Exploration and Comparison of the Geometrical and Physicochemical Properties of an αC Allosteric Pocket in the Structural Kinome

Strategy toward Kinase-Selective Drug Discovery

Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar kinase drug pockets, off-target inhibitor toxicity has been a major cause for clinical trial failures. The pockets are similar but not identical. Here, we describe a transformation invariant protocol to identify distinct geometric features in the drug pocket that can distinguish one kinase from all others. We integrate available experimental structures with the artificial intelligence-based structural kinome, performing a kinome-wide structural bioinformatic analysis to establish the structural principles of kinase drug selectivity. We generate the structural landscape from the experimental kinase-ligand complexes and propose a binary network that encapsulates the information. The results show that all kinases contain binary units that are shared by less than seven other kinases in the kinome. 331 kinases contain unique binary units that may distinguish them from all others. The structural features encoded by these binary units in the network represent the inhibitor-accessible geometric space that may capture the kinome-wide selectivity. Our proposed binary network with the unsupervised clustering can serve as a general structural bioinformatic protocol for extracting the distinguishing structural features for any protein from their families. We apply the binary network to epidermal growth factor receptor tyrosine kinase inhibitor selectivity by targeting the gate area and the AKT1 serine/threonine kinase selectivity by binding to the αC-helix region and the allosteric pocket. Finally, we develop the cross-platform software, KDS (Kinase Drug Selectivity), for customized visualization and analysis of the binary networks in the human kinome (https://github.com/CBIIT/KDS).

On the development of B-Raf inhibitors acting through innovative mechanisms

B-Raf is a protein kinase participating to the regulation of many biological processes in cells. Several studies have demonstrated that this protein is frequently upregulated in human cancers, especially when it bears activating mutations. In the last years, few ATP-competitive inhibitors of B-Raf have been marketed for the treatment of melanoma and are currently under clinical evaluation on a variety of other types of cancer. Although the introduction of drugs targeting B-Raf has provided significant advances in cancer treatment, responses to ATP-competitive inhibitors remain limited, mainly due to selectivity issues, side effects, narrow therapeutic windows, and the insurgence of drug resistance.

Impressive research efforts have been made so far towards the identification of novel ATP-competitive modulators with improved efficacy against cancers driven by mutant Raf monomers and dimers, some of them showing good promises. However, several limitations could still be envisioned for these compounds, according to literature data. Besides, increased attentions have arisen around approaches based on the design of allosteric modulators, polypharmacology, proteolysis targeting chimeras (PROTACs) and drug repurposing for the targeting of B-Raf proteins. The design of compounds acting through such innovative mechanisms is rather challenging. However, valuable therapeutic opportunities can be envisioned on these drugs, as they act through innovative mechanisms in which limitations typically observed for approved ATP-competitive B-Raf inhibitors are less prone to emerge. In this article, current approaches adopted for the design of non-ATP competitive inhibitors targeting B-Raf are described, discussing also on the possibilities, ligands acting through such innovative mechanisms could provide for the obtainment of more effective therapies.

Principles of Kinase Allosteric Inhibition and Pocket Validation

With several marketed drugs, allosteric inhibition of kinases has translated to pharmacological effects and clinical benefits comparable to those from orthosteric inhibition. However, despite much effort over more than 20 years, the number of kinase targets associated with FDA-approved allosteric drugs is limited, suggesting the challenges in identifying and validating allosteric inhibitors. Here we review the principles of allosteric inhibition, summarize the discovery of allosteric MEK1/2 and BCR-ABL1 inhibitors, and discuss the approaches to screening and demonstrating the functional activity of allosteric pocket ligands.

A computational approach to explore and identify potential herbal inhibitors for the p21-activated kinase 1 (PAK1)

The oncogenic kinase PAK1 (p21-activated kinase 1) is involved in developing many diseases including cancers, neurofibromatosis, Alzheimer's disease, diabetes (type 2), and hypertension. Thus, it is thought to be a prominent therapeutic target, and its selective inhibitors have a huge market potential. Recently, herbal PAK1 inhibitors have gained immense interest over synthetic ones mainly due to their non-toxic effects. Till date, many herbal compounds have been suggested to inhibit PAK1, but their information on selectivity, bioavailability, ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties, and molecular interactions with PAK1 has not been explored. Hence, this study was designed with computational approaches to explore and identify the best herbal PAK1-blockers showing good ADMET properties, druggable features and binding affinity with PAK1. Herbal inhibitors reported here were initially filtered with Lipinski's rule of five (RO5). Then, molecular docking between these inhibitors and PAK1 catalytic sites was performed using AutoDock Vina and GOLD suite to determine the binding affinity and interactions. Finally, 200 ns molecular dynamics (MD) simulations on three top-ranked inhibitors including cucurbitacin I (C-I), nymphaeol A (NA), and staurosporine (SPN) were carried out. The binding free energies and interactions revealed that NA can strongly bind with the PAK1 catalytic cleft. PASS prediction and ADMET profiling supported that NA is appeared to be a more selective and safer inhibitor than C-I and SPN. These results conform to the previous experimental evidences, and therefore, NA from Okinawa propolis could be a promising inhibitor for treating PAK1-dependent illnesses.Communicated by Ramaswamy H. Sarma.