The design of compounds with desirable properties - The anti-HIV case study.

Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artificial intelligence into the field of computational drug design are accelerating the process of identifying, developing, and optimizing potential drugs. Here, we present novel approach to design new molecules with desired properties. We combined various neural networks and linear regression algorithms to build models for cytotoxicity and anti-HIV activity based on Continual Molecular Interior analysis (CoMIn) and Cinderella's Shoe (CiS) derived molecular descriptors. After validating the reliability of the models, a genetic algorithm was coupled with the Des-Pot Grid algorithm to generate new molecules from a predefined pool of molecular fragments and predict their bioactivity and cytotoxicity. This combination led to the proposal of 16 hit molecules with high anti-HIV activity and low cytotoxicity. The anti-SARS-CoV-2 activity of the hits was predicted.

Cucumis melo var. momordica as a Potent Antidiabetic, Antioxidant and Possible Anticovid Alternative: Investigation through Experimental and Computational Methods.

Diabetes mellitus is a typical life threatening of disease, which generate due to the dysfunction of ß cells of pancreas. In 2014, WHO stated that 422 million people were infected with DM. The current pattern of management of diabetes included synthetic or plant based oral hypoglycemic drugs and insulin but drug resentence is become a very big issues in antidiabetic therapy. Thus, it's very earnest to discover now medication for this disease. Now the days, it is well acknowledged that diabetic patients are more prone towards covid and related complications. Thus, medical practitioners reformed the methodology of prescribing medication for covid infected antidiabetic therapy and encouraging the medication contains dual pharmacological properties. It is also well know that polyphenols specifically hold a significant role in oxidative stress and reduced the severity of many inflammatory diseases. Cucumis melo has rich history as ethano-pharmacological use in Indian subcontinent. The fruit and seed are well-known for the treatment of various diseases due to the presence of phenolics. Therefore, in this study, the combined mixture of flower and seeds were used for the extraction of polyphenolic rich extract and tested for antidiabetic activity through the antioxidant and in vivo experiments. The antioxidant potential measurement exhibited that the selected plant extract has the significant competence to down-regulate oxidative stress (DPPH scavenging IC50 at 60.7±1.05 µg/mL, ABTS IC50 at 62.15±0.50 µg/mL). Furthermore, the major polyphenolic phyto-compounds derived from the Cucumis melo were used for in silico anticovid activity, docking, and complementarity studies. The anticovid activity prognosis reflected that selected phyto-compounds amentoflavone and vanillic acid have optimal possibility to interact with 3C-like protease and through this moderate anticovid activity can be exhibit. The docking experiments established that the selected compounds have propensity to interact with protein tyrosine phosphatase 1B, 11ß-Hydroxysteroid dehydrogenase, superoxide dismutase, glutathione peroxidase, and catalase ß-glucuronidase receptor. In vivo experiments showed that 500 mg/kg, Cucumis melo extract ominously amplified body weight, plasma insulin, high-density lipoprotein levels, and biochemical markers. Furthermore, extract significantly downregulate the blood glucose, total cholesterol, triglycerides, low-density lipoprotein, and very low-density lipoprotein.

Green synthesis of silver nanoformulation of Scindapsus officinalis as potent anticancer and predicted anticovid alternative: Exploration via experimental and computational methods

The current study was focused on the investigation of anticancer activity of Scindapsus Officinalis fruit extract embedded silver nanoparticles (So-AgNPs) followed by anticovid activity prognosis of major phytocompounds, which participate in nanoformulation synthesis. The synthesis process involved the addition of AgNO3 solution (1 mM) and color change of the extract from light brown to dark, confirmed the formation of silver nanoparticles. Further, the characterization of synthesized So-AgNPs were done using different spectroscopical and microscopical techniques. FTIR spectra of So-AgNPs indicated vibrational peaks of polyphenolic hydroxyl groups, which are responsible for the stabilization of nanoformulation. Others microscopy methods such as SEM, TEM, XRD, and EDX illustrated that the synthesized So-AgNPs consist irregular size, spherical shape and thoroughly dispersed above the plane. Anticancer evaluation illustrated that the So-AgNPs have dose dependent anti-breast and anti-hepatic cancer activity (range of 97.72 ± 0.42 – 54.86 ± 0.46 % cell viability), which were noticed more effective than raw fruit extract of Scindapsus Officinalis. The computational anticovid prediction of major phyto-compound of the extract [which designate as inhibitor 1: ((2R,3S,4S,5R)-2-(hydroxymethyl)-6-(((1S,5S)-1-methyl-5-(2-methylprop-1-en-1-yl)cyclopent-2-en-1-yl)oxy)tetrahydro-2H-pyran-3,4,5-triol)] illustrated moderate tendency to interact with corona main protease enzyme (expected pIC > 6 μM). However, the molecular docking and dynamics studies showed that selected compounds have moderate tendency to interact human dihydrofolate reductase and topoisomerase 1 enzyme. The accomplished approach shows that So-AgNPs with adsorbed phytocompounds on its surface consist valuable experimentally proved anticancer potency and computationally predicted anticovid effect. Thus, the formulation can be used as an alternative to the covid infected cancer population.

Proposition of a new allosteric binding site for potential SARS-CoV-2 3CL protease inhibitors by utilizing molecular dynamics simulations and ensemble docking.

The SARS-CoV-2 3CL protease (3CLpro) shows a high similarity with 3CL proteases of other beta-coronaviruses, such as SARS and MERS. It is the main enzyme involved in generating various non-structural proteins that are important for viral replication and is one of the most important proteins responsible for SARS-CoV-2 virulence. In this study, we have conducted an ensemble docking of molecules from the DrugBank database using both the crystallographic structure of the SARS-CoV-2 3CLpro, as well as five conformations obtained after performing a cluster analysis of a 300 ns molecular dynamics (MD) simulation. This procedure elucidated the inappropriateness of the active site for non-covalent inhibitors, but it has also shown that there exists an additional, more favorable, allosteric binding site, which could be a better target for non-covalent inhibitors, as it could prevent dimerization and activation of SARS-CoV-2 3CLpro. Two such examples are radotinib and nilotinib, tyrosine kinase inhibitors already in use for treatment of leukemia and which binding to the newly found allosteric binding site was also confirmed using MD simulations. Communicated by Ramaswamy H. Sarma.

Molecular dynamics analysis of phytochemicals from Ageratina adenophora against COVID-19 main protease (Mpro) and human angiotensin-converting enzyme 2 (ACE2).

The outbreak of COVID-19 created unprecedented strain in the healthcare system. Various research revealed that COVID-19 main protease (Mpro) and human angiotensin-converting enzyme 2 (ACE2) are responsible for viral replication and entry into the human body, respectively. Blocking the activity of these enzymes gives a potential therapeutic target for the COVID-19. The objective of the study was to explore phytochemicals from Ageratina adenophora against SARS-CoV-2 through in-silico studies. In this study, 34 phytochemicals of A. adenophora were docked with Mpro and ACE2 through AutoDock Tools-1.5.6 and their binding affinity was studied. Phytochemicals with higher affinity have been chosen for further molecular dynamics simulations to determine the stability with target protein. Molecular dynamics simulations were studied on GROMACS 5.1.4 version. Furthermore, 5-ß-glucosyl-7-demethoxy-encecalin (5GDE) and 2-oxocadinan-3,6(11)-dien-12,7-olide (BODO) were found to be potential blockers with excellent binding affinity with Mpro and ACE2 than their native inhibitors remdesivir and hydroxychloroquine respectively. The drug likeness study and pharmacokinetics of the phytoconstituents present in A. adenophora provide an excellent support for the lead drug discovery against COVID-19.