In silico design of small molecule inhibitors of CDK9/cyclin T1 interaction

Design, synthesis, and biological evaluation of novel 4,4'-bipyridine derivatives acting as CDK9-Cyclin T1 protein-protein interaction inhibitors against triple-negative breast cancer

Cyclin-dependent kinase 9 (CDK9) is directly related to tumor development in triple-negative breast cancer (TNBC) patients. Increased CDK9 is significantly associated with poor patient prognosis, while inhibiting CDK9-Cyclin T1 protein-protein interaction has recently been demonstrated as a new approach to TNBC treatment. Herein, we synthesized a novel class of 4,4'-bipyridine derivatives as potential CDK9-Cyclin T1 PPI inhibitors against TNBC. The represented compound B19 was found to be an excellent and selective CDK9-Cyclin T1 PPI inhibitor with good potency against TNBC cell lines while exhibiting lower toxicity in normal human cell lines than the positive compound I-CDK9. Notably, compound B19 showed good pharmacokinetic properties and excellent antitumor activity against TNBC (4T1) allografts in mice with a therapeutic index of more than 42 (TGI4T1(12.5 mg/kg,i.p.) = 63.1% vs. LD50 = 537 mg/kg). Moreover, the administration of B19 in combination with the PARP inhibitor Olaparib results in a significant increase of the antitumor activity in MDA-MB-231 cells relative to that of either single agent. To our knowledge, B19 is the first reported non-metal organic compound that acts as a selective CDK9-Cyclin T1 PPI inhibitor with in vivo antitumor activity, and it may be alone and in combination with PARP inhibitor Olaparib for TNBC therapy.

Targeting Protein-Protein Interactions to Inhibit Cyclin-Dependent Kinases

Cyclin-dependent kinases (CDKs) play diverse and critical roles in normal cells and may be exploited as targets in cancer therapeutic strategies. CDK4 inhibitors are currently approved for treatment in advanced breast cancer. This success has led to continued pursuit of targeting other CDKs. One challenge has been in the development of inhibitors that are highly selective for individual CDKs as the ATP-binding site is highly conserved across this family of proteins. Protein-protein interactions (PPI) tend to have less conservation amongst different proteins, even within protein families, making targeting PPI an attractive approach to improving drug selectivity. However, PPI can be challenging to target due to structural and physicochemical features of these interactions. A review of the literature specific to studies focused on targeting PPI involving CDKs 2, 4, 5, and 9 was conducted and is presented here. Promising lead molecules to target select CDKs have been discovered. None of the lead molecules discovered have led to FDA approval; however, the studies covered in this review lay the foundation for further discovery and develop of PPI inhibitors for CDKs.

Ligand- and structure-based identification of novel CDK9 inhibitors for the potential treatment of leukemia

Cyclin-dependent kinase 9 (CDK9) plays a vital role in controlling cell transcription and has been an attractive target for cancer treatment. Herein, ten predictive models derived from 1330 unique molecules against CDK9 were constructed based on molecular fingerprints and graphs using two conventional machine learning and four deep learning methods. The evaluation results showed that FP-GNN deep learning architecture performed best for CDK9 inhibitors prediction with the highest BA and F1 values of 0.681 and 0.912 for testing set. We then performed virtual screening to identify new CDK9 inhibitors by incorporating the optimal established predictive model and molecular docking. Five compounds were identified to show broad anticancer activity against various cancer cell lines through bioassays. For example, C9 exhibited antiproliferative activities against HeLa, MOLM-13 and MDA-MB-231 with IC₅₀ values of 2.53, 3.92 and 11.65 μM. Kinase inhibition assay results demonstrated that these compounds displayed submicromolar (214 ∼ 504 nM) inhibitory activities against CDK9. Further cellular mechanism evaluation revealed that C9 suppressed the activity of CDK9 and interfered with the expression of Mcl-1 and cleaved PARP in MOLM-13 cells, resulting in the induction of cellular apoptosis. In addition, C9 displayed a good stability in rat liver microsomes, artificial gastrointestinal fluid and plasm. An online platform (called DEEPCDK9Pred) was developed based on the FP-GNN models to predict or design new CDK9 inhibitors. Collectively, our findings demonstrated that FP-GNN algorithm can achieve accurate prediction of CDK9 inhibitors and the subsequent discovery of C9 as a new potential CDK9 inhibitor deserves further structural modification for the treatment of leukemia.

Inhibition of the CDK9-cyclin T1 protein-protein interaction as a new approach against triple-negative breast cancer

Cyclin-dependent kinase 9 (CDK9) activity is correlated with worse outcomes of triple-negative breast cancer (TNBC) patients. The heterodimer between CDK9 with cyclin T1 is essential for maintaining the active state of the kinase and targeting this protein–protein interaction (PPI) may offer promising avenues for selective CDK9 inhibition. Herein, we designed and generated a library of metal complexes bearing the 7-chloro-2-phenylquinoline CˆN ligand and tested their activity against the CDK9–cyclin T1 PPI. Complex 1 bound to CDK9 via an enthalpically-driven binding mode, leading to disruption of the CDK9–cyclin T1 interaction in vitro and in cellulo. Importantly, complex 1 showed promising anti-metastatic activity against TNBC allografts in mice and was comparably active compared to cisplatin. To our knowledge, 1 is the first CDK9–cyclin T1 PPI inhibitor with anti-metastatic activity against TNBC. Complex 1 could serve as a new platform for the future design of more efficacious kinase inhibitors against cancer, including TNBC.

Advances in the Treatment of Explicit Water Molecules in Docking and Binding Free Energy Calculations

Background:

The inclusion of direct effects mediated by water during the ligandreceptor recognition is a hot-topic of modern computational chemistry applied to drug discovery and development. Docking or virtual screening with explicit hydration is still debatable, despite the successful cases that have been presented in the last years. Indeed, how to select the water molecules that will be included in the docking process or how the included waters should be treated remain open questions.

Objective:

In this review, we will discuss some of the most recent methods that can be used in computational drug discovery and drug development when the effect of a single water, or of a small network of interacting waters, needs to be explicitly considered.

Results:

Here, we analyse the software to aid the selection, or to predict the position, of water molecules that are going to be explicitly considered in later docking studies. We also present software and protocols able to efficiently treat flexible water molecules during docking, including examples of applications. Finally, we discuss methods based on molecular dynamics simulations that can be used to integrate docking studies or to reliably and efficiently compute binding energies of ligands in presence of interfacial or bridging water molecules.

Conclusions:

Software applications aiding the design of new drugs that exploit water molecules, either as displaceable residues or as bridges to the receptor, are constantly being developed. Although further validation is needed, workflows that explicitly consider water will probably become a standard for computational drug discovery soon.

Overview of CDK9 as a target in cancer research

CDK9 is a protein in constant development in cancer therapy. Herein we present an overview of the enzyme as a target for cancer therapy. We provide data on its characteristics and mechanism of action. In recent years, CDK9 inhibitors that have been designed with molecular modeling have demonstrated good antitumoral activity in vitro. Clinical studies of the drugs flavopiridol, dinaciclib, seliciclib, SNS-032 and RGB-286638 used as CDK9 inhibitors are also reviewed, with their additional targets and their relative IC50 values. Unfortunately, treatment with these drugs remains unsuccessful and involves many adverse effects. We could conclude that there are many small molecules that bind to CDK9, but their lack of selectivity against other CDKs do not allow them to get to the clinical use. However, drug designers currently have the tools needed to improve the selectivity of CDK9 inhibitors and to make successful treatment available to patients.