Discovery of 5,7-Dihydro-6H-pyrrolo[2,3-d]pyrimidin-6-ones as Highly Selective CDK2 Inhibitors

Recent advances in regulating the cell cycle through inhibiting CDKs for cancer treatment

The inhibition of cyclin-dependent kinases (CDKs) is considered a promising strategy for cancer treatment due to their role in cell cycle regulation. However, CDK inhibitors with no selectivity among CDK families have not been approved. A CDK inhibitor with high selectivity for CDK4/6 exhibited significant treatment effects on breast cancer and has become a heavy bomb on the market. Subsequently, resistance gradually decreased the efficacy of selective CDK4/6 inhibitors in breast cancer treatment. In this review, we first introduce the development of selective CDK4/6 inhibitors and then explain the role of CDK2 activation in inducing resistance to CDK4/6 inhibitors. Moreover, we focused on the development of CDK2/4/6 inhibitors and selective CDK2 inhibitors, which will aid in the discovery of novel CDK inhibitors targeting the cell cycle in the future.

Targeting cyclin-dependent kinases: From pocket specificity to drug selectivity

The development of selective modulators of cyclin-dependent kinases (CDKs), a kinase family with numerous members and functional variations, is a significant preclinical challenge. Recent advancements in crystallography have revealed subtle differences in the highly conserved CDK pockets. Exploiting these differences has proven to be an effective strategy for achieving excellent drug selectivity. While previous reports briefly discussed the structural features that lead to selectivity in individual CDK members, attaining inhibitor selectivity requires consideration of not only the specific structures of the target CDK but also the features of off-target members. In this review, we summarize the structure-activity relationships (SARs) that influence selectivity in CDK drug development and analyze the pocket features that lead to selectivity using molecular-protein binding models. In addition, in recent years, novel CDK modulators have been developed, providing more avenues for achieving selectivity. These cases were also included. We hope that these efforts will assist in the development of novel CDK drugs.

Inhibitors and PROTACs of CDK2: challenges and opportunities

INTRODUCTION

Abundant evidence suggests that the overexpression of CDK2-cyclin A/E complex disrupts normal cell cycle regulation, leading to uncontrolled proliferation of cancer cells. Thus, CDK2 has become a promising therapeutic target for cancer treatment. In recent years, insights into the structures of the CDK2 catalytic site and allosteric pockets have provided notable opportunities for developing more effective clinical candidates of CDK2 inhibitors.

AREA COVERED

This article reviews the latest CDK2 inhibitors that have entered clinical trials and discusses the design and discovery of the most promising new preclinical CDK2 inhibitors in recent years. Additionally, it summarizes the development of allosteric CDK2 inhibitors and CDK2-targeting PROTACs. The review encompasses strategies for inhibitor and PROTAC design, structure-activity relationships, as well as in vitro and in vivo biological assessments.

EXPERT OPINION

Despite considerable effort, no CDK2 inhibitor has yet received FDA approval for marketing due to poor selectivity and observed toxicity in clinical settings. Future research must prioritize the optimization of the selectivity, potency, and pharmacokinetics of CDK2 inhibitors and PROTACs. Moreover, exploring combination therapies incorporating CDK2 inhibitors with other targeted agents, or the design of multi-target inhibitors, presents significant promise for advancing cancer treatment strategies.

Macrocyclization strategy for improving candidate profiles in medicinal chemistry

Macrocycles are defined as cyclic compounds with 12 or more members. In medicinal chemistry, they are categorized based on their core chemistry into cyclic peptides and macrocycles. Macrocycles are advantageous because of their structural diversity and ability to achieve high affinity and selectivity towards challenging targets that are often not addressable by conventional small molecules. The potential of macrocyclization to optimize drug-like properties while maintaining adequate bioavailability and permeability has been emphasized as a key innovation in medicinal chemistry. This review provides a detailed case study of the application of macrocyclization over the past 5 years, starting from the initial analysis of acyclic active compounds to optimization of the resulting macrocycles for improved efficacy and drug-like properties. Additionally, it illustrates the strategic value of macrocyclization in contemporary drug discovery efforts.

A dual diffusion model enables 3D molecule generation and lead optimization based on target pockets

Structure-based generative chemistry is essential in computer-aided drug discovery by exploring a vast chemical space to design ligands with high binding affinity for targets. However, traditional in silico methods are limited by computational inefficiency, while machine learning approaches face bottlenecks due to auto-regressive sampling. To address these concerns, we have developed a conditional deep generative model, PMDM, for 3D molecule generation fitting specified targets. PMDM consists of a conditional equivariant diffusion model with both local and global molecular dynamics, enabling PMDM to consider the conditioned protein information to generate molecules efficiently. The comprehensive experiments indicate that PMDM outperforms baseline models across multiple evaluation metrics. To evaluate the applications of PMDM under real drug design scenarios, we conduct lead compound optimization for SARS-CoV-2 main protease (Mpro) and Cyclin-dependent Kinase 2 (CDK2), respectively. The selected lead optimization molecules are synthesized and evaluated for their in-vitro activities against CDK2, displaying improved CDK2 activity.

Identification of abemaciclib derivatives targeting cyclin-dependent kinase 4 and 6 using molecular dynamics, binding free energy calculation, synthesis, and pharmacological evaluation

CDK4/6 plays a crucial role in various cancers and is an effective anticancer drug target. However, the gap between clinical requirements and approved CDK4/6 drugs is unresolved. Thus, there is an urgent need to develop selective and oral CDK4/6 inhibitors, particularly for monotherapy. Here, we studied the interaction between abemaciclib and human CDK6 using molecular dynamics simulations, binding free energy calculations, and energy decomposition. V101 and H100 formed stable hydrogen bonds with the amine-pyrimidine group, and K43 interacted with the imidazole ring via an unstable hydrogen bond. Meanwhile, I19, V27, A41, and L152 interacted with abemaciclib through π-alkyl interactions. Based on the binding model, abemaciclib was divided into four regions. With one region modification, 43 compounds were designed and evaluated using molecular docking. From each region, three favorable groups were selected and combined with each other to obtain 81 compounds. Among them, C2231-A, which was obtained by removing the methylene group from C2231, showed better inhibition than C2231. Kinase profiling revealed that C2231-A showed inhibitory activity similar to that of abemaciclib; additionally, C2231-A inhibited the growth of MDA-MB-231 cells to a greater extent than did abemaciclib. Based on molecular dynamics simulation, C2231-A was identified as a promising candidate compound with considerable inhibitory effects on human breast cancer cell lines.

Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design

Selective CDK2 inhibitors have the potential to provide effective therapeutics for CDK2-dependent cancers and for combating drug resistance due to high cyclin E1 (CCNE1) expression intrinsically or CCNE1 amplification induced by treatment of CDK4/6 inhibitors. Generative models that take advantage of deep learning are being increasingly integrated into early drug discovery for hit identification and lead optimization. Here we report the discovery of a highly potent and selective macrocyclic CDK2 inhibitor QR-6401 (23) accelerated by the application of generative models and structure-based drug design (SBDD). QR-6401 (23) demonstrated robust antitumor efficacy in an OVCAR3 ovarian cancer xenograft model via oral administration.