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The current study investigates the effectiveness of phytocompounds from the whole green jackfruit flour methanol extract (JME) against obesity-linked diabetes mellitus using integrated network pharmacology and molecular modeling approach. Through network pharmacology, druglikeness and pharmacokinetics, molecular docking simulations, GO analysis, molecular dynamics simulations, and binding free energy analyses, it aims to look into the mechanism of the JME phytocompounds in the amelioration of obesity-linked diabetes mellitus. There are 15 predicted genes corresponding to the 11 oral bioactive compounds of JME. The most important of these 15 genes was MAPK3. According to the network analysis, the insulin signaling pathway has been predicted to have the strongest affinity to MAPK3 protein, which was chosen as the target. With regard to the molecular docking simulation, the greatest notable binding affinity for MAPK3 was discovered to be caffeic acid (-8.0 kJ/mol), deoxysappanone B 7,3'-dimethyl ether acetate (DBDEA) (-8.2 kJ/mol), and syringic acid (-8.5 kJ/mol). All the compounds were found to be stable inside the inhibitor binding pocket of the enzyme during molecular dynamics simulation. During binding free energy calculation, all the compounds chiefly used Van der Waal's free energy to bind with the target protein (caffeic acid: 102.296 kJ/mol, DBDEA: -104.268 kJ/mol, syringic acid: -100.171 kJ/mol). Based on these findings, it may be inferred that the reported JME phytocompounds could be used for in vitro and in vivo research, with the goal of targeting MAPK3 inhibition for the treatment of obesity-linked diabetes mellitus.

The most commonly accepted hypothesis of Alzheimer's disease (AD) is the amyloid hypothesis caused due to formation of accumulation of Aβ42 isoform, which leads to neurodegeneration. In this regard, presenilin-1 (PSEN-1) and -2 (PSEN-2) proteins play a crucial role by altering the amyloid precursor protein (APP) metabolism, affecting γ-secretase protease secretion, finally leading to the increased levels of Aβ. In the absence of reported commercial pharmacotherapeutic agents targeting presenilins, we aim to propose benzophenone integrated derivatives (BIDs) as the potential inhibitors of presenilin proteins through in silico approach. The study evaluates the interaction of BIDs through molecular docking simulations, molecular dynamics simulations, and binding free energy calculations. This is the first ever computational approach to discover the potential inhibitors of presenilin proteins. It also comprises druglikeliness and pharmacotherapeutic potential analysis of the compounds. Out of all the screened BIDs, BID-16 was found to be the lead compound against both the presenilin proteins. Based on these results, one can evaluate BID-16 as an anti-Alzheimer's potential specifically targeting presenilin proteins in near future using in vitro and in vivo methods.