Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach.

Worldwide coronavirus disease 2019 (COVID-19) outbreak is still threatening global health since its outbreak first reported in the late 2019. The causative novel virus has been designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although COVID-19 emergent with significant mortality, there is no availability of definite treatment measures. It is now extremely desirable to identify potential chemical entities against SARS-CoV-2 for the treatment of COVID-19. In the present study, a state-of-art virtual screening protocol was implemented on three anti-viral specific chemical libraries against SARS-CoV-2 main protease (Mpro). Particularly, viewing the large-scale biological role of Mpro in the viral replication process it has been considered as a prospective anti-viral drug target. Herein, on collected 79,892 compounds, hierarchical multistep docking followed by relative binding free energy estimation has been performed. Thereafter, implying a user-defined XP-dock and MM-GBSA cut-off scores as -8.00 and -45.00 kcal/mol, chemical space has been further reduced. Exhaustive molecular binding interactions analyses and various pharmacokinetics profiles assessment suggested four compounds (ChemDiv_D658-0159, ChemDiv_F431-0433, Enamine_Z3019991843 and Asinex_LAS_51389260) as potent inhibitors/modulators of SARS-CoV-2 Mpro. In-depth protein-ligand interactions stability in the dynamic state has been evaluated by 100 ns molecular dynamics (MD) simulation studies along with MM-GBSA-based binding free energy estimations of entire simulation trajectories that have revealed strong binding affinity of all identified compounds towards Mpro. Hence, all four identified compounds might be considered as promising candidates for future drug development specifically targeting the SARS-CoV-2 Mpro; however, they also need experimental assessment for a better understanding of molecular interaction mechanisms.

Pharmacoinformatics approach based identification of potential Nsp15 endoribonuclease modulators for SARS-CoV-2 inhibition.

In the current study, a structure-based virtual screening paradigm was used to screen a small molecular database against the Non-structural protein 15 (Nsp15) endoribonuclease of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 is the causative agent of the recent outbreak of coronavirus disease 2019 (COVID-19) which left the entire world locked down inside the home. A multi-step molecular docking study was performed against antiviral specific compounds (~8722) collected from the Asinex antiviral database. The less or non-interacting molecules were wiped out sequentially in the molecular docking. Further, MM-GBSA based binding free energy was estimated for 26 compounds which shows a high affinity towards the Nsp15. The drug-likeness and pharmacokinetic parameters of all 26 compounds were explored, and five molecules were found to have an acceptable pharmacokinetic profile. Overall, the Glide-XP docking score and Prime-MM-GBSA binding free energy of the selected molecules were explained strong interaction potentiality towards the Nsp15 endoribonuclease. The dynamic behavior of each molecule with Nsp15 was assessed using conventional molecular dynamics (MD) simulation. The MD simulation information was strongly favors the Nsp15 and each identified ligand stability in dynamic condition. Finally, from the MD simulation trajectories, the binding free energy was estimated using the MM-PBSA method. Hence, the proposed final five molecules might be considered as potential Nsp15 modulators for SARS-CoV-2 inhibition.

Structure-Based Screening of DNA GyraseB Inhibitors for Therapeutic Applications in Tuberculosis: a Pharmacoinformatics Study.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB) and considered as serious public health concern worldwide which kills approximately five thousand people every day. Therefore, TB drug development efforts are in gigantic need for identification of new potential chemical agents to eradicate TB from the society. The bacterial DNA gyrase B (GyrB) protein as an experimentally widely accepted effective drug target for the development of TB chemotherapeutics. In the present study, advanced pharmacoinformatics approaches were used to screen the Mcule database against the GyrB protein. Based on a number of chemometric parameters, five molecules were found to be crucial to inhibit the GyrB. A number of molecular binding interactions between the proposed inhibitors and important active site residues of GyrB were observed. The predicted drug-likeness properties of all molecules were indicated that compounds possess characteristics to be the drug-like candidates. The dynamic nature of each molecule was explored through the molecular dynamics (MD) simulation study. Various analyzing parameters from MD simulation trajectory have suggested rationality of the molecules to be potential GyrB inhibitor. Moreover, the binding free energy was calculated from the entire MD simulation trajectories highlighted greater binding free energy values for all newly identified compounds also substantiated the strong binding affection towards the GyrB in comparison to the novobiocin. Therefore, the proposed molecules might be considered as potential anti-TB chemical agents for future drug discovery purposes subjected to experimental validation. Graphical Abstract.