Targeting the cancer kinome through polypharmacology

Kinase Drug Discovery: Impact of Open Science and Artificial Intelligence

Given their central role in signal transduction, protein kinases (PKs) were first implicated in cancer development, caused by aberrant intracellular signaling events. Since then, PKs have become major targets in different therapeutic areas. The preferred approach to therapeutic intervention of PK-dependent diseases is the use of small molecules to inhibit their catalytic phosphate group transfer activity. PK inhibitors (PKIs) are among the most intensely pursued drug candidates, with currently 80 approved compounds and several hundred in clinical trials. Following the elucidation of the human kinome and development of robust PK expression systems and high-throughput assays, large volumes of PK/PKI data have been produced in industrial and academic environments, more so than for many other pharmaceutical targets. In addition, hundreds of X-ray structures of PKs and their complexes with PKIs have been reported. Substantial amounts of PK/PKI data have been made publicly available in part as a result of open science initiatives. PK drug discovery is further supported through the incorporation of data science approaches, including the development of various specialized databases and online resources. Compound and activity data wealth compared to other targets has also made PKs a focal point for the application of artificial intelligence (AI) in pharmaceutical research. Herein, we discuss the interplay of open and data science in PK drug discovery and review exemplary studies that have substantially contributed to its development, including kinome profiling or the analysis of PKI promiscuity versus selectivity. We also take a close look at how AI approaches are beginning to impact PK drug discovery in light of their increasing data orientation.

Small molecules for impairing endoplasmic reticulum in cancer

The endoplasmic reticulum plays an important role in maintaining the protein homeostasis of cells as well as regulating Ca2+ storage. An increased load of unfolded proteins in the endoplasmic reticulum due to alterations in the cell's metabolic pathway leads to the activation of the unfolded protein response, also known as ER stress. ER stress plays a major role in maintaining the growth and survival of various cancer cells, but persistent ER stress can also lead to cell death and hence can be a therapeutic pathway in the treatment of cancer. In this review, we focus on different types of small molecules that impair different ER stress sensors, the protein degradation machinery, and chaperone proteins. We also review the metal complexes and other miscellaneous compounds inducing ER stress through multiple mechanisms. Finally, we discuss the challenges in this emerging area of research and the potential direction of research to overcome them towards next-generation ER-targeted cancer therapy.

Discovery of Thioether-Cyclized Macrocyclic Covalent Inhibitors by mRNA Display

Macrocyclic peptides are promising scaffolds for the covalent ligand discovery. However, platforms enabling the direct identification of covalent macrocyclic ligands in a high-throughput manner are limited. In this study, we present an mRNA display platform allowing selection of covalent macrocyclic inhibitors using 1,3-dibromoacetone-vinyl sulfone (DBA-VS). Testcase selections on TEV protease resulted in potent covalent inhibitors with diverse cyclic structures, among which cTEV6-2, a macrocyclic peptide with a unique C-terminal cyclization, emerged as the most potent covalent inhibitor of TEV protease described to-date. This study outlines the workflow for integrating chemical functionalization─installation of a covalent warhead─with mRNA display and showcases its application in targeted covalent ligand discovery.

Targeted ferritinophagy in gastrointestinal cancer: from molecular mechanisms to implications

Gastrointestinal cancer is a significant global health burden, necessitating the development of novel therapeutic strategies. Emerging evidence has highlighted the potential of targeting ferritinophagy as a promising approach for the treatment of gastrointestinal cancer. Ferritinophagy is a form of selective autophagy that is mediated by the nuclear receptor coactivator 4 (NCOA4). This process plays a crucial role in regulating cellular iron homeostasis and has been implicated in various pathological conditions, including cancer. This review discusses the molecular mechanisms underlying ferritinophagy and its relevance to gastrointestinal cancer. Furthermore, we highlight the potential therapeutic implications of targeting ferritinophagy in gastrointestinal cancer. Several approaches have been proposed to modulate ferritinophagy, including small molecule inhibitors and immunotherapeutic strategies. We discuss the advantages and challenges associated with these therapeutic interventions and provide insights into their potential clinical applications.

Design of a covalent protein-protein interaction inhibitor of SRPKs to suppress angiogenesis and invasion of cancer cells

Serine-arginine (SR) proteins are splicing factors that play essential roles in both constitutive and alternative pre-mRNA splicing. Phosphorylation of their C-terminal RS domains by SR protein kinases (SRPKs) regulates their localization and diverse cellular activities. Dysregulation of phosphorylation has been implicated in many human diseases, including cancers. Here, we report the development of a covalent protein-protein interaction inhibitor, C-DBS, that targets a lysine residue within the SRPK-specific docking groove to block the interaction and phosphorylation of the prototypic SR protein SRSF1. C-DBS exhibits high specificity and conjugation efficiency both in vitro and in cellulo. This self-cell-penetrating inhibitor attenuates the phosphorylation of endogenous SR proteins and subsequently inhibits the angiogenesis, migration, and invasion of cancer cells. These findings provide a new foundation for the development of covalent SRPK inhibitors for combatting diseases such as cancer and viral infections and overcoming the resistance encountered by ATP-competitive inhibitors.

Systematic Investigation of Dual-Target-Directed Ligands

Multitarget-directed ligands (MTDLs) are compounds rationally designed to affect multiple targets, aiming for a better therapeutic profile. For over 20 years, MTDLs have garnered increasing attention, the idea being that their full potential would have been achieved, thanks to unprecedented target combinations and advanced medicinal chemistry strategies. This study presents a literature mining effort resulting in a data set of dual-target-directed ligands (DTDLs), the fundamental example of MTDLs. We used this data set to evaluate the rationale behind target selection and the chemical novelty of DTDLs targeting specific protein combinations. Our analysis focused on DTDL targets in terms of biological function, disease association, structure, and chemogenomic traits. We also compared DTDLs with single-target compounds. We found that well-known target pathology associations often guide DTDL design, leveraging existing chemical scaffolds and binding pocket similarities. These findings highlight the current state of the field and suggest substantial untapped potential for rational polypharmacology.

Biomaterials for Targeting Endoplasmic Reticulum in Cancer

Endoplasmic reticulum (ER) is one of the most important sub-cellular organelles which controls myriads of biological functions including protein biosynthesis with proper functional folded form, protein misfolding, protein transport into Golgi body for secretion, Ca2+ homeostasis and so on. Subsequently, dysregulation in ER function leads to ER stress followed by disease pathology like cancer. Hence, targeting ER in the cancer cells emerged as one of the futuristic strategies for cancer treatment. However, the major challenge is to selectively and specifically target ER in the sub-cellular milieu in the cancer tissues, due to the lack of ER targeting chemical moieties to recognize the ER markers. To address this, in the last decade, numerous biomaterials were explored to selectively impair and image ER in cancer cells to induce ER stress. This review outlines those biomaterials which consists of carbon and silicon materials, lipid nanoparticles (liposomes and micelles), supramolecular self-assembled nanostructures, cell membrane-coated nanoparticles and metallic nanoparticles. Moreover, we also discuss the challenges and possible solutions of this promising field to usher the readers towards next-generation ER targeted cancer therapy.

De novo generation of multi-target compounds using deep generative chemistry

Polypharmacology drugs-compounds that inhibit multiple proteins-have many applications but are difficult to design. To address this challenge we have developed POLYGON, an approach to polypharmacology based on generative reinforcement learning. POLYGON embeds chemical space and iteratively samples it to generate new molecular structures; these are rewarded by the predicted ability to inhibit each of two protein targets and by drug-likeness and ease-of-synthesis. In binding data for >100,000 compounds, POLYGON correctly recognizes polypharmacology interactions with 82.5% accuracy. We subsequently generate de-novo compounds targeting ten pairs of proteins with documented co-dependency. Docking analysis indicates that top structures bind their two targets with low free energies and similar 3D orientations to canonical single-protein inhibitors. We synthesize 32 compounds targeting MEK1 and mTOR, with most yielding >50% reduction in each protein activity and in cell viability when dosed at 1-10 μM. These results support the potential of generative modeling for polypharmacology.

Data-oriented protein kinase drug discovery

The continued growth of data from biological screening and medicinal chemistry provides opportunities for data-driven experimental design and decision making in early-phase drug discovery. Approaches adopted from data science help to integrate internal and public domain data and extract knowledge from historical in-house data. Protein kinase (PK) drug discovery is an exemplary area where large amounts of data are accumulating, providing a valuable knowledge base for discovery projects. Herein, the evolution of PK drug discovery and development of small molecular PK inhibitors (PKIs) is reviewed, highlighting milestone developments in the field and discussing exemplary studies providing a basis for increasing data orientation of PK discovery efforts.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Design, synthesis, and evaluation of dual EGFR/AURKB inhibitors as anticancer agents for non-small cell lung cancer

The epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are first-line agents for mutant EGFR-positive (mEGFR+) NSCLC. However, secondary resistant mutations develop following therapy that prevent EGFR-TKI binding. The EGFR-TKIs are rendered ineffective in NSCLC expressing EGFR resistant mutations (rmEGFR+). Mutations in Kirsten rat sarcoma virus protein (mKRAS) support persistent signaling downstream of EGFR regardless of EGFR-TKI earlier in the signaling cascade. The EGFR-TKIs are ineffective in mKRAS+ NSCLC. Thus, newer anticancer agents are needed for rmEGFR+ and mKRAS+ NSCLC. Aurora kinase B (AURKB) is a mitosis related kinase that is overexpressed in NSCLC and supports cancer cell proliferation and survival. Literature reports have suggested that AURKB inhibitors if given concurrently with an EGFR-TKI could overcome EGFR-TKI resistance in mKRAS+ NSCLC and rmEGFR + NSCLC, and showed improved anticancer effects compared to current single-targeted EGFR-TKIs. Molecular modeling was used to identify similarities between the kinase pockets of EGFR and AURKB. An overlap was observed for the inactive conformation of EGFR and the active conformation of AURKB. Compounds 3-7 were synthesized as dual EGFR/AURKB inhibitors for mKRAS+ and rmEGFR+ NSCLC. Compounds 5, 6 and 7 were identified as dual EGFR/AURKB inhibitors. Compound 5 demonstrated modest micromolar inhibition of rmEGFR+ NSCLC. All investigated compounds showed moderate inhibition of mKRAS+ NSCLC cells. Compound 7 demonstrated single-digit micromolar inhibition of mKRAS+ NSCLC.

Revisiting Aurora Kinase B: A promising therapeutic target for cancer therapy

Cancer continues to be a major health concern globally, although the advent of targeted therapy has revolutionized treatment options. Aurora Kinase B is a serine-threonine kinase that has been explored as an oncology therapeutic target for more than two decades. Aurora Kinase B inhibitors show promising biological results in in-vitro and in-vivo experiments. However, there are no inhibitors approved yet for clinical use, primarily because of the side effects associated with Aurora B inhibitors. Several studies demonstrate that Aurora B inhibitors show excellent synergy with various chemotherapeutic agents, radiation therapy, and targeted therapies. This makes it an excellent choice as an adjuvant therapy to first-line therapies, which greatly improves the therapeutic window and side effect profile. Recent studies indicate the role of Aurora B in some deadly cancers with limited therapeutic options, like triple-negative breast cancer and glioblastoma. Herein, we review the latest developments in Aurora Kinase B targeted research, with emphasis on its potential as an adjuvant therapy and its role in some of the most difficult-to-treat cancers.

A novel flavonol-polysaccharide from Tamarix chinensis alleviates influenza A virus-induced acute lung injury. Evidences for its mechanism of action

BACKGROUND

Tamarix chinensis Lour. is a Chinese medicine used for treating inflammation-related diseases and its crude polysaccharides (MBAP90) exhibited significant anticomplement activities in vitro.

PURPOSE

To obtain anticomplement homogenous polysaccharides from MBAP90 and explore its therapeutic effects and potential mechanism on influenza A virus (IAV)-induced acute lung injury (ALI).

METHODS

Anticomplement activity-guided fractionation of the water-soluble crude polysaccharides from the leaves and twigs of T. chinensis were performed by diethylaminoethyl-52 (DEAE-52) cellulose and gel permeation columns to yield a homogeneous polysaccharide MBAP-5, which was further characterized using ultra-high-performance liquid chromatography-ion trap tandem mass spectrometry (UPLC-IT-MS) and nuclear magnetic resonance (NMR) analysis. In vitro, the anticomplement activity of MBAP-5 through classical pathway was measured using a hemolytic test. The therapeutic effects of MBAP-5 on ALI were evaluated in H1N1-infected mice. H&E staining, enzyme linked immunosorbent assay (ELISA), immunohistochemistry, and western blot were used to systematically access lung histomorphology, inflammatory cytokines, degree of complement component 3c, 5aR, and 5b-9 (C3c, C5aR, and C5b-9) deposition, and inflammasome signaling pathway protein expressions in lung tissues.

RESULTS

MBAP-5 was a novel flavonol-polysaccharide with the molecular weight (Mw) of 153.6 kDa. Its structure was characterized to process a backbone of →4)-α-D-GlcpA-(1→, →6)-α-D-Glcp-(1→, →3,4)-α-D-Glcp-(1→, →3,4,6)-α-D-Glcp-(1→, and →4,6)-β-D-Glcp-(1→, as well as branches of α-L-Araf-(1→ and β-D-Galp-(1→. Particularly, O-3 of →3,4,6)-α-D-Glcp-(1→ was substituted by quercetin. In vitro assay showed that MBAP-5 had a potent anticomplement activity with a CH50 value of 102 ± 4 µg/ml. Oral administration of MBAP-5 (50 and 100 mg/kg) effectively attenuated the H1N1-induced pulmonary injury in vivo by reducing pulmonary edema, virus replication, and inflammatory responses. Mechanistically, MBAP-5 inhibited the striking deposition and contents of complement activation products (C3c, C5aR, and C5b-9) in the lung. Toll-like receptor 4 (TLR4) /transcription factor nuclear factor κB (NF-κB) signaling pathway was constrained by MBAP-5 treatment. In addition, MBAP-5 could suppress activation of the inflammasome pathways, including Nod-like receptor pyrin domain 3 (NLRP3), cysteinyl aspartate specific proteinase-1/12 (caspase-1/12), apoptosis‑associated speck‑like protein (ASC), gasdermin D (GSDMD), interleukin (IL)-1β, and IL-18 expressions.

CONCLUSIONS

A novel flavonol-polysaccharide MBAP-5 isolated from T. chinensis demonstrated a therapeutic effect against ALI induced by IAV attack. The mechanism might be associated with inhibition of complement system and inflammasome pathways activation.

Comprehensive Data-Driven Assessment of Non-Kinase Targets of Inhibitors of the Human Kinome

Protein kinases (PKs) are involved in many intracellular signal transduction pathways through phosphorylation cascades and have become intensely investigated pharmaceutical targets over the past two decades. Inhibition of PKs using small-molecular inhibitors is a premier strategy for the treatment of diseases in different therapeutic areas that are caused by uncontrolled PK-mediated phosphorylation and aberrant signaling. Most PK inhibitors (PKIs) are directed against the ATP cofactor binding site that is largely conserved across the human kinome comprising 518 wild-type PKs (and many mutant forms). Hence, these PKIs often have varying degrees of multi-PK activity (promiscuity) that is also influenced by factors such as single-site mutations in the cofactor binding region, compound binding kinetics, and residence times. The promiscuity of PKIs is often-but not always-critically important for therapeutic efficacy through polypharmacology. Various in vitro and in vivo studies have also indicated that PKIs have the potential of interacting with additional targets other than PKs, and different secondary cellular targets of individual PKIs have been identified on a case-by-case basis. Given the strong interest in PKs as drug targets, a wealth of PKIs from medicinal chemistry and their activity data from many assays and biological screens have become publicly available over the years. On the basis of these data, for the first time, we conducted a systematic search for non-PK targets of PKIs across the human kinome. Starting from a pool of more than 155,000 curated human PKIs, our large-scale analysis confirmed secondary targets from diverse protein classes for 447 PKIs on the basis of high-confidence activity data. These PKIs were active against 390 human PKs, covering all kinase groups of the kinome and 210 non-PK targets, which included other popular pharmaceutical targets as well as currently unclassified proteins. The target distribution and promiscuity of the 447 PKIs were determined, and different interaction profiles with PK and non-PK targets were identified. As a part of our study, the collection of PKIs with activity against non-PK targets and the associated information are made freely available.

All the mutations that are fit to die

In this issue of Cell Chemical Biology, Chakraborty et al.1 employ a deep mutational screening analysis of 3,500 single point mutations in every residue in Src kinase's catalytic domain to determine which residues are critical for conferring ATP-competitive inhibitor resistance. They identify a dynamically controlled resistance site.

AI for targeted polypharmacology: The next frontier in drug discovery

In drug discovery, targeted polypharmacology, i.e., targeting multiple molecular targets with a single drug, is redefining therapeutic design to address complex diseases. Pre-selected pharmacological profiles, as exemplified in kinase drugs, promise enhanced efficacy and reduced toxicity. Historically, many of such drugs were discovered serendipitously, limiting predictability and efficacy, but currently artificial intelligence (AI) offers a transformative solution. Machine learning and deep learning techniques enable modeling protein structures, generating novel compounds, and decoding their polypharmacological effects, opening an avenue for more systematic and predictive multi-target drug design. This review explores the use of AI in identifying synergistic co-targets and delineating them from anti-targets that lead to adverse effects, and then discusses advances in AI-enabled docking, generative chemistry, and proteochemometric modeling of proteome-wide compound interactions, in the context of polypharmacology. We also provide insights into challenges ahead.

HDAC specificity and kinase off-targeting by purine-benzohydroxamate anti-hematological tumor agents

A series of hybrid inhibitors, combining pharmacophores of known kinase inhibitors bearing anilino-purines (ruxolitinib, ibrutinib) and benzohydroxamate HDAC inhibitors (nexturastat A), were generated in the present study. The compounds have been synthesized and tested against solid and hematological tumor cell lines. Compounds 4d-f were the most promising in cytotoxicity assays (IC50 ≤ 50 nM) vs. hematological cells and displayed moderate activity in solid tumor models (EC50 = 9.3-21.7 μM). Compound 4d potently inhibited multiple kinase targets of interest for anticancer effects, including JAK2, JAK3, HDAC1, and HDAC6. Molecular dynamics simulations showed that 4d has stable interactions with HDAC and members of the JAK family, with differences in the hinge binding energy conferring selectivity for JAK3 and JAK2 over JAK1. The kinase inhibition profile of compounds 4d-f allows selective cytotoxicity, with minimal effects on non-tumorigenic cells. Moreover, these compounds have favorable pharmacokinetic profiles, with high stability in human liver microsomes (e.g., see t1/2: >120 min for 4f), low intrinsic clearance, and lack of significant inhibition of four major CYP450 isoforms.

Pharmacological approaches to understanding protein kinase signaling networks

Protein kinases play vital roles in controlling cell behavior, and an array of kinase inhibitors are used successfully for treatment of disease. Typical drug development pipelines involve biological studies to validate a protein kinase target, followed by the identification of small molecules that effectively inhibit this target in cells, animal models, and patients. However, it is clear that protein kinases operate within complex signaling networks. These networks increase the resilience of signaling pathways, which can render cells relatively insensitive to inhibition of a single kinase, and provide the potential for pathway rewiring, which can result in resistance to therapy. It is therefore vital to understand the properties of kinase signaling networks in health and disease so that we can design effective multi-targeted drugs or combinations of drugs. Here, we outline how pharmacological and chemo-genetic approaches can contribute to such knowledge, despite the known low selectivity of many kinase inhibitors. We discuss how detailed profiling of target engagement by kinase inhibitors can underpin these studies; how chemical probes can be used to uncover kinase-substrate relationships, and how these tools can be used to gain insight into the configuration and function of kinase signaling networks.

The combination of PAC-1 and entrectinib for the treatment of metastatic uveal melanoma

The treatment of metastatic uveal melanoma remains a major clinical challenge. Procaspase-3, a proapoptotic protein and precursor to the key apoptotic executioner caspase-3, is overexpressed in a wide range of malignancies, and the drug PAC-1 leverages this overexpression to selectively kill cancer cells. Herein, we investigate the efficacy of PAC-1 against uveal melanoma cell lines and report the synergistic combination of PAC-1 and entrectinib. This preclinical activity, tolerability data in mice, and the known clinical effectiveness of these drugs in human cancer patients led to a small Phase 1b study in patients with metastatic uveal melanoma. The combination of PAC-1 and entrectinib was tolerated with no treatment-related grade ≥3 toxicities in these patients. The pharmacokinetics of entrectinib were not affected by PAC-1 treatment. In this small and heavily pretreated initial cohort, stable disease was observed in four out of six patients, with a median progression-free survival of 3.38 months (95% CI 1.6-6.5 months). This study is an initial demonstration that the combination of PAC-1 and entrectinib may warrant further clinical investigation. Clinical trial registration: Clinical Trials.gov: NCT04589832.

An insight into the structure-activity relationship studies of anticancer medicinal attributes of 7-azaindole derivatives: a review

In the current portfolio, there is a lot of interest in the 7-azaindole building block for drug discovery. The creation of synthetic, sophisticated methods for the modification of 7-azaindoles is a promising area of research. This review covers the structure-activity relationship of 7-azaindole analogs, which have been shown to be effective anticancer agents in the literature of the past two decades. Positions 1, 3 and 5 of the 7-azaindole ring are the most active sites. Disubstitution is used for the synthesis of a new analog of the 7-azaindole moiety. All positions are used to create novel molecules that are effective anticancer agents. The alkyl, aryl carboxamide group and heterocyclic ring are the most successful types of substitution.

Anticancer pan-ErbB inhibitors reduce inflammation and tissue injury and exert broad-spectrum antiviral effects

Targeting host factors exploited by multiple viruses could offer broad-spectrum solutions for pandemic preparedness. Seventeen candidates targeting diverse functions emerged in a screen of 4,413 compounds for SARS-CoV-2 inhibitors. We demonstrated that lapatinib and other approved inhibitors of the ErbB family of receptor tyrosine kinases suppress replication of SARS-CoV-2, Venezuelan equine encephalitis virus (VEEV), and other emerging viruses with a high barrier to resistance. Lapatinib suppressed SARS-CoV-2 entry and later stages of the viral life cycle and showed synergistic effect with the direct-acting antiviral nirmatrelvir. We discovered that ErbB1, ErbB2, and ErbB4 bind SARS-CoV-2 S1 protein and regulate viral and ACE2 internalization, and they are required for VEEV infection. In human lung organoids, lapatinib protected from SARS-CoV-2-induced activation of ErbB-regulated pathways implicated in non-infectious lung injury, proinflammatory cytokine production, and epithelial barrier injury. Lapatinib suppressed VEEV replication, cytokine production, and disruption of blood-brain barrier integrity in microfluidics-based human neurovascular units, and reduced mortality in a lethal infection murine model. We validated lapatinib-mediated inhibition of ErbB activity as an important mechanism of antiviral action. These findings reveal regulation of viral replication, inflammation, and tissue injury via ErbBs and establish a proof of principle for a repurposed, ErbB-targeted approach to combat emerging viruses.

Drosophila Screening Identifies Dual Inhibition of MEK and AURKB as an Effective Therapy for Pancreatic Ductal Adenocarcinoma

Significant progress has been made in understanding the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) by generating and using murine models. To accelerate drug discovery by identifying novel therapeutic targets on a systemic level, here we generated a Drosophila model mimicking the genetic signature in PDAC (KRAS, TP53, CDKN2A, and SMAD4 alterations), which is associated with the worst prognosis in patients. The '4-hit' flies displayed epithelial transformation and decreased survival. Comprehensive genetic screening of their entire kinome revealed kinases including MEK and AURKB as therapeutic targets. Consistently, a combination of the MEK inhibitor trametinib and the AURKB inhibitor BI-831266 suppressed the growth of human PDAC xenografts in mice. In patients with PDAC, the activity of AURKB was associated with poor prognosis. This fly-based platform provides an efficient whole-body approach that complements current methods for identifying therapeutic targets in PDAC.

SIGNIFICANCE

Development of a Drosophila model mimicking genetic alterations in human pancreatic ductal adenocarcinoma provides a tool for genetic screening that identifies MEK and AURKB inhibition as a potential treatment strategy.

Systematic Analysis of Covalent and Allosteric Protein Kinase Inhibitors

In drug discovery, protein kinase inhibitors (PKIs) are intensely investigated as drug candidates in different therapeutic areas. While ATP site-directed, non-covalent PKIs have long been a focal point in protein kinase (PK) drug discovery, in recent years, there has been increasing interest in allosteric PKIs (APKIs), which are expected to have high kinase selectivity. In addition, as compounds acting by covalent mechanisms experience a renaissance in drug discovery, there is also increasing interest in covalent PKIs (CPKIs). There are various reasons for this increasing interest such as the anticipated high potency, prolonged residence times compared to non-competitive PKIs, and other favorable pharmacokinetic properties. Due to the popularity of PKIs for therapeutic intervention, large numbers of PKIs and large volumes of activity data have accumulated in the public domain, providing a basis for large-scale computational analysis. We have systematically searched for CPKIs containing different reactive groups (warheads) and investigated their potency and promiscuity (multi-PK activity) on the basis of carefully curated activity data. For seven different warheads, sufficiently large numbers of CPKIs were available for detailed follow-up analysis. For only three warheads, the median potency of corresponding CPKIs was significantly higher than of non-covalent PKIs. However, for CKPIs with five of seven warheads, there was a significant increase in the median potency of at least 100-fold compared to PKI analogues without warheads. However, in the analysis of multi-PK activity, there was no general increase in the promiscuity of CPKIs compared to non-covalent PKIs. In addition, we have identified 29 new APKIs in X-ray structures of PK-PKI complexes. Among structurally characterized APKIs, 13 covalent APKIs in complexes with five PKs are currently available, enabling structure-based investigation of PK inhibition by covalent-allosteric mechanisms.

CMGC Kinases in Health and Cancer

CMGC kinases, encompassing cyclin-dependent kinases (CDKs), mitogen-activated protein kinases (MAPKs), glycogen synthase kinases (GSKs), and CDC-like kinases (CLKs), play pivotal roles in cellular signaling pathways, including cell cycle regulation, proliferation, differentiation, apoptosis, and gene expression regulation. The dysregulation and aberrant activation of these kinases have been implicated in cancer development and progression, making them attractive therapeutic targets. In recent years, kinase inhibitors targeting CMGC kinases, such as CDK4/6 inhibitors and BRAF/MEK inhibitors, have demonstrated clinical success in treating specific cancer types. However, challenges remain, including resistance to kinase inhibitors, off-target effects, and the need for better patient stratification. This review provides a comprehensive overview of the importance of CMGC kinases in cancer biology, their involvement in cellular signaling pathways, protein-protein interactions, and the current state of kinase inhibitors targeting these kinases. Furthermore, we discuss the challenges and future perspectives in targeting CMGC kinases for cancer therapy, including potential strategies to overcome resistance, the development of more selective inhibitors, and novel therapeutic approaches, such as targeting protein-protein interactions, exploiting synthetic lethality, and the evolution of omics in the study of the human kinome. As our understanding of the molecular mechanisms and protein-protein interactions involving CMGC kinases expands, so too will the opportunities for the development of more selective and effective therapeutic strategies for cancer treatment.

Applications of promiscuity of FDA-approved kinase inhibitors in drug repositioning and toxicity

Promiscuity of therapeutics has important implications in treatment and toxicity. So far, a comprehensive understanding of promiscuity related to kinase inhibitors is lacking and such an analysis may offer potential opportunities for drug repurposing. In the present study, profiling of inhibitor-specific kinases based on the available biochemical IC50s was performed, fold-change of IC50 values for additional targets were calculated by taking the primary target as the reference kinase, and finally the promiscuity degree (PD) for FDA-approved kinase inhibitors was calculated. Surprisingly, class II inhibitors showed more PD than that of the class I inhibitors. We further identified cancer types and sub-types in which additional kinase targets or off-targets of inhibitors were overexpressed for potential drug repurposing. In addition, the expression of these kinases in normal human tissues were also profiled to predict toxicity following drug repositioning. Taken together, the study offers opportunities for cancer treatment in a kinase-specific manner.

Palbociclib (PD 0332991) Interaction with Kinases. Theoretical and Comparative Molecular Docking Study

The optimized geometry of palbociclib, (PD 0332991) (8-cyclopentyl-6-ethanoyl-5-methyl-2-(5-(piperazin-1-yl)pyridin-2-ylamino)pyrido[2,3-d]pyrimidin-7(8H)-one), electrostatic potential map, molecular orbitals were calculated using the density functional theory. The geometry was used in a molecular docking study of palbociclib-kinase complexes, results could be explained by the charge of the nitrogen and oxygen atoms within the palbociclib. Energy gap of HOMO-LUMO surfaces, could help to explain the reactivity of the ligand and the hydrogen bonding with three different kinases, two of CDK6 and one of CDK4 type. Docking results are similar and complementary with literature reports using molecular dynamics, were hydrogen bonding was obtained and analyzed. The promiscuity of three kinases with palbociclib was detected by the docking results, thus, palbociclib could be used in other types of cancer besides myeloid leukemia. Some similarities are found with CDK4/CDK6 kinases which allow us to determine that palbociclib could be used to control other resistant inhibitor types of cancer.

Synthesis, kinetics and cellular studies of new phenothiazine analogs as potent human-TLK inhibitors

The alterations in the expression patterns of protein kinases often implicate human cancer initiation and progression. Human tousled-like kinases (TLKs), both TLK1/1B and TLK2, are evolutionary kinases found in cell signaling pathways and are involved in DNA repair, replication, and chromosomal integrity. Several reports have demonstrated the numerous roles of TLK1B in the development and progression of cancer via its interactions with different partners, and this direct association has made them viable molecular targets for cancer therapy. Previous studies have shown phenothiazines to be potent TLK1B inhibitors. Herein, we report the design and synthesis of a class of phenothiazine molecules and their biological inhibitory effect on hTLK1B/KD through in vitro kinase assays, cellular assays, and in silico studies. We identified a few inhibitors with better inhibition and physio-chemical properties than the reported TLK1B inhibitors using a recombinant human tousled-like kinase 1B-kinase domain (hTLK1B-KD). Very interestingly, inhibitory activity with LNCap cells was found to be on the sub-nanomolar level. Our attempts to study the newly designed phenothiazine analogs, as well as generate a stable catalytically active hTLK1B-KD in high yield, represent a fundamental step towards the structure-based design of future TLK-specific inhibitors.

Protein kinases: Role of their dysregulation in carcinogenesis, identification and inhibition

Protein kinases belong to the phosphor-transferases superfamily of enzymes, which "activate" enzymes via phosphorylation. The kinome of an organism is the total set of genes in the genome, which encode for all the protein kinases. Certain mutations in the kinome have been linked to dysregulation of protein kinases, which in turn can lead to several diseases and disorders including cancer. In this review, we have briefly discussed the role of protein kinases in various biochemical processes by categorizing cancer associated phenotypes and giving their protein kinase examples. Various techniques have also been discussed, which are being used to analyze the structure of protein kinases, and associate their roles in the oncogenesis. We have also discussed protein kinase inhibitors and United States Federal Drug Administration (USFDA) approved drugs, which target protein kinases and can serve as a counter to protein kinase dysregulation and mitigate the effects of oncogenesis. Overall, this review briefs about the importance of protein kinases, their roles in oncogenesis on dysregulation and how their inhibition via various drugs can be used to mitigate their effects.

Recent development of multi-targeted inhibitors of human topoisomerase II enzyme as potent cancer therapeutics

Multi-target therapies have been considered one of the viable options to overcome the challenges to eradicate intrinsic and acquired drug-resistant cancer cells. While to increase the efficacy of therapeutics, the use of a single drug against multiple structurally similar sites, which noncommittedly modulate several vital cellular pathways proposed as a potential alternative to a 'single drug single target'. Besides, it reduces the usage of a number of drugs and their side effects. Topoisomerase II enzyme plays a very significant role in DNA replication and thus served as an important target for numerous anti-cancer agents. However, in spite of promising clinical results, in several cases, it was found that cancer cells have developed resistance against the anti-cancer agents targeting this enzyme. Therefore, multi-target therapies have been proposed as an alternative to overcome different drug resistance mechanisms while topoisomerases II are a primary target site. In this review, we have tried to discuss the characteristics of the binding cavity available for interactions of drugs, and potent inhibitors concurrently modulate the functions of topoisomerases II as well as other structurally related target sites. Additionally, the mechanism of drug resistance by considering molecular and cellular insights by including various types of cancers.

Loss of NF1 in Melanoma Confers Sensitivity to SYK Kinase Inhibition

Neurofibromin 1 (NF1) loss of function (LoF) mutations are frequent in melanoma and drive hyperactivated RAS and tumor growth. NF1LoF melanoma cells, however, do not show consistent sensitivity to individual MEK, ERK, or PI3K/mTOR inhibitors. To identify more effective therapeutic strategies for treating NF1LoF melanoma, we performed a targeted kinase inhibitor screen. A tool compound named MTX-216 was highly effective in blocking NF1LoF melanoma growth in vitro and in vivo. Single-cell analysis indicated that drug-induced cytotoxicity was linked to effective cosuppression of proliferation marker Ki-67 and ribosomal protein S6 phosphorylation. The antitumor efficacy of MTX-216 was dependent on its ability to inhibit not only PI3K, its nominal target, but also SYK. MTX-216 suppressed expression of a group of genes that regulate mitochondrial electron transport chain and are associated with poor survival in patients with NF1LoF melanoma. Furthermore, combinations of inhibitors targeting either MEK or PI3K/mTOR with an independent SYK kinase inhibitor or SYK knockdown reduced the growth of NF1LoF melanoma cells. These studies provide a path to exploit SYK dependency to selectively target NF1LoF melanoma cells.

SIGNIFICANCE

A kinase inhibitor screen identifies SYK as a targetable vulnerability in melanoma cells with NF1 loss of function.

Advances in Computational Polypharmacology

In drug discovery, polypharmacology encompasses the use of small molecules with defined multi-target activity and in vivo effects resulting from multi-target engagement. Multi-target compounds are often efficacious in the treatment of complex diseases involving target and pathway networks, but might also elicit unwanted side effects. Computational approaches such as target prediction or multi-target ligand design have been used to support polypharmacological drug discovery. In addition to efforts directed at the identification or design of new multi-target compounds, other computational investigations have aimed to differentiate such compounds from potential false-positives or explore the molecular basis of multi-target activities. Herein, a concise overview of the field is provided and recent advances in computational polypharmacology through machine learning are discussed.

Artificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors

BACKGROUND

Vast amounts of rapidly accumulating biological data related to cancer and a remarkable progress in the field of artificial intelligence (AI) have paved the way for precision oncology. Our recent contribution to this area of research is CancerOmicsNet, an AI-based system to predict the therapeutic effects of multitargeted kinase inhibitors across various cancers. This approach was previously demonstrated to outperform other deep learning methods, graph kernel models, molecular docking, and drug binding pocket matching.

METHODS

CancerOmicsNet integrates multiple heterogeneous data by utilizing a deep graph learning model with sophisticated attention propagation mechanisms to extract highly predictive features from cancer-specific networks. The AI-based system was devised to provide more accurate and robust predictions than data-driven therapeutic discovery using gene signature reversion.

RESULTS

Selected CancerOmicsNet predictions obtained for "unseen" data are positively validated against the biomedical literature and by live-cell time course inhibition assays performed against breast, pancreatic, and prostate cancer cell lines. Encouragingly, six molecules exhibited dose-dependent antiproliferative activities, with pan-CDK inhibitor JNJ-7706621 and Src inhibitor PP1 being the most potent against the pancreatic cancer cell line Panc 04.03.

CONCLUSIONS

CancerOmicsNet is a promising AI-based platform to help guide the development of new approaches in precision oncology involving a variety of tumor types and therapeutics.

High Efficacy and Drug Synergy of HDAC6-Selective Inhibitor NN-429 in Natural Killer (NK)/T-Cell Lymphoma

NK/T-cell lymphoma (NKTCL) and γδ T-cell non-Hodgkin lymphomas (γδ T-NHL) are highly aggressive lymphomas that lack rationally designed therapies and rely on repurposed chemotherapeutics from other hematological cancers. Histone deacetylases (HDACs) have been targeted in a range of malignancies, including T-cell lymphomas. This study represents exploratory findings of HDAC6 inhibition in NKTCL and γδ T-NHL through a second-generation inhibitor NN-429. With nanomolar in vitro HDAC6 potency and high in vitro and in cellulo selectivity for HDAC6, NN-429 also exhibited long residence time and improved pharmacokinetic properties in contrast to older generation inhibitors. Following unique selective cytotoxicity towards γδ T-NHL and NKTCL, NN-429 demonstrated a synergistic relationship with the clinical agent etoposide and potential synergies with doxorubicin, cytarabine, and SNS-032 in these disease models, opening an avenue for combination treatment strategies.

Systematic Exploration of Privileged Warheads for Covalent Kinase Drug Discovery

Kinase-targeted drug discovery for cancer therapy has advanced significantly in the last three decades. Currently, diverse kinase inhibitors or degraders have been reported, such as allosteric inhibitors, covalent inhibitors, macrocyclic inhibitors, and PROTAC degraders. Out of these, covalent kinase inhibitors (CKIs) have been attracting attention due to their enhanced selectivity and exceptionally strong affinity. Eight covalent kinase drugs have been FDA-approved thus far. Here, we review current developments in CKIs. We explore the characteristics of the CKIs: the features of nucleophilic amino acids and the preferences of electrophilic warheads. We provide systematic insights into privileged warheads for repurposing to other kinase targets. Finally, we discuss trends in CKI development across the whole proteome.

CORN-Condition Orientated Regulatory Networks: bridging conditions to gene networks

A transcriptional regulatory network (TRN) is a collection of transcription regulators with their associated downstream genes, which is highly condition-specific. Understanding how cell states can be programmed through small molecules/drugs or conditions by modulating the whole gene expression system granted us the potential to amend abnormal cells and cure diseases. Condition Orientated Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/home) is a library of condition (small molecule/drug treatments and gene knockdowns)-based transcriptional regulatory sub-networks (TRSNs) that come with an online TRSN matching tool. It allows users to browse condition-associated TRSNs or match those TRSNs by inputting transcriptomic changes of interest. CORN utilizes transcriptomic changes data after specific conditional treatment in cells, and in vivo transcription factor (TF) binding data in cells, by combining TF binding information and calculations of significant expression alterations of TFs and genes after the conditional treatments, TRNs under the effect of different conditions were constructed. In short, CORN associated 1805 different types of specific conditions (small molecule/drug treatments and gene knockdowns) to 9553 TRSNs in 25 human cell lines, involving 204TFs. By linking and curating specific conditions to responsive TRNs, the scientific community can now perceive how TRNs are altered and controlled by conditions alone in an organized manner for the first time. This study demonstrated with examples that CORN can aid the understanding of molecular pathology, pharmacology and drug repositioning, and screened drugs with high potential for cancer and coronavirus disease 2019 (COVID-19) treatments.

Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs

Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.

Whole proteome mapping of compound-protein interactions

Off-target binding is one of the primary causes of toxic side effects of drugs in clinical development, resulting in failures of clinical trials. While off-target drug binding is a known phenomenon, experimental identification of the undesired protein binders can be prohibitively expensive due to the large pool of possible biological targets. Here, we propose a new strategy combining chemical similarity principle and deep learning to enable proteome-wide mapping of compound-protein interactions. We have developed a pipeline to identify the targets of bioactive molecules by matching them with chemically similar annotated "bait" compounds and ranking them with deep learning. We have constructed a user-friendly web server for drug-target identification based on chemical similarity (DRIFT) to perform searches across annotated bioactive compound datasets, thus enabling high-throughput, multi-ligand target identification, as well as chemical fragmentation of target-binding moieties.

Compounds co-targeting kinases in axon regulatory pathways promote regeneration and behavioral recovery after spinal cord injury in mice

Recovery from spinal cord injury (SCI) and other central nervous system (CNS) trauma is hampered by limits on axonal regeneration in the CNS. Regeneration is restricted by the lack of neuron-intrinsic regenerative capacity and by the repressive microenvironment confronting damaged axons. To address this challenge, we have developed a therapeutic strategy that co-targets kinases involved in both extrinsic and intrinsic regulatory pathways. Prior work identified a kinase inhibitor (RO48) with advantageous polypharmacology (co-inhibition of targets including ROCK2 and S6K1), which promoted CNS axon growth in vitro and corticospinal tract (CST) sprouting in a mouse pyramidotomy model. We now show that RO48 promotes neurite growth from sensory neurons and a variety of CNS neurons in vitro, and promotes CST sprouting and/or regeneration in multiple mouse models of spinal cord injury. Notably, these in vivo effects of RO48 were seen in several independent experimental series performed in distinct laboratories at different times. Finally, in a cervical dorsal hemisection model, RO48 not only promoted growth of CST axons beyond the lesion, but also improved behavioral recovery in the rotarod, gridwalk, and pellet retrieval tasks. Our results provide strong evidence for RO48 as an effective compound to promote axon growth and regeneration. Further, they point to strategies for increasing robustness of interventions in pre-clinical models.

A lymphatic-absorbed multi-targeted kinase inhibitor for myelofibrosis therapy

Activation of compensatory signaling nodes in cancer often requires combination therapies that are frequently plagued by dose-limiting toxicities. Intestinal lymphatic drug absorption is seldom explored, although reduced toxicity and sustained drug levels would be anticipated to improve systemic bioavailability. A potent orally bioavailable multi-functional kinase inhibitor (LP-182) is described with intrinsic lymphatic partitioning for the combined targeting of phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways without observable toxicity. We demonstrate selectivity and therapeutic efficacy through reduction of downstream kinase activation, amelioration of disease phenotypes, and improved survival in animal models of myelofibrosis. Our further characterization of synthetic and physiochemical properties for small molecule lymphatic uptake will support continued advancements in lymphatropic therapy for altering disease trajectories of a myriad of human disease indications.

Combination therapies simultaneously inhibiting different therapeutic targets in cancer is challenged by individual pharmacokinetic profiles. Here, the authors generate an orally provided multi-targeted kinase inhibitor that is lymphatic absorbed and increases survival in a murine model of myelofibrosis.

Discovery of spirooxindole-derived small-molecule compounds as novel HDAC/MDM2 dual inhibitors and investigation of their anticancer activity

Simultaneous inhibition of more than one target is considered to be a novel strategy in cancer therapy. Owing to the importance of histone deacetylases (HDACs) and p53-murine double minute 2 (MDM2) interaction in tumor development and their synergistic effects, a series of MDM2/HDAC bifunctional small-molecule inhibitors were rationally designed and synthesized by incorporating an HDAC pharmacophore into spirooxindole skeletons. These compounds exhibited good inhibitory activities against both targets. In particular, compound 11b was demonstrated to be most potent for MDM2 and HDAC, reaching the enzyme inhibition of 68% and 79%, respectively. Compound 11b also showed efficient antiproliferative activity towards MCF-7 cells with better potency than the reference drug SAHA and Nutlin-3. Furthermore, western blot analysis revealed that compound 11b increased the expression of p53 and Ac-H4 in MCF-7 cells in a dose-dependent manner. Our results indicate that dual inhibition of HDAC and MDM2 may provide a novel and efficient strategy for the discovery of antitumor drug in the future.

Anti-Survival Effect of SI306 and Its Derivatives on Human Glioblastoma Cells

Glioblastoma (GBM) is the most common adult brain tumor and, although many efforts have been made to find valid therapies, the onset of resistance is the main cause of recurrence. Therefore, it is crucial to identify and target the molecular mediators responsible for GBM malignancy. In this context, the use of Src inhibitors such as SI306 (C1) and its prodrug (C2) showed promising results, suggesting that SI306 could be the lead compound useful to derivate new anti-GBM drugs. Therefore, a new prodrug of SI306 (C3) was synthesized and tested on CAS-1 and U87 human GBM cells by comparing its effect to that of C1 and C2. All compounds were more effective on CAS-1 than U87 cells, while C2 was the most active on both cell lines. Moreover, the anti-survival effect was associated with a reduction in the expression of epidermal growth factor receptor (EGFR)WT and EGFR-vIII in U87 and CAS-1 cells, respectively. Collectively, our findings demonstrate that all tested compounds are able to counteract GBM survival, further supporting the role of SI306 as progenitor of promising new drugs to treat malignant GBM.

SAR Probing of KX2-391 Provided Analogues With Juxtaposed Activity Profile Against Major Oncogenic Kinases

Tirbanibulin (KX2-391, KX-01), a dual non-ATP (substrate site) Src kinase and tubulin-polymerization inhibitor, demonstrated a universal anti-cancer activity for variety of cancer types. The notion that KX2-391 is a highly selective Src kinase inhibitor have been challenged by recent reports on the activities of this drug against FLT3-ITD mutations in some leukemic cell lines. Therefore, we hypothesized that analogues of KX2-391 may inhibit oncogenic kinases other than Src. A set of 4-aroylaminophenyl-N-benzylacetamides were synthesized and found to be more active against leukemia cell lines compared to solid tumor cell lines. N-(4-(2-(benzylamino)-2-oxoethyl)phenyl)-4-chlorobenzamide (4e) exhibited activities at IC₅₀ 0.96 µM, 1.62 µM, 1.90 µM and 4.23 µM against NB4, HL60, MV4-11 and K562 leukemia cell lines, respectively. We found that underlying mechanisms of 4e did not include tubulin polymerization or Src inhibition. Such results interestingly suggested that scaffold-hopping of KX2-391 may change the two main underlying cytotoxic mechanisms (Src and tubulin). Kinase profiling using two methods revealed that 4e significantly reduces the activities of some other potent oncogenic kinases like the MAPK member ERK1/2 (>99%) and it also greatly upregulates the pro-apoptotic c-Jun kinase (84%). This research also underscores the importance of thorough investigation of total kinase activities as part of the structure-activity relationship studies.

New kinase and HDAC hybrid inhibitors: recent advances and perspectives

Cancer is the second most common cause of death worldwide. It can easily acquire resistance to treatments, demanding new therapeutic strategies, such as simultaneous inhibition of kinase and HDAC enzymes with hybrid inhibitors. Different approaches to this have varied according to their targets, with a few common trends, such as the usage of heterocycle scaffolds for kinase interaction, especially pyrimidine and quinazolines, and hydroxamic acids and benzamides for HDAC inhibition. Besides the hybrid compounds developed focusing on the inhibition tyrosine kinase and receptor tyrosine kinase, many advances have occurred in the development of serine-threonine kinase/HDAC and lipid kinase/HDAC novel compounds. Here, the latest strategies employed in this research area will be reviewed, alongside trends in inhibitor design, and observed gaps will be punctuated.

Covalent Inhibition of the Human 20S Proteasome with Homobelactosin C Inquired by QM/MM Studies

20S proteasome is a main player in the protein degradation pathway in the cytosol, thus intervening in multiple pivotal cellular processes. Over the years the proteasome has emerged as a crucial target for the treatment of many diseases such as neurodegenerative diseases, cancer, autoimmune diseases, developmental disorders, cystic fibrosis, diabetes, cardiac diseases, atherosclerosis, and aging. In this work, the mechanism of proteasome covalent inhibition with bisbenzyl-protected homobelactosin C (hBelC) was explored using quantum mechanics/molecular mechanics (QM/MM) methods. Molecular dynamic simulations were used to describe key interactions established between the hBelC and its unique binding mode in the primed site of the β5 subunit. The free energy surfaces were computed to characterize the kinetics and thermodynamics of the inhibition process. This study revealed that although the final inhibition product for hBelC is formed according to the same molecular mechanism as one described for hSalA, the free energy profile of the reaction pathway differs significantly from the one previously reported for γ-lactam-β-lactone containing inhibitors in terms of the height of the activation barrier as well as the stabilization of the final product. Moreover, it was proved that high stabilization of the covalent adduct formed between β5-subunit and hBelC, together with the presence of aminocarbonyl side chain in the structure of the inhibitor which prevents the hydrolysis of the ester bond from taking place, determines its irreversible character.

Differentiating Inhibitors of Closely Related Protein Kinases with Single- or Multi-Target Activity via Explainable Machine Learning and Feature Analysis

Protein kinases are major drug targets. Most kinase inhibitors are directed against the adenosine triphosphate (ATP) cofactor binding site, which is largely conserved across the human kinome. Hence, such kinase inhibitors are often thought to be promiscuous. However, experimental evidence and activity data for publicly available kinase inhibitors indicate that this is not generally the case. We have investigated whether inhibitors of closely related human kinases with single- or multi-kinase activity can be differentiated on the basis of chemical structure. Therefore, a test system consisting of two distinct kinase triplets has been devised for which inhibitors with reported triple-kinase activities and corresponding single-kinase activities were assembled. Machine learning models derived on the basis of chemical structure distinguished between these multi- and single-kinase inhibitors with high accuracy. A model-independent explanatory approach was applied to identify structural features determining accurate predictions. For both kinase triplets, the analysis revealed decisive features contained in multi-kinase inhibitors. These features were found to be absent in corresponding single-kinase inhibitors, thus providing a rationale for successful machine learning. Mapping of features determining accurate predictions revealed that they formed coherent and chemically meaningful substructures that were characteristic of multi-kinase inhibitors compared with single-kinase inhibitors.

Novel Aurora A and Protein Kinase C (α, β1, β2, and θ) Multitarget Inhibitors: Impact of Selenium Atoms on the Potency and Selectivity

Aurora kinases and protein kinase C (PKC) have been shown to be involved in different aspects of cancer progression. To date, no dual Aurora/PKC inhibitor with clinical efficacy and low toxicity is available. Here, we report the identification of compound 2e as a potent small molecule capable of selectively inhibiting Aurora A kinase and PKC isoforms α, β1, β2 and θ. Compound 2e demonstrated significant inhibition of the colony forming ability of metastatic breast cancer cells in vitro and metastasis development in vivo. In vitro kinase screening and molecular modeling studies revealed the critical role of the selenium-containing side chains within 2e, where selenium atoms were shown to significantly improve its selectivity and potency by forming additional interactions and modulating the protein dynamics. In comparison to other H-bonding heteroatoms such as sulfur, our studies suggested that these selenium atoms also confer more favorable PK properties.

Discovery of Kinase and Carbonic Anhydrase Dual Inhibitors by Machine Learning Classification and Experiments

A multi-target small molecule modulator is advantageous for treating complicated diseases such as cancers. However, the strategy and application for discovering a multi-target modulator have been less reported. This study presents the dual inhibitors for kinase and carbonic anhydrase (CA) predicted by machine learning (ML) classifiers, and validated by biochemical and biophysical experiments. ML trained by CA I and CA II inhibitor molecular fingerprints predicted candidates from the protein-specific bioactive molecules approved or under clinical trials. For experimental tests, three sulfonamide-containing kinase inhibitors, 5932, 5946, and 6046, were chosen. The enzyme assays with CA I, CA II, CA IX, and CA XII have allowed the quantitative comparison in the molecules’ inhibitory activities. While 6046 inhibited weakly, 5932 and 5946 exhibited potent inhibitions with 100 nM to 1 μM inhibitory constants. The ML screening was extended for finding CAs inhibitors of all known kinase inhibitors. It found XMU-MP-1 as another potent CA inhibitor with an approximate 30 nM inhibitory constant for CA I, CA II, and CA IX. Differential scanning fluorimetry confirmed the direct interaction between CAs and small molecules. Cheminformatics studies, including docking simulation, suggest that each molecule possesses two separate functional moieties: one for interaction with kinases and the other with CAs.

Anticancer drug resistance: An update and perspective

Driver mutations promote initiation and progression of cancer. Pharmacological treatment can inhibit the action of the mutant protein; however, drug resistance almost invariably emerges. Multiple studies revealed that cancer drug resistance is based upon a plethora of distinct mechanisms. Drug resistance mutations can occur in the same protein or in different proteins; as well as in the same pathway or in parallel pathways, bypassing the intercepted signaling. The dilemma that the clinical oncologist is facing is that not all the genomic alterations as well as alterations in the tumor microenvironment that facilitate cancer cell proliferation are known, and neither are the alterations that are likely to promote metastasis. For example, the common KRasG12C driver mutation emerges in different cancers. Most occur in NSCLC, but some occur, albeit to a lower extent, in colorectal cancer and pancreatic ductal carcinoma. The responses to KRasG12C inhibitors are variable and fall into three categories, (i) new point mutations in KRas, or multiple copies of KRAS G12C which lead to higher expression level of the mutant protein; (ii) mutations in genes other than KRAS; (iii) original cancer transitioning to other cancer(s). Resistance to adagrasib, an experimental antitumor agent exerting its cytotoxic effect as a covalent inhibitor of the G12C KRas, indicated that half of the cases present multiple KRas mutations as well as allele amplification. Redundant or parallel pathways included MET amplification; emerging driver mutations in NRAS, BRAF, MAP2K1, and RET; gene fusion events in ALK, RET, BRAF, RAF1, and FGFR3; and loss-of-function mutations in NF1 and PTEN tumor suppressors. In the current review we discuss the molecular mechanisms underlying drug resistance while focusing on those emerging to common targeted cancer drivers. We also address questions of why cancers with a common driver mutation are unlikely to evolve a common drug resistance mechanism, and whether one can predict the likely mechanisms that the tumor cell may develop. These vastly important and tantalizing questions in drug discovery, and broadly in precision medicine, are the focus of our present review. We end with our perspective, which calls for target combinations to be selected and prioritized with the help of the emerging massive compute power which enables artificial intelligence, and the increased gathering of data to overcome its insatiable needs.