In this chapter, we present a focused overview of recent investigations utilizing various in silico methods to explore potential therapeutic agents for diabetes, as a prominent representative of endocrine disorders. We highlight approved or potential therapeutic targets that have been examined through molecular modeling techniques including docking, molecular dynamics simulations, ADMET prediction, and QSAR modeling. Discussed targets include glycosidases, PPARs, DPP-4, and SGLT2, among others. A special case is examined through molecular dynamics simulations of insulin, especially on its conformational changes, as those are important in its activity or dysfunction. As we conclude, it is evident that in silico methods have become integral in drug discovery, repositioning, and optimization processes. A notable development in recent research is the widespread adoption of ADMET tools, and the expanding role of artificial intelligence, particularly machine learning, is anticipated to revolutionize the application of traditional in silico methods.