Design Of Kinase Inhibitors Research Articles

Cocrystallization of the Src-Family Kinase Hck with the ATP-Site Inhibitor A-419259 Stabilizes an Extended Activation Loop Conformation.

Hematopoietic cell kinase (Hck) is a member of the Src kinase family and is a promising drug target in myeloid leukemias. Here, we report the crystal structure of human Hck in complex with the pyrrolopyrimidine inhibitor A-419259, determined at a resolution of 1.8 Å. This structure reveals the complete Hck active site in the presence of A-419259, including the αC-helix, the DFG motif, and the activation loop. A-419259 binds at the ATP-site of Hck and induces an overall closed conformation of the kinase with the regulatory SH3 and SH2 domains bound intramolecularly to their respective internal ligands. A-419259 stabilizes the DFG-in/αC-helix-out conformation observed previously with Hck and the pyrazolopyrimidine inhibitor PP1 (PDB: 1QCF). However, the activation loop conformations are distinct, with PP1 inducing a folded loop structure with the tyrosine autophosphorylation site (Tyr416) pointing into the ATP binding site, while A-419259 stabilizes an extended loop conformation with Tyr416 facing out into the solvent. Autophosphorylation also induces activation loop extension and significantly reduces the Hck sensitivity to PP1 but not A-419259. In cancer cells where Hck is constitutively active, the extended autophosphorylation loop may render Hck more sensitive to inhibitors like A-419259 which prefer this kinase conformation. More generally, these results provide additional insight into targeted kinase inhibitor design and how conformational preferences of inhibitors may impact selectivity and potency.

Design and activity evaluation of new EGFR tyrosine kinase inhibitors containing cyclic polyamines

The EGFR-TK pathway is pivotal in non-small-cell lung cancer (NSCLC) treatment, drugs targeting both EGFR wild-type and mutant tumor cells are still urgently needed. The focus of our study is on ATP-competitive inhibitors crucial for NSCLC therapy, specifically targeting the epidermal growth factor receptor (EGFR). A series of derivatives of Erlotinib and Icotinib were developed by incorporating a macrocyclic polyamine into a quinazoline scaffold to enhance their inhibitory activity against drug-resistant cells. The compounds exhibit modest activity against EGFR triple mutants (EGFRdel19/T790M/C797S). Compound b demonstrated slightly improved inhibition activity against PC-9del19/T790M/C797S (IC50 = 496.3 nM). This could provide some insights for optimizing EGFR inhibitors, particularly in the context of EGFR triple mutants.

Probing conformational dynamics of EGFR mutants via SEIRA spectroscopy: potential implications for tyrosine kinase inhibitor design.

Missense mutations in EGFR's catalytic domain alter its function, promoting cancer. SEIRA spectroscopy, supported by MD simulations, reveals structural differences in the compactness and hydration of helical motifs between active and inactive EGFR conformations models. These findings provide novel insights into the biophysical mechanisms driving EGFR activation and drug resistance, offering a robust method for studying emerging EGFR mutations and their structural impacts on TKIs' efficacy.

Identification of kinase inhibitors as potential host-directed therapies for intracellular bacteria

The emergence of antimicrobial resistance has created an urgent need for alternative treatments against bacterial pathogens. Here, we investigated kinase inhibitors as potential host-directed therapies (HDTs) against intracellular bacteria, specifically Salmonella Typhimurium (Stm) and Mycobacterium tuberculosis (Mtb). We screened 827 ATP-competitive kinase inhibitors with known target profiles from two Published Kinase Inhibitor Sets (PKIS1 and PKIS2) using intracellular infection models for Stm and Mtb, based on human cell lines and primary macrophages. Additionally, the in vivo safety and efficacy of the compounds were assessed using zebrafish embryo infection models. Our screen identified 11 hit compounds for Stm and 17 hit compounds for Mtb that were effective against intracellular bacteria and non-toxic for host cells. Further experiments were conducted to prioritize Stm hit compounds that were able to clear the intracellular infection in primary human macrophages. From these, two structurally related Stm hit compounds, GSK1379738A and GSK1379760A, exhibited significant activity against Stm in infected zebrafish embryos. In addition, we identified compounds that were active against intracellular Mtb, including morpholino-imidazo/triazolo-pyrimidinones that target PIK3CB, as well as 2-aminobenzimidazoles targeting ABL1. Overall, this study provided insights into kinase targets acting at the host–pathogen interface and identified several kinase inhibitors as potential HDTs.

<i>De novo</i> design and virtual screening of potential Bcr-Abl tyrosine kinase inhibitors using deep learning and molecular modeling technologies

De novo design and virtual screening of small-molecule compounds with a high potential inhibitory activity against the Bcr-Abl tyrosine kinase playing a key role in the pathogenesis of chronic myeloid leukemia (CML) were carried out by an integrated computational approach including technologies of deep learning and molecular modeling. As a result, according to the calculation data we identified 5 compounds exhibiting low values of binding free energy to the enzyme comparable with those predicted for imatinib, nilotinib and ponatinib, anticancer drugs widely used in the clinic to treat patients with CML. It was shown that these compounds are able to form stable complexes with the ATP-binding sites of the Bcr-Abl tyrosine kinase and its mutant form T315I, which is confirmed by the analysis of the profiles of binding affinity and intermolecular interactions responsible for their energy stabilization. Based on the obtained data, these compounds, which have been generated by the deep learning neural network, are assumed to form promising basic structures for development of new effective drugs for treatment of patients with CML.

What doesn't fit is made to fit: Pim-1 kinase adapts to the configuration of stilbene-based inhibitors.

Recently, we have developed novel Pim-1 kinase inhibitors starting from a dihydrobenzofuran core structure using a computational approach. Here, we report the design and synthesis of stilbene-based Pim-1 kinase inhibitors obtained by formal elimination of the dihydrofuran ring. These inhibitors of the first design cycle, which were obtained as inseparable cis/trans mixtures, showed affinities in the low single-digit micromolar range. To be able to further optimize these compounds in a structure-based fashion, we determined the X-ray structures of the protein-ligand-complexes. Surprisingly, only the cis-isomer binds upon crystallization of the cis/trans-mixture of the ligands with Pim-1 kinase and the substrate PIMTIDE, the binding mode being largely consistent with that predicted by docking. After crystallization of the exclusively trans-configured derivatives, a markedly different binding mode for the inhibitor and a concomitant rearrangement of the glycine-rich loop is observed, resulting in the ligand being deeply buried in the binding pocket.

Design, synthesis and biological evaluation of potent epidermal growth factor receptor tyrosine kinase (EGFR-TK) inhibitors against resistance mutation for lung cancer treatment

In this study, we identified a newly synthesized compound 7o with potent inhibition on EGFR primary mutants (L858R, Del19) and drug-resistant mutant T790M with nanomolar IC50 values. 7o showed strong antiproliferative effects against EGFR mutant-driven non-small cell lung cancer (NSCLC) cells such as H1975, PC-9 and HCC827, over cells expressing EGFRWT. Molecular docking was performed to investigate the possible binding modes of 7o inside the binding site of EGFRL858R/T790M and EGFRWT. Analysis of cell cycle evidenced that 7o induced cell cycle arrest in G1 phases in the EGFR mutant cells, H1975 and PC-9, which resulted in decreased S-phase populations. Moreover, compound 7o induced cancer cell apoptosis in in vitro assays. In addition, 7o inhibited cellular phosphorylation of EGFR. In vivo, oral administration of 7o caused rapid tumor regression in H1975 xenograft model. Therefore, 7o might deserve further optimization as cancer treatment agent for EGFR mutant-driven NSCLC.

Design, synthesis and biological evaluation of EGFR kinase inhibitors that spans the orthosteric and allosteric sites

Acquired drug resistance occurred in the treatment of non-small-cell lung cancer is a persistent challenge, especially in EGFR mutant type. In this study, we present design, synthesis and biological evaluation of novel quinazoline and pyrrolopyrimidine derivatives that simultaneously occupy the orthosteric and allosteric sites of EGFR. Among them, compound A-7 was confirmed as a potential EGFRL858R/T790M/C797S and EGFRDel19/T790M/C797S inhibitor. Docking study indicated that compound A-7 could simultaneously occupy two binding sites of EGFR and form three key H-bonds with the residues Met793, Lys745 and Met766 in two regions.

Molecular docking and molecular dynamics simulations reveal the clinical resistance of the gatekeeper mutation V564F of FGFR2 against Infigratinib

Fibroblast growth factor receptor 2 (FGFR2), as a transmembrane receptor tyrosine kinase, is implicated in a plethora of human cancers, including intrahepatic cholangiocarcinomas, breast cancers, and non-small cell lung cancer. The clinically relevant V564F gatekeeper mutation conferred resistance to current FGFR2 drug − Infigratinib. In this study, the protein − ligand interactions between FGFR2 kinase domain (wild-type and V564F) and Infigratinib were compared through an integrated computational method. The multiple, large-scale molecular dynamics (MD) simulations, together with dynamic cross-correlation analysis and binding free energy calculations suggested that the resistant mutation may not trigger the conformational changes of the FGFR2 kinase domain. The simulation results also indicated that the driving force to decrease the binding affinity of Infigratinib to the FGFR2 V564F variant derived from the difference in the protein − ligand hydrogen bonding interactions. Moreover, the per-residue free energy decomposition analysis revealed that the reduced contributions from several residues in the ATP-binding site of FGFR2, especially Glu565 and Ala567 located at the kinase hinge domain, were the key residues responsible for the loss of binding affinity of Infigratinib to the V564F variant. This study may offer useful information for the design of novel selective kinase inhibitors targeting FGFR2.

An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches.

Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quantitative structure-activity relationship have been applied to the design and optimization of small molecule kinase inhibitors. In this review, we provide an overview of recent advances in CADD and SMKIs and the application of CADD in the discovery of SMKIs.

Development of Kinase-Centric Drugs: A Computational Perspective.

Kinases are prominent drug targets in the pharmaceutical and research community due to their involvement in signal transduction, physiological responses, and upon dysregulation, in diseases such as cancer, neurological and autoimmune disorders. Several FDA-approved small-molecule drugs have been developed to combat human diseases since Gleevec was approved for the treatment of chronic myelogenous leukemia. Kinases were considered "undruggable" in the beginning. Several FDA-approved small-molecule drugs have become available in recent years. Most of these drugs target ATP-binding sites, but a few target allosteric sites. Among kinases that belong to the same family, the catalytic domain shows high structural and sequence conservation. Inhibitors of ATP-binding sites can cause off-target binding. Because members of the same family have similar sequences and structural patterns, often complex relationships between kinases and inhibitors are observed. To design and develop drugs with desired selectivity, it is essential to understand the target selectivity for kinase inhibitors. To create new inhibitors with the desired selectivity, several experimental methods have been designed to profile the kinase selectivity of small molecules. Experimental approaches are often expensive, laborious, time-consuming, and limited by the available kinases. Researchers have used computational methodologies to address these limitations in the design and development of effective therapeutics. Many computational methods have been developed over the last few decades, either to complement experimental findings or to forecast kinase inhibitor activity and selectivity. The purpose of this review is to provide insight into recent advances in theoretical/computational approaches for the design of new kinase inhibitors with the desired selectivity and optimization of existing inhibitors.

Unveiling the Selectivity Mechanism of Type-I LRRK2 Inhibitors by Computational Methods: Insights from Binding Thermodynamics and Kinetics Simulation.

Understanding the selectivity mechanisms of inhibitors toward highly similar proteins is very important in new drug discovery. Developing highly selective targeting of leucine-rich repeat kinase 2 (LRRK2) kinases for the treatment of Parkinson's disease (PD) is challenging because of the similarity of the kinase ATP binding pocket. During the development of LRRK2 inhibitors, off-target effects on other kinases, especially TTK and JAK2 kinases, have been observed. As a result, significant time and resources have been devoted to improving the selectivity for the LRRK2 target. DNL201 is an LRRK2 kinase inhibitor entering phase I clinical studies. The experiments have shown that DNL201 significantly inhibits LRRK2 kinase activity, with >167-fold selectivity over JAK2 and TTK kinases. However, the potential mechanisms of inhibitor preferential binding to LRRK2 kinase are still not well elucidated. In this work, to reveal the underlying general selectivity mechanism, we carried out several computational methods and comprehensive analyses from both the binding thermodynamics and kinetics on two representative LRRK2 inhibitors (DNL201 and GNE7915) to LRRK2. Our results suggest that the structural and kinetic differences between the proteins may play a key role in determining the activity of the selective small-molecule inhibitor. The selectivity mechanisms proposed in this work could be helpful for the rational design of novel selective LRRK2 kinase inhibitors against PD.

Imidazole-4-N-acetamide Derivatives as a Novel Scaffold for Selective Targeting of Cyclin Dependent Kinases.

The rational design of cyclin-dependent protein kinase (CDK) inhibitors presumes the development of approaches for accurate prediction of selectivity and the activity of small molecular weight anticancer drug candidates. Aiming at attenuation of general toxicity of low selectivity compounds, we herein explored the new chemotype of imidazole-4-N-acetamide substituted derivatives of the pan-CDK inhibitor PHA-793887. Newly synthesized compounds 1-4 containing an aliphatic methyl group or aromatic radicals at the periphery of the scaffold were analyzed for the prediction of relative free energies of binding to CDK1, -2, -5, and -9 using a protocol based on non-equilibrium (NEQ) thermodynamics. This methodology allows for the demonstration of a good correlation between the calculated parameters of interaction of 1-4 with individual targets and the values of inhibitory potencies in in vitro kinase assays. We provide evidence in support of NEQ thermodynamics as a time sparing, precise, and productive approach for generating chemical inhibitors of clinically relevant anticancer targets.

An industrial evaluation of proteochemometric modelling: Predicting drug-target affinities for kinases

Deep learning proteochemometric (PCM) models have been reported to achieve excellent performances on public benchmarking datasets. Nevertheless, numerous papers have cast doubt on commonly used evaluation metrics, suggesting they do not reflect true prospective predictive abilities. The aim of this study is to provide a comprehensive assessment of performance of a state-of-the-art PCM model on proprietary data and evaluate its potential over other modelling approaches as a virtual screening tool for kinase inhibitors. Whilst the model has been shown to achieve an RMSE of 0.48 on a public benchmarking dataset, an impaired overall performance was observed for the proprietary dataset in this study, with an RMSE of 0.85 and a Pearson Correlation Coefficient of 0.65 using a temporal splitting strategy. We hypothesise that the more limited performance can be in part attributed to a shift in the chemical space observed over time in an industrial setting, which is not considered by the more lenient random ligand splitting strategy, more commonly used on benchmarking datasets. The overall performance of the PCM model was statistically similar to a multitask model and only slightly superior to a KNN and random forest PCM model. A comprehensive analysis of performance was performed to capture the key challenges faced in the design of competitive kinase inhibitors, which revealed the key limitations of PCM modelling. For example, the model showed poor predictive abilities for understudied targets, and a limited ability to assess ligand selectivity and promiscuity, with no improved performance over a multitask model or a random forest PCM model. Overall, these findings reveal that the PCM model assessed in this study does not provide significant benefits over less complex models such as multitask model or a random forest PCM model as a virtual screening tool for kinase inhibitors in an industrial setting. Taken together, this study highlights the need for more robust evaluations of PCM models by using stricter splitting strategies, more extensive benchmarking and more comprehensive performance analysis beyond traditional metrics.

Rational Design of Covalent Kinase Inhibitors by an Integrated Computational Workflow (Kin-Cov).

Covalent kinase inhibitors (CKIs) hold great promise for drug development. However, examples of computationally guided design of CKIs are still scarce. Here, we present an integrated computational workflow (Kin-Cov) for rational design of CKIs. The design of the first covalent leucine-zipper and sterile-α motif kinase (ZAK) inhibitor was presented as an example to showcase the power of computational workflow for CKI design. The two representative compounds, 7 and 8, inhibited ZAK kinase with half-maximal inhibitory concentration (IC50) values of 9.1 and 11.5 nM, respectively. Compound 8 displayed an excellent ZAK target specificity in Kinome profiling against 378 wild-type kinases. Structural biology and cell-based Western blot washout assays validated the irreversible binding characteristics of the compounds. Our study presents a rational approach for the design of CKIs based on the reactivity and accessibility of nucleophilic amino acid residues in a kinase. The workflow is generalizable and can be applied to facilitate CKI-based drug design.

Structural Mass Spectrometry Probes the Inhibitor-Induced Allosteric Activation of CDK12/CDK13-Cyclin K Dissociation.

The rational design and development of effective inhibitors for cyclin-dependent kinases 12 and 13 (CDK12 and CDK13) are largely dependent on the understanding of the dynamic inhibition conformations but are difficult to be achieved by conventional characterization tools. Herein, we integrate the structural mass spectrometry (MS) methods of lysine reactivity profiling (LRP) and native MS (nMS) to systematically interrogate both the dynamic molecular interactions and overall protein assembly of CDK12/CDK13-cyclin K (CycK) complexes under the modulation of small molecule inhibitors. The essential structure insights, including inhibitor binding pocket, binding strength, interfacial molecular details, and dynamic conformation changes, can be derived from the complementary results of LRP and nMS. We find the inhibitor SR-4835 binding can greatly destabilize the CDK12/CDK13-CycK interactions in an unusual allosteric activation way, thereby providing a novel alternative for the kinase activity inhibition. Our results underscore the great potential of LRP combination with nMS for the evaluation and rational design of effective kinase inhibitors at the molecular level.

Covalent Inhibition by a Natural Product-Inspired Latent Electrophile.

Strategies to target specific protein cysteines are critical to covalent probe and drug discovery. 3-Bromo-4,5-dihydroisoxazole (BDHI) is a natural product-inspired, synthetically accessible electrophilic moiety that has previously been shown to react with nucleophilic cysteines in the active site of purified enzymes. Here, we define the global cysteine reactivity and selectivity of a set of BDHI-functionalized chemical fragments using competitive chemoproteomic profiling methods. Our study demonstrates that BDHIs capably engage reactive cysteine residues in the human proteome and the selectivity landscape of cysteines liganded by BDHI is distinct from that of haloacetamide electrophiles. Given its tempered reactivity, BDHIs showed restricted, selective engagement with proteins driven by interactions between a tunable binding element and the complementary protein sites. We validate that BDHI forms covalent conjugates with glutathione S-transferase Pi (GSTP1) and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1), emerging anticancer targets. BDHI electrophile was further exploited in Bruton's tyrosine kinase (BTK) inhibitor design using a single-step late-stage installation of the warhead onto acrylamide-containing compounds. Together, this study expands the spectrum of optimizable chemical tools for covalent ligand discovery and highlights the utility of 3-bromo-4,5-dihydroisoxazole as a cysteine-reactive electrophile.

BET Bromodomain Inhibitors: Novel Design Strategies and Therapeutic Applications

The mammalian bromodomain and extra-terminal domain (BET) family of proteins consists of four conserved members (Brd2, Brd3, Brd4, and Brdt) that regulate numerous cancer-related and immunity-associated genes. They are epigenetic readers of histone acetylation with broad specificity. BET proteins are linked to cancer progression due to their interaction with numerous cellular proteins including chromatin-modifying factors, transcription factors, and histone modification enzymes. The spectacular growth in the clinical development of small-molecule BET inhibitors underscores the interest and importance of this protein family as an anticancer target. Current approaches targeting BET proteins for cancer therapy rely on acetylation mimics to block the bromodomains from binding chromatin. However, bromodomain-targeted agents are suffering from dose-limiting toxicities because of their effects on other bromodomain-containing proteins. In this review, we provided an updated summary about the evolution of small-molecule BET inhibitors. The design of bivalent BET inhibitors, kinase and BET dual inhibitors, BET protein proteolysis-targeting chimeras (PROTACs), and Brd4-selective inhibitors are discussed. The novel strategy of targeting the unique C-terminal extra-terminal (ET) domain of BET proteins and its therapeutic significance will also be highlighted. Apart from single agent treatment alone, BET inhibitors have also been combined with other chemotherapeutic modalities for cancer treatment demonstrating favorable clinical outcomes. The investigation of specific biomarkers for predicting the efficacy and resistance of BET inhibitors is needed to fully realize their therapeutic potential in the clinical setting.

Structural Analysis of Interactions between Epidermal Growth Factor Receptor (EGFR) Mutants and Their Inhibitors

People’s lives and health are gravely threatened by non-small-cell lung cancer (NSCLC). Mutations in epidermal growth factor receptor (EGFR), a transmembrane receptor tyrosine kinase, are considered one of the causes of NSCLC. Tyrosine kinase inhibitors (TKIs) are typically used to treat patients with EGFR mutations. In this study, Gefitinib, a member of the first generation of TKIs, was used to treat an EGFR single-point mutation (single mutant, SM). Patients harboring additional T790M mutations in the kinase domain of the EGFR were resistant to Gefitinib. Then, the L858R/T790M double mutation (double mutant, DM) was treated with the second generation of TKIs, such as Afatinib. Here, we constructed four computational models to uncover the structural basis between EGFR mutants (SM and DM) and corresponding inhibitors (Gefitinib and Afatinib). The binding energy in the G-SM (representing Gefitinib in complex with SM) system was larger than that in the G-DM (Representing Gefitinib in complex with DM) system. Gefitinib’s affinity with L792 and M793 was drastically reduced by the longer side chain of M790 in the G-DM system, which pushed Gefitinib outside of the pocket. Additionally, the A-DM system’s binding energy was higher than the G-DM system’s. Afatinib, unlike Gefitinib, induced the P-loop region to move downwards to decrease the pocket entrance size to accommodate Afatinib properly and stably in the A-DM (Afatinib in complex with DM) system. These results uncover the details of interactions between EGFR and its inhibitors and shed light on the design of new tyrosine kinase inhibitors.

In Silico study and design of some new potent threonine tyrosine kinase inhibitors using molecular docking simulation

ABSTRACT Threonine tyrosine kinase (TTK) is one of the most important members of kinase enzymes and has a major role in the phosphorylation of threonine and tyrosine amino acids in proteins. TTK can cause some important diseases, such as Alzheimer, cancers and cardio diseases. Nowadays, In Silico study and evaluation are applied through virtual screening tools, such as molecular docking simulations and predictions of ADMET-related properties to investigate new potent inhibitors of this target protein. The molecular docking simulation is performed to achieve the best binding affinity and docking scores. This is done by comparison between the standard inhibitor and high-scoring selected ligands. After evaluation of Molecular docking results and ADMET related properties, N-(cyclopropylmethyl)-5-(4-methylphenyl)imidazo[1,2-a]pyrazin-8-amine (L5 table 1), 3-[4-[1-(cyclopropylamino)ethenyl]phenyl]-N-(2-methylpropyl)imidazo[1,2-a]pyrazin-8-amine (L2 table 1), (Z)-1-[(E)-[(Z)-1-[7-(aminomethyl)-2-(4-methylphenyl)imidazo[1,2-a]pyridin-3-yl]but-2-enylidene]amino]-N-(cyclopropylmethyl)prop-1-en-1-amine were indicated as new TTK potent inhibitors.