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Malik, J. A.

Publications and source records attributed to Malik, J. A..

2 recordsLinked to original sources
bioRxiv2021

In-silico pharmacophore and Molecular Docking based drug discovery against Marburg Virus Viral Protein VP35; A potent of MAVD.

Marburg virus is a member of filoviridae and spreads severe Marburg hemorrhagic illness in humans and animals. Nowadays, there is no vaccine available that can completely stop the replication of Marburg replication. Therefore, this study is designed to repurpose the effective therapeutic antiviral drug by using a computational approach against exploring the mechanism of Marburg virus Viral protein 35. We have retrieved about 40570 drug-like small compounds from the ZINC database using the "ZINC Pharmer" online tool. Molecular docking of the ligands from the ready-to-dock database has been carried out using MOE. The five drugs have been identified to bind with VP35 possibly. A study was also performed to evaluate the drug-like characteristics of the substances for absorption, distribution, metabolism, and excretion (ADME). The findings clearly showed that ligands are interacting with the MARV VP35 protein. Interestingly, Lipinskis rule of five was observed by all ligands. These findings provide the foundation for reconstituting and utilizing molecules as a possible therapy for Marburg Virus Disease (MVD).

bioinformatics↗
bioRxiv2021

Discovery of potential drug-like compounds against Viral protein (VP40) of Marburg Virus using pharmacophoric based virtual screening from ZINC database.

Marburg virus (MARV) has been confirmed to cause extreme hemorrhagic fever (HFM) in human and animals. The effective and suitable vaccine to treat the MARV virus is not commercialized in public and demands rigorously tested on several scales. This research used a CADD (Computer-Aided Drug Design) computational based technology to find novel drug-like compounds that could inhibit the replicating of the VP40. The pharmacophoric features bases screening was done using an online computational based software, "ZINC Pharmer". We retrieved about 32456 compounds mainly focused on the properties of pharmacophores from the ZINC database. Lipinskis rule was also used to predict these drug-like compounds. as well as molecular coupling-dependent screening and selection of VP40 screening ligand complexes based on S-rank (lower than reference) and value of root, mean square (RMSD) (bottom) to examine for reference) using the Molecular Working Environment (MOE) machine. As a result, 100 compounds were found to have a close interaction with MARV VP40, followed by the Binding energy (BE) analysis of these 100 compounds. Only 50 were the strongest binding energy than favipiravir [reference inhibitor] after using the MOE-LigX algorithm to compare their binding energy. After that, ADMET analysis predicted only five compounds (ZINC95457352, ZINC38752258, ZINC38752253, ZINC39272175, and ZINC38752377) passed the ADMET parameters and have the strongest inhibitory effect against the MARVs VP40. It has been suggested that these "drug-like" candidates have an increased ability to inhibit MARV replication, leading to treatment of MARVD.

bioinformatics↗