Despite the fact that there are several anticancer drugs available, cancer has evolved using different pathways inside the cell. The protein tyrosine phosphatases pathway is responsible for monitoring cell proliferation, diversity, migration, and metabolism. More specifically, the SHP2 protein, which is a member of the PTPs family, is closely related to cancer. In our efforts, with the aid of a structure-based drug design, we optimized the known inhibitor SHP099 by introducing 1-(methylsulfonyl)-4-prolylpiperazine as a linker. We designed and synthesized three pyrazine-based small molecules. We started with prolines as cyclic amines, confirming that our structures had the same interactions with those already existing in the literature, and, here, we report one new hydrogen bond. These studies concluded in the discovery of methyl (6-amino-5-(2,3-dichlorophenyl)pyrazin-2-yl)prolylprolinate hydrochloride as one of the final compounds which is an active and acceptable cytotoxic agent.

Over the past few decades, drug discovery has greatly improved the outcomes for patients, but several challenges continue to hinder the rapid development of novel drugs. Addressing unmet clinical needs requires the pursuit of drug targets that have a higher likelihood to lead to the development of successful drugs. Here we describe a bioinformatic approach for identifying novel cancer drug targets by performing statistical analysis to ascertain quantitative changes in expression levels between protein-coding genes, as well as co-expression networks to classify these genes into groups. Subsequently, we provide an overview of druggability assessment methodologies to prioritize and select the best targets to pursue.