In-Silico Research to Screen Various Phytochemicals as Potential Therapeutics Against Beta Glucan Synthase Enzyme from Black Fungus Endangering Covid Patients in India

Abstract

Mucormycosis, has reportedly decimated numerous Indian states. This malady has already been deemed a catastrophe in several Indian states. Black fungus appears to have been a deadly, existence situation that needs medical assistance. Mucormycosis has indeed been medicated using antagonists of glucan biosynthesis processes, however, the discovery is now in its beginning stages. Because of its main functions in glucan biosynthesis, betaglucan synthase was picked as nothing more than a great option for therapeutic development in this investigation. The objectives of this research were about to conduct in-silico assessment plus molecular docking analysis on a number of phytocompounds (a total of 32 phytochemicals) in regard towards 1,3-beta-glucan synthase protein (4M80). There have been very few studies done on in-silico investigation by using beta-glucan synthase as target protein for various phytochemicals to date. The strongest interacting phytomolecule was found to be rhamnazin 3- rutinoside, with the largest negative correlating -10.54 Kcal/mol. The interacting energy of hesperidin, the secondbest interacting chemical, would have to be -10.47 Kcal/mol, whereas pectolinarin, the third-best dealing compound, had been -10.38 Kcal/mol. This study, which aimed to predict the repressive exercises of plant-derived materials that specifically target 4M80 proteins, found a number of interesting findings, including how the pharmaceutical had a vastly greater posture as well as complexation than hydroxychloroquine and the antibiotic fluconazole. Furthermore, ADME was also carried out with all the selected compounds. More studies in animal and clinical prototype may lay the groundwork for some of these compounds to be utilised in drug research.

Comprehensive Review on the Virulence Factors and Therapeutic Strategies with the Aid of Artificial Intelligence against Mucormycosis

“…For instance, high cotH gene copy numbers are linked to increased virulence. Transcriptome analysis has identified Wex1, a novel exonuclease involved in virulence. , Virtual screening and AI applications in antifungal drug discovery : AI algorithms aid in predicting novel protein structures, drug-target interactions, virtual screening of drug libraries, and assessing molecular features like drug toxicity. , Researchers have applied these methods to identify potential inhibitors for mucormycosis, some of which are summarized in Table . , Machine learning (ML) in drug repurposing for fungal infections involves exploring extensive compound databases (HTVS for computer aided drug designing), property predictions (ADME/T), QSAR, and pharmacophore analysis . ML algorithms systematically screen existing drug databases for potential candidates against fungal infections, including mucormycosis.…”

“…Virtual screening and AI applications in antifungal drug discovery : AI algorithms aid in predicting novel protein structures, drug-target interactions, virtual screening of drug libraries, and assessing molecular features like drug toxicity. , Researchers have applied these methods to identify potential inhibitors for mucormycosis, some of which are summarized in Table . , …”