Evolution of kinase polypharmacology across HSP90 drug discovery.
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ABSTRACT:
SUBMITTER: Antolin AA
PROVIDER: S-EPMC8550792 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Heat-shock protein 90 (Hsp90) promotes the maturation and stability of its client proteins, including many kinases. In doing so, Hsp90 may allow its clients to accumulate mutations as previously proposed by the capacitor hypothesis. If true, Hsp90 clients should show increased evolutionary rate compared with nonclients; however, other factors, such as gene expression and protein connectivity, may confound or obscure the chaperone's putative contribution. Here, we compared the evolutionary rates of many Hsp90 clients and nonclients in the human protein kinase superfamily. We show that Hsp90 client status promotes evolutionary rate independently of, but in a small magnitude similar to that of gene expression and protein connectivity. Hsp90's effect on kinase evolutionary rate was detected across mammals, specifically relaxing purifying selection. Hsp90 clients also showed increased nucleotide diversity and harbored more damaging variation than nonclient kinases across humans. These results are consistent with the central argument of the capacitor hypothesis that interaction with the chaperone allows its clients to harbor genetic variation. Hsp90 client status is thought to be highly dynamic with as few as one amino acid change rendering a protein dependent on the chaperone. Contrary to this expectation, we found that across protein kinase phylogeny Hsp90 client status tends to be gained, maintained, and shared among closely related kinases. We also infer that the ancestral protein kinase was not an Hsp90 client. Taken together, our results suggest that Hsp90 played an important role in shaping the kinase superfamily.
| S-EPMC4271522 | biostudies-literature
Project description:Recently, despite the great success achieved by the so-called "magic bullets" in the treatment of different diseases through a marked and specific interaction with the target of interest, the pharmacological research is moving toward the development of "molecular network active compounds," embracing the related polypharmacology approach. This strategy was born to overcome the main limitations of the single target therapy leading to a superior therapeutic effect, a decrease of adverse reactions, and a reduction of potential mechanism(s) of drug resistance caused by robustness and redundancy of biological pathways. It has become clear that multifactorial diseases such as cancer, neurological, and inflammatory disorders, may require more complex therapeutic approaches hitting a certain biological system as a whole. Concerning epigenetics, the goal of the multi-epi-target approach consists in the development of small molecules able to simultaneously and (often) reversibly bind different specific epi-targets. To date, two dual histone deacetylase/kinase inhibitors (CUDC-101 and CUDC-907) are in an advanced stage of clinical trials. In the last years, the growing interest in polypharmacology encouraged the publication of high-quality reviews on combination therapy and hybrid molecules. Hence, to update the state-of-the-art of these therapeutic approaches avoiding redundancy, herein we focused only on multiple medication therapies and multitargeting compounds exploiting epigenetic plus nonepigenetic drugs reported in the literature in 2018. In addition, all the multi-epi-target inhibitors known in literature so far, hitting two or more epigenetic targets, have been included.
| S-EPMC6917854 | biostudies-literature
Project description:INTRODUCTION:In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success. AREAS COVERED:In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies. EXPERT OPINION:Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multi-omics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.
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Project description:Oncogenic conversion of the RET (rearranged during transfection) tyrosine kinase is associated with several cancers. A fragment-based chemical screen led to the identification of a novel RET inhibitor, Pz-1. Modeling and kinetic analysis identified Pz-1 as a type II tyrosine kinase inhibitor that is able to bind the "DFG-out" conformation of the kinase. Importantly, from a single-agent polypharmacology standpoint, Pz-1 was shown to be active on VEGFR2, which can block the blood supply required for RET-stimulated growth. In cell-based assays, 1.0 nM of Pz-1 strongly inhibited phosphorylation of all tested RET oncoproteins. At 1.0 mg kg(-1) day(-1) per os, Pz-1 abrogated the formation of tumors induced by RET-mutant fibroblasts and blocked the phosphorylation of both RET and VEGFR2 in tumor tissue. Pz-1 featured no detectable toxicity at concentrations of up to 100.0 mg kg(-1), which indicates a large therapeutic window. This study validates the effectiveness and usefulness of a medicinal chemistry/polypharmacology approach to obtain an inhibitor capable of targeting multiple oncogenic pathways.
| S-EPMC4535927 | biostudies-literature
Project description:Polypharmacology (action of drugs against multiple targets) represents a tempting avenue for new drug development; unfortunately, methods capable of exploiting the known polypharmacology of drugs for target deconvolution are lacking. Here, we present an ensemble approach using elastic net regularization combined with mRNA expression profiling and previously characterized data on a large set of kinase inhibitors to identify kinases that are important for epithelial and mesenchymal cell migration. By profiling a selected optimal set of 32 kinase inhibitors in a panel against six cell lines, we identified cell type-specific kinases that regulate cell migration. Our discovery of several informative kinases with a previously uncharacterized role in cell migration (such as Mst and Taok family of MAPK kinases in mesenchymal cells) may represent novel targets that warrant further investigation. Target deconvolution using our ensemble approach has the potential to aid in the rational design of more potent but less toxic drug combinations.
| S-EPMC3977247 | biostudies-literature
Project description:Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar kinase drug pockets, off-target inhibitor toxicity has been a major cause for clinical trial failures. The pockets are similar but not identical. Here, we describe a transformation invariant protocol to identify distinct geometric features in the drug pocket that can distinguish one kinase from all others. We integrate available experimental structures with the artificial intelligence-based structural kinome, performing a kinome-wide structural bioinformatic analysis to establish the structural principles of kinase drug selectivity. We generate the structural landscape from the experimental kinase-ligand complexes and propose a binary network that encapsulates the information. The results show that all kinases contain binary units that are shared by less than seven other kinases in the kinome. 331 kinases contain unique binary units that may distinguish them from all others. The structural features encoded by these binary units in the network represent the inhibitor-accessible geometric space that may capture the kinome-wide selectivity. Our proposed binary network with the unsupervised clustering can serve as a general structural bioinformatic protocol for extracting the distinguishing structural features for any protein from their families. We apply the binary network to epidermal growth factor receptor tyrosine kinase inhibitor selectivity by targeting the gate area and the AKT1 serine/threonine kinase selectivity by binding to the αC-helix region and the allosteric pocket. Finally, we develop the cross-platform software, KDS (Kinase Drug Selectivity), for customized visualization and analysis of the binary networks in the human kinome (https://github.com/CBIIT/KDS).
| S-EPMC10018734 | biostudies-literature
Project description:Masitinib, a highly selective protein kinase inhibitor, can sensitise gemcitabine-refractory cancer cell lines when used in combination with gemcitabine. Here we report a reverse proteomic approach that identifies the target responsible for this sensitisation: the deoxycytidine kinase (dCK). Masitinib, as well as other protein kinase inhibitors, such as imatinib, interact with dCK and provoke an unforeseen conformational-dependent activation of this nucleoside kinase, modulating phosphorylation of nucleoside analogue drugs. This phenomenon leads to an increase of prodrug phosphorylation of most of the chemotherapeutic drugs activated by this nucleoside kinase. The unforeseen dual activity of protein kinase inhibition/nucleoside kinase activation could be of great therapeutic benefit, through either reducing toxicity of therapeutic agents by maintaining effectiveness at lower doses or by counteracting drug resistance initiated via down modulation of dCK target.
| S-EPMC5681654 | biostudies-literature
Project description:Concomitant inhibition of multiple cancer-driving kinases is an established strategy to improve the durability of clinical responses to targeted therapies. The difficulty of discovering kinase inhibitors with an appropriate multitarget profile has, however, necessitated the application of combination therapies, which can pose major clinical development challenges. Epigenetic reader domains of the bromodomain family have recently emerged as new targets for cancer therapy. Here we report that several clinical kinase inhibitors also inhibit bromodomains with therapeutically relevant potencies and are best classified as dual kinase-bromodomain inhibitors. Nanomolar activity on BRD4 by BI-2536 and TG-101348, which are clinical PLK1 and JAK2-FLT3 kinase inhibitors, respectively, is particularly noteworthy as these combinations of activities on independent oncogenic pathways exemplify a new strategy for rational single-agent polypharmacological targeting. Furthermore, structure-activity relationships and co-crystal structures identify design features that enable a general platform for the rational design of dual kinase-bromodomain inhibitors.
| S-EPMC3998711 | biostudies-literature
Project description:Polypharmacology plays an important role in defining response and adverse effects of drugs. For some mechanisms, experimentally mapping polypharmacology is commonplace, although this is typically done within the same protein class. Four PARP inhibitors have been approved by the FDA as cancer therapeutics, yet a precise mechanistic rationale to guide clinicians on which to choose for a particular patient is lacking. The four drugs have largely similar PARP family inhibition profiles, but several differences at the molecular and clinical level have been reported that remain poorly understood. Here, we report the first comprehensive characterization of the off-target kinase landscape of four FDA-approved PARP drugs. We demonstrate that all four PARP inhibitors have a unique polypharmacological profile across the kinome. Niraparib and rucaparib inhibit DYRK1s, CDK16 and PIM3 at clinically achievable, submicromolar concentrations. These kinases represent the most potently inhibited off-targets of PARP inhibitors identified to date and should be investigated further to clarify their potential implications for efficacy and safety in the clinic. Moreover, broad kinome profiling is recommended for the development of PARP inhibitors as PARP-kinase polypharmacology could potentially be exploited to modulate efficacy and side-effect profiles.
| S-EPMC7026418 | biostudies-literature
Project description:Drug repurposing has emerged as an important strategy and it has a great potential in identifying therapeutic applications for COVID-19. An extensive virtual screening of 4193 FDA approved drugs has been carried out against 24 proteins of SARS-CoV2 (NSP1-10 and NSP12-16, envelope, membrane, nucleoprotein, spike, ORF3a, ORF6, ORF7a, ORF8, and ORF9b). The drugs were classified into top 10 and bottom 10 drugs based on the docking scores followed by the distribution of their therapeutic indications. As a result, the top 10 drugs were found to have therapeutic indications for cancer, pain, neurological disorders, and viral and bacterial diseases. As drug resistance is one of the major challenges in antiviral drug discovery, polypharmacology and network pharmacology approaches were employed in the study to identify drugs interacting with multiple targets and drugs such as dihydroergotamine, ergotamine, bisdequalinium chloride, midostaurin, temoporfin, tirilazad, and venetoclax were identified among the multi-targeting drugs. Further, a pathway analysis of the genes related to the multi-targeting drugs was carried which provides insight into the mechanism of drugs and identifying targetable genes and biological pathways involved in SARS-CoV2.
| S-EPMC10411734 | biostudies-literature