Discovery of a Series of 7-Azaindoles as Potent and Highly Selective CDK9 Inhibitors for Transient Target Engagement

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.

MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics

Molecular dynamics (MD) simulation is a powerful tool for characterizing ligand-protein conformational dynamics and offers significant advantages over docking and other rigid structure-based computational methods. However, setting up, running, and analyzing MD simulations continues to be a multi-step process making it cumbersome to assess a library of ligands in a protein binding pocket using MD. We present an automated workflow that streamlines setting up, running, and analyzing Desmond MD simulations for protein-ligand complexes using machine learning (ML) models. The workflow takes a library of pre-docked ligands and a prepared protein structure as input, sets up and runs MD with each protein-ligand complex, and generates simulation fingerprints for each ligand. Simulation fingerprints (SimFP) capture protein-ligand compatibility, including stability of different ligand-pocket interactions and other useful metrics that enable easy rank-ordering of the ligand library for pocket optimization. SimFPs from a ligand library are used to build & deploy ML models that predict binding assay outcomes and automatically infer important interactions. Unlike relative free-energy methods that are constrained to assess ligands with high chemical similarity, ML models based on SimFPs can accommodate diverse ligand sets. We present two case studies on how SimFP helps delineate structure-activity relationship (SAR) trends and explain potency differences across matched-molecular pairs of (1) cyclic peptides targeting PD-L1 and (2) small molecule inhibitors targeting CDK9.

Recent Discovery and Development of Inhibitors that Target CDK9 and Their Therapeutic Indications

CDK9 is a cyclin-dependent kinase that plays pivotal roles in multiple cellular functions including gene transcription, cell cycle regulation, DNA damage repair, and cellular differentiation. Targeting CDK9 is considered an attractive strategy for antitumor therapy, especially for leukemia and lymphoma. Several potent small molecule inhibitors, exemplified by TG02 (4), have progressed to clinical trials. However, many of them face challenges such as low clinical efficacy and multiple adverse reactions and may necessitate the exploration of novel strategies to lead to success in the clinic. In this perspective, we present a comprehensive overview of the structural characteristics, biological functions, and preclinical status of CDK9 inhibitors. Our focus extends to various types of inhibitors, including pan-inhibitors, selective inhibitors, dual-target inhibitors, degraders, PPI inhibitors, and natural products. The discussion encompasses chemical structures, structure-activity relationships (SARs), biological activities, selectivity, and therapeutic potential, providing detailed insight into the diverse landscape of CDK9 inhibitors.

Discovery of Selective and Potent Macrocyclic CDK9 Inhibitors for the Treatment of Osimertinib-Resistant Non-Small-Cell Lung Cancer

Effectiveness of epidermal growth factor receptor (EGFR) inhibitors, including Osimertinib, for treating non-small-cell lung cancer (NSCLC) is limited due to the continuous emergence of drug resistance. Hence, it is urgent to develop new therapeutic approaches. CDK9, a key regulator of RNA transcription, has emerged as a promising target for the development of antitumor drugs due to its crucial role in modulating the levels of antiapoptotic protein Mcl-1. Herein, we present the synthesis, optimization, and evaluation of selective CDK9 inhibitors with a macrocyclic scaffold that effectively suppresses the growth of NSCLC cells. Notably, compound Z11, a potent CDK9 inhibitor (IC50 = 3.20 nM) with good kinase selectivity, significantly inhibits cell proliferation and colony formation and induces apoptosis in Osimertinib-resistant H1975 cells. Furthermore, Z11 demonstrates a significant suppression of tumor growth in six patient-derived organoids, including three organoids resistant to Osimertinib. Overall, Z11 served as a promising macrocycle-based CDK9 inhibitor for treating Osimertinib-resistant NSCLC.

Computing the relative binding affinity of ligands based on a pairwise binding comparison network

Structure-based lead optimization is an open challenge in drug discovery, which is still largely driven by hypotheses and depends on the experience of medicinal chemists. Here we propose a pairwise binding comparison network (PBCNet) based on a physics-informed graph attention mechanism, specifically tailored for ranking the relative binding affinity among congeneric ligands. Benchmarking on two held-out sets (provided by Schrödinger and Merck) containing over 460 ligands and 16 targets, PBCNet demonstrated substantial advantages in terms of both prediction accuracy and computational efficiency. Equipped with a fine-tuning operation, the performance of PBCNet reaches that of Schrödinger's FEP+, which is much more computationally intensive and requires substantial expert intervention. A further simulation-based experiment showed that active learning-optimized PBCNet may accelerate lead optimization campaigns by 473%. Finally, for the convenience of users, a web service for PBCNet is established to facilitate complex relative binding affinity prediction through an easy-to-operate graphical interface.

Azaindole derivatives as potential kinase inhibitors and their SARs elucidation

Currently, heterocycles have occupied an important position in the fields of drug design. Among them, azaindole moiety is regarded as one privileged scaffold to develop therapeutic agents. Since two nitrogen atoms of azaindole increase the possibility to form hydrogen bonds in the adenosine triphosphate (ATP)-binding site, azaindole derivatives are important sources of kinase inhibitors. Moreover, some of them have been on the market or in clinical trials for the treatment of some kinase-related diseases (e.g., vemurafenib, pexidartinib, decernotinib). In this review, we focused on the recent development of azaindole derivatives as potential kinase inhibitors based on kinase targets, such as adaptor-associated kinase 1 (AAK1), anaplastic lymphoma kinase (ALK), AXL, cell division cycle 7 (Cdc7), cyclin-dependent kinases (CDKs), dual-specificity tyrosine (Y)-phosphorylation regulated kinase 1A (DYRK1A), fibroblast growth factor receptor 4 (FGFR4), phosphatidylinositol 3-kinase (PI3K) and proviral insertion site in moloney murine leukemia virus (PIM) kinases. Meanwhile, the structure-activity relationships (SARs) of most azaindole derivatives were also elucidated. In addition, the binding modes of some azaindoles complexed with kinases were also investigated during the SARs elucidation. This review may offer an insight for medicinal chemists to rationally design more potent kinase inhibitors bearing the azaindole scaffold.

A patent review of selective CDK9 inhibitors in treating cancer

INTRODUCTION

The dysregulation of CDK9 protein is greatly related to the proliferation and differentiation of various cancers due to its key role in the regulation of RNA transcription. Moreover, CDK9 inhibition can markedly downregulate the anti-apoptotic protein Mcl-1 which is essential for the survival of tumors. Thus, targeting CDK9 is considered to be a promising strategy for antitumor drug development, and the development of selective CDK9 inhibitors has gained increasing attention.

AREAS COVERED

This review focuses on the development of selective CDK9 inhibitors reported in patent publications during the period 2020-2022, which were searched from SciFinder and Cortellis Drug Discovery Intelligence.

EXPERT OPINION

Given that pan-CDK9 inhibitors may lead to serious side effects due to poor selectivity, the investigation of selective CDK9 inhibitors has attracted widespread attention. CDK9 inhibitors make some advance in treating solid tumors and possess the therapeutic potential in EGFR-mutant lung cancer. CDK9 inhibitors with short half-life and intravenous administration might result in transient target engagement and contribute to a better safety profile in vivo. However, more efforts are urgently needed to accelerate the development of CDK9 inhibitors, including the research on new binding modes between ligand and receptor or new protein binding sites.

Discovery of 2H-benzo[b][1,4]oxazin-3(4H)-one derivatives as potent and selective CDK9 inhibitors that enable transient target engagement for the treatment of hematologic malignancies

Cyclin-dependent kinase 9 (CDK9) is a transcriptional regulator and a potential therapeutic target in hematologic malignancies. Selective and transient CDK9 inhibition reduces Mcl-1 expression and induces apoptosis in Mcl-1-dependent tumor cells for survival. Here, we describe our efforts to discover a novel series of 2H-benzo[b][1,4]oxazin-3(4H)-one as CDK9 inhibitors. Compound 32k was identified as a selective CDK9 inhibitor with short pharmacokinetic and physicochemical properties suitable for intravenous administration. Short-term treatment with 32k resulted in a rapid dose-dependent decrease in cellular p-Ser2-RNAPII, Mcl-1 and c-Myc, leading to apoptosis in the MV4-11 cell line. Correspondingly, significant in vivo antitumor efficacy was observed in xenograft models derived from multiple hematological tumors with intermittent 32k dosing. These results provide evidence that selective transient CDK9 inhibitors could be used for the treatment of hematologic malignancies.

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022).

Mechanistic Insights into a CDK9 Inhibitor Via Orthogonal Proteomics Methods

Cyclin-dependent-kinases (CDKs) are members of the serine/threonine kinase family and are highly regulated by cyclins, a family of regulatory subunits that bind to CDKs. CDK9 represents one of the most studied examples of these transcriptional CDKs. CDK9 forms a heterodimeric complex with its regulatory subunit cyclins T1, T2 and K to form the positive transcription elongation factor b (P-TEFb). This complex regulates transcription via the phosphorylation of RNA polymerase II (RNAPolII) on Ser-2, facilitating promoter clearance and transcription elongation and thus remains an attractive therapeutic target. Herein, we have utilized classical affinity purification chemical proteomics, kinobeads assay, compressed CEllular Thermal Shift Assay (CETSA)-MS and Limited Proteolysis (LiP) to study the selectivity, target engagement and downstream mechanistic insights of a CDK9 tool compound. The above experiments highlight the value of quantitative mass spectrometry approaches to drug discovery, specifically proteome wide target identification and selectivity profiling. The approaches utilized in this study unanimously indicated that the CDK family of kinases are the main target of the compound of interest, with CDK9, showing the highest target affinity with remarkable consistency across approaches. We aim to provide guidance to the scientific community on the available chemical biology/proteomic tools to study advanced lead molecules and to highlight pros and cons of each technology while describing our findings in the context of the CDKs biology.

Discovery of novel and potent tacrine derivatives as CDK2 inhibitors

After optimization of the lead compound, ZLHT-7, a compound with 10-fold higher selectivity for CDK2 over CDK9, was discovered.

CDK9 Inhibitors in Cancer Research

Cyclin dependent kinase 9 (CDK9) played an essential role in regulating transcriptional elongation. Aberrations in CDK9 activity have been observed in various cancers, which made CDK9 was an attractive therapeutic...

Transcriptional cyclin-dependent kinases: Potential drug targets in cancer therapy

In the wake of the development of the concept of cell cycle and its limiting points, cyclin-dependent kinases (CDKs) are considered to play a central role in regulating cell cycle progression. Recent studies have strongly demonstrated that CDKs also has multiple functions, especially in response to extracellular and intracellular signals by interfering with transcriptional events. Consequently, how to inhibit their function has been a hot research topic. It is worth noting that the key role of CDKs in regulating transcription has been explored in recent years, but its related pharmacological targets are less developed, and most inhibitors have not entered the clinical stage. Accordingly, this perspective focus on the biological functions of transcription related CDKs and their complexes, some key upstream and downstream signals, and inhibitors for cancer treatment in recent years. In addition, some corresponding combined treatment strategies will provide a more novel perspective for future cancer remedy.