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Dengue infection is the most common arthropod‐borne disease caused by dengue viruses, predominantly affecting millions of human beings annually. To find out promising chemical entities for therapeutic application in Dengue, in the current research, a multi‐step virtual screening effort was conceived to screen out the entire "screening library" of the Asinex database. Initially, through "Lipinski rule of five" filtration criterion almost 0.6 million compounds were collected and docked with NS3‐NS2B protein. Thereby, the chemical space was reduced to about 3500 compounds through the analysis of binding affinity obtained from molecular docking study in AutoDock Vina. Further, the "Virtual Screening Workflow" (VSW) utility of Schrödinger suite was used, which follows a stepwise multiple docking programs such as ‐ high‐throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking, and in postprocessing analysis the MM‐GBSA based free binding energy calculation. Finally, five potent molecules were proposed as potential inhibitors for the dengue NS3‐NS2B protein based on the investigation of molecular interactions map and protein‐ligand fingerprint analyses. Different pharmacokinetics and drug‐likeness parameters were also checked, which favour the potentiality of selected molecules for being drug‐like candidates. The molecular dynamics (MD) simulation analyses of protein‐ligand complexes were explained that NS3‐NS2B bound with proposed molecules quite stable in dynamic states as observed from the root means square deviation (RMSD) and root means square fluctuation (RMSF) parameters. The binding free energy was calculated using MM‐GBSA method from the MD simulation trajectories revealed that all proposed molecules possess such a strong binding affinity towards the dengue NS3‐NS2B protein. Therefore, proposed molecules may be potential chemical components for effective inhibition of dengue NS3‐NS2B protein subjected to experimental validation. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation. [ABSTRACT FROM AUTHOR]

Histone deacetylase 8 (HDAC8) has emerged as a promising drug target for cancer therapeutics development. HDAC8 has been reported to regulate cancer cell proliferation, invasion and promote metastasis through modulation of cell cycle associated proteins. Of late, phytocompounds have been demonstrated to exhibit anticancer and anti-HDAC8 activity. Here, we have shown the HDAC8 inhibitory potential of an active phytocompound from HC9 (herbal composition-9), a polyherbal anticancer formulation based on the traditional Ayurvedic drug, Stanya Shodhan Kashaya. HC9 was recently reported to exhibit anticancer activity against breast cancer cells through induction of cell cycle arrest, decrease in migration and invasion as well as regulation of inflammation and chromatin modulators. In silico studies such as molecular docking, molecular dynamics (MD) simulation and binding free energy analyses showed greater binding energy values and interaction stability of MA with HDAC8 compared to other phytocompounds of HC9. Interestingly, in vitro validation confirmed the anti-HDAC8 activity of MA. Further, in vitro studies showed that MA significantly decreased the viability of breast and prostate cancer cell lines, thereby confirming its anticancer potential. [Display omitted] • HDAC8 inhibitory activity of phytocompounds from HC9 are identified. • The study has unfolded therapeutic significance of Matairesinol against HDAC8 and its anticancer activity against breast and prostate cancer cells. • Docking study revealed a number of crucial bonds between phytocompounds and HDAC8. • MD simulation has explained the stability of phytochemicals-HDAC8 complexes. • MM-GBSA-binding free energy suggested strong affinity of phytochemicals towards HDAC8. [ABSTRACT FROM AUTHOR]

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. Image 1 • Nsp15 of SARS-CoV-2 considers as an important therapeutic target for COVID-19. • Entire Asinex antiviral database screened through multistep molecular docking. • MD simulations reveal stable interactions with putative modulators (N1–N5). • Binding free energy values suggested strong binding affinity towards Nsp15. • ADMET analyses shown accepted drug-like profile for all modulators of Nsp15. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a neurodegenerative disorder generally developed with aging. AD slowly hammers the memory and cognitive abilities which eventually leads to abnormal behaviour, and ultimately left with disability and dependency. It is anticipated that by the year 2050, world population will experience the incidence of 100 million AD cases. It has been more than hundred years passed since AD recognized as a dreadfull disease, but there is no effective curative agent discovered against AD to date. One of the major hallmarks of the AD development is the accumulation of extracellular amyloid-beta (Aβ) plaques in the brain. In the amyloidogenic process, an extensively studied beta-secretase enzyme, known as BACE1, plays a key role in the accumulation and production of Aβ fragments. Therefore, successful inhibition of BACE1 by small molecular chemical entities can be an effective approach for anti-AD drug development. Hence, the current study has been perceived to find out potential BACE1 inhibitiors by virtual screening of entire Asinex chemical library database through multi-step molecular docking methodologies. Further, sequential screening of in-silico pharmacokinetics, molecular dynamic (MD) simulations analyses along with binding free energy estimation were performed. Comparative analyses and characteristics of molecular binding interactions assessment finally suggests that five molecules (B1–B5) to be the most promising BACE1 inhibitors. Molecular interactions analyses revealed that either one or both the catalytic dyad residues (Asp32 and Asp228) of BACE1 has formed strong molecular interactions with all the proposed molecules. Not only the catalytic dyad residues are involved in the formation of molecular binding interactions but also other important non-Asp binders residues such as Gly34, Tyr71, Trp115, Arg128, Lys224, Gly230, Thr231, Thr232, Arg235, Thr329, and Val332 found to interact with the selected compounds. Moreover, the dynamic behaviour of proposed molecules and BACE1 was explored through all-atoms MD simulation study for 100 ns time span. Analysis of MD simulation trajectories explained that all identified molecules are efficient enough to retain the structural and molecular interactions integrity inside the receptor cavity of BACE1 in dynamic environment. Finally, the binding free energy of each molecule has calculated from MD simulation trajectories through MM-PBSA method and found that all molecules possess a strong binding affinity towards the BACE1. The high negative binding free energies are found to be within the range of −994.978 to −561.562 kJ/mol for the identified compounds. Henceforth, analyses of extensively studied multi-cheminformatics approaches explained that proposed molecules might be promising BACE1 inhibitors for therapeutic application in AD, subjected to experimental validation. Image 1 • CNS-Asinex database was virtually screened to identify potential BACE1 inhibitors. • Through docking and VSW five potential molecules were identified as BACE1 inhibitors. • Different pharmacokinetics parameters were checked for final proposed molecules. • MD simulation was performed of BACE1 complex with proposed molecules. • The binding energy was calculated using MM-PBSA approach. [ABSTRACT FROM AUTHOR]

• Wild type Catalase-peroxidase enzyme (WT katG) mutated into five mutant katG (MT katG). • Molecular docking was performed WT and MT katG. • Screening was performed based on binding energy of Isoniazid and promising katG inhibitors proposed. • MD simulation was performed for MT katG-proposed molecules complex. • Binding energy of proposed molecules was calculated using MM-PBSA approach. Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb). In the present age, due to the rapid increase in antibiotic resistance worldwide, TB has become a major threat to human life. Regardless of significant efforts have been inclined to improve the healthcare systems for improving diagnosis, treatment, and anticipatory measures controlling TB is challenging. To date, there are no such therapeutic chemical agents available to fight or control the bacterial drug-resistance. The catalase-peroxidase enzyme (katG) which encoded by the katG gene of Mtb is most frequently getting mutated and hence promotes Isoniazid resistance by diminishing the normal activity of katG enzyme. In the current study, an effort has been intended to find novel and therapeutically active antibacterial chemical compounds through pharmacoinformatics methodologies. Initially, the five mutant katG were generated by making mutation of Ser315 by Thr, Ile, Arg, Asn, and Gly followed by structural optimizations. About eight thousand small molecules were collected from the Asinex antibacterial library. All molecules were docked to active site of five mutant katG and wild type katG. To narrow down the chemical space several criteria were imposed including, screening for highest binding affinity towards katG proteins, compounds satisfying various criterion of drug-likeliness properties like Lipinski's rule of five (RO5), Veber's rule, absorption, distribution, metabolism, and excretion (ADME) profile, and synthetic accessibility. Finally, five molecules were found to be important antibacterial katG inhibitors. All the analyzed parameters suggested that selected molecules are promising in nature. Binding interactions analysis revealed that proposed molecules are efficient enough to form a number of strong binding interactions with katG proteins. Dynamic behavior of the proposed molecules with katG protein was evaluated through 100 ns molecular dynamics (MD) simulation study. Parameters calculated from the MD simulation trajectories adjudged that all molecules can form stable complexes with katG. High binding free energy of all proposed molecules definitely suggested strong affection towards the katG. Hence, it can be concluded that proposed molecules might be used as antibacterial chemical component subjected to experimental validation. [ABSTRACT FROM AUTHOR]