Antidiabetic Drugs and Target Prediction on Human for Type 2 Diabetes Mellitus: A Minireview of Pharmacological Profile

With the advent of Covid-19, it is necessary to repurpose new treatment alternatives, either in the form of an effective single dose of these antidiabetic drug agents or an efficacious combination of them for elderly population with or had suffered this condition. Such new treatment alternatives would prevent the development of the common comorbidities, such as heart failure, nephropathy, neuropathy and retinopathy. This mini-review has the objective of predicting the targets of bioactive small molecules in human using healthcare applied artificial intelligence. Method. The tool is a tuned algorithm, with novel data in web interface. Results. Information figures of Swiss Target Prediction, which allow predictions on therapy combinations and probable side effects, were reordered. This tool is useful to understand the molecular mechanisms underlying a given phenotype or bioactivity, to rationalize possible favorable or unfavorable side effects, to predict off-targets of known molecules and to clear the way to drug repurposing. Predictions are done using a ligand-based approach, based on the similarity between a query molecule and the known ligands of a large collection of protein targets. Conclusion. The result of this study highlighted crucial recommendations for the use of some of the antidiabetic agent groups in diabetic patients, which would also reduce the cost of their therapies. This is very important for patients who, due to their ill condition, are obliged to take medicine for a long period and whose life depends on it.