Millions of people in developing nations rely on herbal traditional medicine for the treatment of ailments such as diabetes mellitus, stomach disorders and respiratory diseases. Xeroderris stuhlmannii (Taub.) Mendonca & E.P. Sousa is a medicinal plant used traditionally in Zimbabwe to treat diabetes mellitus and its complications. However, there is no scientific evidence to support its role as an antidiabetic medicinal plant. Here we hypothesized that Xeroderris stuhlmannii (Taub.) Mendonca & E.P. Sousa contain bioactive phytochemicals that can scavenge free radicals, and inhibit digestive enzymes that contribute to type 2 diabetes mellitus (T2DM). To test this hypothesis, we examined the free radical scavenging potential of crude extracts using the diphenyl-2-picrylhydrazyl assay in vitro. Furthermore, we carried out in vitro antidiabetic activity of crude extracts using chromogenic 3,5-dinitrosalicylic acid and p-nitrophenyl-alpha-D-glucopyranoside substrates on alpha-amylase and alpha-glucosidase. In addition, we used molecular docking approaches to screen for bioactive phytochemical compounds targeting the digestive enzymes. Our results showed that phytochemicals in Xeroderris stuhlmannii (Taub.) Mendonca & E.P. Sousa extracts scavenged free radicals with IC50 values ranging from 0.011-0.013 micrograms/mL. Further, the crude extracts significantly inhibited alpha-amylase and alpha-glucosidase with IC50 values of 12.9-21.1 micrograms/mL and 8.8-16.0 micrograms/mL, respectively. In silico molecular docking findings and pharmacokinetic predictions showed that myricetin is a novel inhibitor of the digestive enzymes that contributes to high blood glucose. Collectively, our findings suggest pharmacological targeting of digestive enzymes by Xeroderris stuhlmannii (Taub). Mendonca & E.P. Sousa crude extracts could lesion type 2 mellitus complications in humans.
The emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) impedes the End TB Strategy by the World Health Organization aiming for zero deaths, disease, and suffering at the hands of tuberculosis (TB). Mutations within anti-TB drug targets play a major role in conferring drug resistance within Mtb; hence, computational methods and tools are being used to understand the mechanisms by which they facilitate drug resistance. In this article, computational techniques such as molecular docking and molecular dynamics are applied to explore point mutations and their roles in affecting binding affinities for anti-TB drugs, often times lowering the protein’s affinity for the drug. Advances and adoption of computational techniques, chemoinformatics, and bioinformatics in molecular biosciences and resources supporting machine learning techniques are in abundance, and this has seen a spike in its use to predict mutations in Mtb. This article highlights the importance of molecular modeling in deducing how point mutations in proteins confer resistance through destabilizing binding sites of drugs and effectively inhibiting the drug action.
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