Praveen ISAET

2017

A variety of compounds from medicinal plants have been reported to possess antiinflammatory properties. Selected natural compounds that exhibit anti-inflammatory properties were subjected to docking simulation using AutoDock Vina to investigate their interaction modes to the potential macromolecular targets. The docking was performed using different molecular targets, i.e., cyclooxygenase-2, phospholipase A2, NF-κB inhibitor, and interleukin-1 receptor. It revealed that flavonoids have the highest affinity to the macromolecular targets (the lowest binding energy values) and the highest consistency of interaction model. Some terpenoids were identified to have potential inhibitor of phospholipase A2.

Evidence Based Validation of Traditional Medicines, 2021

In the current scenario of medicine, products from natural source have been significantly contributing towards the therapeutic approach in the treatment of disease ailments ranging from simple to complicated ones. The World Health Organization has stated that approximately 80% of the global population rely on herbal medicines/products for their healthcare benefits. But in many cases, the utilization of herbal products as medicine has slowed down due to their lack of standardization involving botanical, chemical and biological (activity/toxicity) aspects. Standardization of medicinal plants and its active constituents has been the major event in the field of plant science involving ethnopharmacology, phytomedicine and pharmacognosy. The conventional or traditional standardization method of medicinal plant research is a cumbersome process, expensive, time-consuming and to a less extent outdated. Hence, a computational technique incorporating in silico molecular docking simulation study has become an essential tool for drug discovery, standardization and screening of phytochemicals. In this chapter, a comprehensive information have been discussed on the approach, significance and application of molecular docking study towards the ligand-protein interaction taking examples of pure active

VirusDisease

SARS-CoV-2, the causative virus of the Corona virus disease that was first recorded in 2019 (COVID-19), has already affected over 110 million people across the world with no clear targeted drug therapy that can be efficiently administered to the wide spread victims. This study tries to discover a novel potential inhibitor to the main protease of the virus, by computer aided drug discovery where various major active phytochemicals of the plant Boerhavia diffusa Linn. namely 2-3-4 beta-Ecdysone, Bioquercetin, Biorobin, Boeravinone J, Boerhavisterol, kaempferol, Liriodendrin, quercetin and trans-caftaric acid were docked to SAR-CoV-2 Main Protease using Molecular docking server. The ligands that showed the least binding energy were Biorobin with-8.17 kcal/mol, Bioquercetin with-7.97 kcal/mol and Boerhavisterol with-6.77 kcal/mol. These binding energies were found to be favorable for an efficient docking and resultant inhibition of the viral main protease. The graphical illustrations and visualizations of the docking were obtained along with inhibition constant, intermolecular energy (total and degenerate), interaction surfaces and HB Plot for all the successfully docked conditions of all the 9 ligands mentioned. Additionally the druglikeness of the top 3 hits namely Bioquercetin, Biorobin and Boeravisterol were tested by ADME studies and Boeravisterol was found to be a suitable candidate obeying the Lipinsky's rule. Since the main protease of SARS has been reported to possess structural similarity with the main protease of MERS, comparative docking of these ligands were also carried out on the MERS Mpro, however the binding energies for this target was found to be unfavorable for spontaneous binding. From these results, it was concluded that Boerhavia diffusa possess potential therapeutic properties against COVID-19. Keywords Boerhavia diffusa Á SARS-CoV-2 Á Covid-19 Á Biorobin Á Bioquercetin Á Boerhavisterol

Research journal of Agricultural Sciences, 2023

In the current scenario medicinal products from natural source have been significantly contributing towards the therapeutic approach in the treatment of diseases ranging from simple to complicate. The utilization of herbal products has slowed down due to lack of standardization involving botanical, chemical and biological (activity /toxicity) aspects. Hence a computational technique incorporating in silico molecular docking simulation study has become an essential tool for drug discovery, standardization and screening of phytochemicals. In this molecular docking study, the ligand-protein interaction of pure active phytol against the targeted fusarium protein is done.

International Journal of Ayurvedic Medicine

Adathodai kudineer (AK) a Classical Siddha formulation is used to treat various fevers which cause moderate to severe acute respiratory symptoms as is indicated in the text. GC-MS analysis was carried out to identify the presence of potent lead molecules in AK against novel corona virus. The aqueous extract has shown the following bioactive compounds such as Napthalene, Benzene Propanol, Benzene Acetic Acid, Furazan-3-amine, Pyrazol-4-Carboxylic acid, 2(3H) Furanone. The ethanolic extract of AK exhibited the molecular compounds such as Eucalyptol, Toluene, 2-Carene, Alpha-Copaene, 1,6-Cyclodecadiene, Aromadendrene, Gamma-murolene, Beta-copaene, Cubebol, Selina-3,7 (11) - Diene, 2-Butanone. Molecular docking is a powerful approach in current trends to identify the possibility of pharmacological effects of medicinal compounds which could be exerted over their Corresponding Protein targets which are relevant for causing disease. Using Auto dock Vina Software, the biomolecules of AK wer...

2021

Due to advancement in the bioinformatics, there is a rapid increase in the computational method to predict the interaction between the interface of two biological origin molecules. Bioinformatics reduces the tedious task to perform the repeated analysing of various molecules interaction and gives the best interface interaction as an output. Prediction and experiment are the ways that undergo simultaneously and provides best route. It gives the promising result with a good precision value. The virtual screening method has been broadly acceptable as it omits the undesirable molecules from the compound repositories and gives a platform with a low cost and timeconsuming process. In our present study we have carry out the computational approach to predict and find out the anticancerous protein from curry leaves. We have selected the target from PDB and the ligand from the PubChem data base. For the preparation of target, we have removed the water molecules and added the polar hydrogen group. And for the preparation of ligand, we have detected the torsion root where docking can be processed. All the files of target and ligand were saved in pdbqt format. We have taken three breast cancerous protein into consideration for the molecular docking against the three anticancerous drugs obtained from PubMed are Oestradiol (PDB ID-3HB5), HER2 (PDB ID-1N8Z) and NUDT-5(PDB ID-5NQR). Oestradiol is a well characterized sex hormone that stimulates breast cancer in female. HER2 protein, when inappropriately activated leads to proliferation and differentiation of breast cancer cells. NUDT 5 has the importance in the gene regulation and the proliferation of breast cancer cells. After the molecular docking via Auto dock Vina Mahanine and Pyrayafoline D showed least interaction energy with the breast cancerous protein. The cancerous protein taken into consideration is also responsible for the other types of cancer but we are mainly focused on the breast cancer. Our present study concludes that the Murraya koenigii may serve as a potential source of bioactive compounds in the prevention of cancer. The potential for developing an anticancerous drugs from higher eukaryotic plants appears rewarding for the mankind as it leads to the development of new drugs that will be helpful for the cancer patient in present date.

Journal of Applied Pharmaceutical Science, 2019

Accumulation of urate crystals and subsequent inflammation are the major cause of pathogenesis of gout. Two pro inflammatory cytokines IL17A and IL18 are upregulated in the serum of gout patients and plays a major role in promoting inflammation. Inhibition of these cytokines by plant phytochemicals would reduce the severity of inflammation in gout. In the present study, in silico analysis of inhibition of IL17A and IL18 by 10 plant phytochemicals were studied using the AutoDock 4.2 based on the principles of Lamarckian genetic algorithm. The results revealed a binding energy in the range of −6.32 kcal/mol to −3.5 kcal/mol and interacted with the amino acids in active pocket of IL17A and IL18. Among all the compounds, syringaresinol showing the least binding energy of −6.05 kcal/mol with IL17A and −6.32 kcal/mol with IL18. The control drug, allopurinol showed a binding energy of −3.32 and −3.18 kcal/mol with IL17A and IL18, respectively. In addition, ADME/T properties of the compounds were also analyzed to predict their drug likeliness. This docking study can be used for developing potent inhibitors of IL17A and IL18 for the treatment of gout.

Karbala international journal of modern science, 2022

The envelope protein (E) is a fusion class II protein that is essential for DENV fusion. We use two active compounds derived from commonly used plants in Indonesia: galangin and kaempferide. We ran a docking and 1000 ps molecular dynamic analysis with normal physiological parameters. During the simulation, galangin and kaempferide binding sites fluctuated. But chloroquine has lesser ligand mobility, hence keeping contact with fusion loops, whereas both drugs lose contact with hydrophobic pockets. However, the two active compounds have a more stable ligand configuration. Less than 2 Å alterations were seen in the RMSF simulation of the protein E residues. In a 1000 ps simulation, all tested compounds form stable complex with protein E, demonstrating that the two active compounds may be predicted as DENV-2 E protein fusion inhibitors, despite chloroquine inhibiting in a unique manner linked to its interaction domains.

Bioinformation, 2016

Dengue disease is a global disease that has no effective treatment. The dengue virus (DENV) NS4B is a target for designing specific antivirals due to its importance in viral replication. Medicinal plants have been a savior for dengue virus as they consist of a class of phytochemicals having anti-viral activity and can pose a new approach ofstrong drug against viruses. The present study analyzes the activity of compounds against NS4B of DENV (1-4) serotypes. In this study Catechin, Cianidanol, Epicatechin, Eupatoretin, Glabranin, Laurifolin, DL-Catechin, astherapeutic agents were filtered by using Lipinski rule's five and the drug-likeness property of these agents were used for assessment of pharmacological properties. The molecular docking results presented the 2-D structures of bioactive complex, which interacted with especially conserved residues of target domains. Interestingly, we find the Catechin, Laurifolin, Cianidanol have highest binding energy against NS4B in DENV-1,2,4 which is evident by the formation of more hydrogen bonds with the amino acid residues at the binding site of the receptor. Our results revealed that the bioactive compound, especially Catechin has significant anti-dengue activities. In addition, this study may be helpful in further experimental investigations.

International Journal of Ayurvedic Medicine

Corona virus disease (COVID-19) is an infectious pandemic disease caused by the newly discovered novel corona virus. World Health Organization has declared the global health emergency due to COVID19 outbreak. Currently, there is no specific treatment or vaccine for fighting against this infectious disease. Aadathodai Kudineer is a drug indicated for Iya Erumal, Kozhai Kattu, Kabasuram. Upon the mortality and severity of the disease COVID19, we tried to identify the possible inhibition of phytocomponents of Aadathodai Kudineer in inhibiting Main Protease and ACE2 Receptor Spike protein SARS-CoV-2 through molecular docking studies. Methodology: In Silico molecular docking analysis was performed for phytocomponents present in the Aadathodai Kudineer formulation for targets main protease and ACE2 Receptor Spike protein, PDB ID: 6LU7 and PDB ID: 2AJF using Autodock tool. ADME properties was also predicted for all the above compounds. Results: Among the 9 active Phytocompounds present in ...