tuberculosis. Finally, the MD simulation was done to evaluate the stability of the ligand for the specific protein.

Promising antivirals for PLpro of SARS-CoV-2 using virtual screening, molecular docking, dynamics, and MMPBSA

The recent pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19) is a viral respiratory disease that has been spread all over the globe. Therefore, it is an urgent requirement to identify and develop drugs for this contagious infection. The papain-like protease (PLpro) of SARS-CoV-2 performs critical functions in virus replication and immune evasion, making it an enticing therapeutic target. SARS-CoV-2 and SARS-CoV PLpro proteases have significant similarities, and an inhibitor discovered for SARS-CoV PLpro is an exciting first step toward therapeutic development. Here, a set of antiviral molecules were screened at the catalytic and S-binding allosteric sites of papain-like protease (PLpro). Molecular docking results suggested that five molecules (44560613, 136277567, S5652, SC75741, and S3833) had good binding affinities at both sites of PLpro. Molecular dynamics analysis like root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), and hydrogen bond results showed that identified molecules with PLpro tend to form stable PLpro-inhibitor(s) complexes. Molecular Mechanics/Position-Boltzmann Surface Area (MMPBSA) analysis confirmed that antiviral molecules bound PLpro complex had lower energy (-184.72 ± 7.81 to -215.67 ± 6.73 kJ/mol) complexes. Noticeably, computational approaches revealed promising antivirals candidates for PLpro, which may be further tested by biochemical and cell-based assays to assess their potential for SARS-CoV-2.Communicated by Ramaswamy H. Sarma.