Targeting the cyclin-dependent kinase family in anticancer drug discovery: From computational to experimental studies

Abstract

Uncontrolled cell proliferation, primarily regulated by cyclin-dependent kinases (CDKs), is a critical driver of cancer progression, with dysregulation of CDKs contributing to various cancer types. CDKs have emerged as well-established targets for cancer therapy; however, traditional drug development methods have often proven to be time-consuming, challenging, and expensive. Recent advancements in CDK inhibitors (CDKIs) have shown immense clinical potential but many first-generation CDKIs face issues of non-selectivity and significant toxicity, limiting their clinical approval. To address these challenges, innovative computational approaches, particularly pharmacophore modeling, have the potential to streamline drug discovery. These methods can guide the selection of small molecules through target-specific structure-activity relationship (SAR) models and chemotypes screening across databases, thereby accelerating the identification of effective CDKIs. This review paper summarizes the latest developments on CDK inhibitors, highlights their structural features, and the methodologies (key databases & software tools) that can provide further suggestions for future drug development.