The Role of QSAR and Virtual Screening Studies in Type 2 Diabetes Drug Discovery.

Background: Due to the increasing number of diabetes cases worldwide, there is an international concern to provide even more effective treatments to control this condition.

Methods: This review brings together a selection of studies that helped to broaden the comprehension of various biological targets and associated mechanisms involved in type 2 diabetes mellitus.

Results: Such studies demonstrated that QSAR techniques and virtual screenings have been successfully employed in drug design projects.

In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment.

Studies have showed that there are many biological targets related to the cancer treatment, for example, TGF type I receptor (TGF-βRI or ALK5). The ALK5 inhibition is a strategy to treat some types of cancer, such as breast, lung, and pancreas. Here, we performed CoMFA and CoMSIA studies for 70 ligands with ALK5 inhibition.

Understanding electrostatic and steric requirements related to hypertensive action of AT(1) antagonists using molecular modeling techniques.

AT1 receptor is an interesting biological target involved in several important diseases, such as blood hypertension and cardiovascular pathologies. In this study we investigated the main electrostatic and steric features of a series of AT1 antagonists related to hypertensive activity using structure and ligand-based strategies (docking and CoMFA). The generated 3D model had good internal and external consistency and was used to predict the potency of an external test set.

Identifying structural features related to the biological activity of a series of AT1 antagonists from fragment-based drug design.

Antagonists of AT1 receptor are interesting substances to develop drugs that can be used for the treatment of hypertension and other diseases that affect the cardiovascular system. This study investigates the main interactions between various AT1 antagonists and the biological target by applying fragment-based drug design (Hologram QSAR - HQSAR). The proposed HQSAR model yielded significant correlation coefficients (q(2) = 0.