In-Silico molecular screening of natural compounds as a potential therapeutic inhibitor for Methicillin-resistant Staphylococcus aureus inhibition.

Methicillin-resistant Staphylococcus aureus (MRSA) is a life-threatening superbug causing infectious diseases such as pneumonia, endocarditis, osteomyelitis, etc. Conventional antibiotics are ineffective against MRSA infections due to their resistance mechanism against the antibiotics. The Penicillin Binding Protein (PBP2a) inhibits the activity of antibiotics by hydrolyzing the ß-lactam ring. Thus, alternate treatment methods are needed for the treatment of MRSA infections. Natural bioactive compounds exhibit good inhibition efficiency against MRSA infections by hindering its enzymatic mechanism, efflux pump system, etc. The present work deals with identifying potential and non-toxic natural bioactive compounds (ligands) through molecular docking studies through StarDrop software. Various natural bioactive compounds which are effective against MRSA infections were docked with the protein (6VVA). The ligands having good binding energy values and pharmacokinetic and drug-likeness properties have been illustrated as potential ligands for treating MRSA infections. From this exploration, Luteolin, Kaempferol, Chlorogenic acid, Sinigrin, Zingiberene, 1-Methyl-4-(6-methylhepta-1,5-dien-2-yl)cyclohex-1-ene, and Curcumin have found with good binding energies of -8.6 kcal/mol, -8.4 kcal/mol, -8.2 kcal/mol, -7.5 kcal/mol, -7.4 kcal/mol, -7.3 kcal/mol, and -7.2 kcal/mol, respectively.

Pharmacokinetic profiling of anticancer phytocompounds using computational approach.

INTRODUCTION: Natural products exhibit diverse scaffolds and are considered as suitable candidates for development of leads. However, poor pharmacokinetics often acts as a hindrance during the drug discovery process. OBJECTIVE: With a view of exploring the absorption, distribution, metabolism, excretion and toxicity (ADMET) profile of plant-based anticancer compounds, open-access databases (NPACT, CancerHSP and TaxKB) were analysed to identify molecules having properties favourable for drug ability. METHODOLOGY: Our workflow involved identification of molecules capable of passing each of the ADMET barriers based on physicochemical properties of molecules, and physiological barriers and factors. RESULTS: The results revealed that out of 5086 phytomolecules, 63% were orally absorbable and 52% distributable. Also, an appreciable proportion of these compounds (45%) could be metabolised and excreted. Furthermore, 28% were found to be non-toxic for cardio toxicity and central nervous system (CNS) activity. Additionally, comparison against known anticancer drugs (reference dataset) revealed that the three libraries exhibit similar trends, thus providing additional confidence to the predictions. Overall, 28% of the molecular dataset was found to have suitable pharmacokinetic properties. We have also discussed a few natural products which exhibit favourable ADMET as well as low nano-micromolar in vitro anticancer activity. CONCLUSION: We have created an interactive database (ADMETCan), which provides access to predicted ADMET of these anticancer phytomolecules. The ease of availability of this dataset is expected to minimise failure rate of these compounds and thus is expected to be beneficial to the scientific community involved in anticancer identification and development.