Kinase mutations in human disease: interpreting genotype-phenotype relationships

Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice

Quantitative predictive modeling of cancer growth, progression, and individual response to therapy is a rapidly growing field. Researchers from mathematical modeling, systems biology, pharmaceutical industry, and regulatory bodies, are collaboratively working on predictive models that could be applied for drug development and, ultimately, the clinical management of cancer patients. A plethora of modeling paradigms and approaches have emerged, making it challenging to compile a comprehensive review across all subdisciplines. It is therefore critical to gauge fundamental design aspects against requirements, and weigh opportunities and limitations of the different model types. In this review, we discuss three fundamental types of cancer models: space-structured models, ecological models, and immune system focused models. For each type, it is our goal to illustrate which mechanisms contribute to variability and heterogeneity in cancer growth and response, so that the appropriate architecture and complexity of a new model becomes clearer. We present the main features addressed by each of the three exemplary modeling types through a subjective collection of literature and illustrative exercises to facilitate inspiration and exchange, with a focus on providing a didactic rather than exhaustive overview. We close by imagining a future multi-scale model design to impact critical decisions in oncology drug development.

Dissecting the multifaceted roles of autophagy in cancer initiation, growth, and metastasis: from molecular mechanisms to therapeutic applications

Autophagy is a cytoplasmic defense mechanism that cells use to break and reprocess their intracellular components. This utilization of autophagy is regarded as a savior in nutrient-deficient and other stressful conditions. Hence, autophagy keeps contact with and responds to miscellaneous cellular tensions and diverse pathways of signal transductions, such as growth signaling and cellular death. Importantly, autophagy is regarded as an effective tumor suppressor because regular autophagic breakdown is essential for cellular maintenance and minimizing cellular damage. However, paradoxically, autophagy has also been observed to promote the events of malignancies. This review discussed the dual role of autophagy in cancer, emphasizing its influence on tumor survival and progression. Possessing such a dual contribution to the malignant establishment, the prevention of autophagy can potentially advocate for the advancement of malignant transformation. In contrast, for the context of the instituted tumor, the agents of preventing autophagy potently inhibit the advancement of the tumor. Key regulators, including calpain 1, mTORC1, and AMPK, modulate autophagy in response to nutritional conditions and stress. Oncogenic mutations like RAS and B-RAF underscore autophagy's pivotal role in cancer development. The review also delves into autophagy's context-dependent roles in tumorigenesis, metastasis, and the tumor microenvironment (TME). It also discusses the therapeutic effectiveness of autophagy for several cancers. The recent implication of autophagy in the control of both innate and antibody-mediated immune systems made it a center of attention to evaluating its role concerning tumor antigens and treatments of cancer.

Identification of phosphorylated small ORF-encoded peptides in Hep3B cells by LC/MS/MS

Small ORF-encoded peptides (SEPs) are a class of low molecular weight proteins and peptides comprising <100 amino acids with important functions in various life activities. Although the sequence length is short, SEPs might also have post-translational modification (PTM). Phosphorylation is one of the most essential PTMs of proteins. In this work, we enriched phosphopeptides with IMAC and TiO2 materials and analyzed the phosphorylated SEPs in Hep3B cells. A total of 24 phosphorylated SEPs were identified, and 11 SEPs were coded by ncRNA. For the sequence analysis, we found that the general characteristics of phosphorylated SEPs are roughly the same as canonical proteins. Besides, two phosphorylation SEPs have the Stathmin family signature 2 motif, which can regulate the microtubule cytoskeleton. Some SEPs have domains or signal peptides, indicating their specific functions and subcellular locations. Kinase network analysis found a small number of kinases that may be a clue to the specific functions of some SEPs. However, only one-fifth of the predicted phosphorylation sites were identified by LC/MS/MS, indicating that many SEP PTMs are hidden in the dark, waiting to be uncovered and verified. This study helps expand our understanding of SEP and provides information for further SEP function investigation. SIGNIFICANCE: Small ORF-encoded peptides (SEPs) are important in various life activities. Although the sequence length is short (<100AA), SEPs might also have post-translational modification (PTM). Phosphorylation is one of the most essential PTMs of proteins. We enriched phosphopeptides and analyzed the phosphorylated SEPs in Hep3B cells. That is the first time to explore the PTM of SPEs systematically. Kinase network analysis found a small number of kinases that may be a clue to the specific functions of SEPs. More SEP PTMs are hidden in the dark and waiting to be uncovered and verified. This study helps expand our understanding of SEP and provides information for further SEP function investigation.

Kinase Inhibitors and Kinase-Targeted Cancer Therapies: Recent Advances and Future Perspectives

Over 120 small-molecule kinase inhibitors (SMKIs) have been approved worldwide for treating various diseases, with nearly 70 FDA approvals specifically for cancer treatment, focusing on targets like the epidermal growth factor receptor (EGFR) family. Kinase-targeted strategies encompass monoclonal antibodies and their derivatives, such as nanobodies and peptides, along with innovative approaches like the use of kinase degraders and protein kinase interaction inhibitors, which have recently demonstrated clinical progress and potential in overcoming resistance. Nevertheless, kinase-targeted strategies encounter significant hurdles, including drug resistance, which greatly impacts the clinical benefits for cancer patients, as well as concerning toxicity when combined with immunotherapy, which restricts the full utilization of current treatment modalities. Despite these challenges, the development of kinase inhibitors remains highly promising. The extensively studied tyrosine kinase family has 70% of its targets in various stages of development, while 30% of the kinase family remains inadequately explored. Computational technologies play a vital role in accelerating the development of novel kinase inhibitors and repurposing existing drugs. Recent FDA-approved SMKIs underscore the importance of blood-brain barrier permeability for long-term patient benefits. This review provides a comprehensive summary of recent FDA-approved SMKIs based on their mechanisms of action and targets. We summarize the latest developments in potential new targets and explore emerging kinase inhibition strategies from a clinical perspective. Lastly, we outline current obstacles and future prospects in kinase inhibition.

The role of kinases in peripheral nerve regeneration: mechanisms and implications

Peripheral nerve injury disease is a prevalent traumatic condition in current medical practice. Despite the present treatment approaches, encompassing surgical sutures, autologous nerve or allograft nerve transplantation, tissue engineering techniques, and others, an effective clinical treatment method still needs to be discovered. Exploring novel treatment methods to improve peripheral nerve regeneration requires more effort in investigating the cellular and molecular mechanisms involved. Many factors are associated with the regeneration of injured peripheral nerves, including the cross-sectional area of the injured nerve, the length of the nerve gap defect, and various cellular and molecular factors such as Schwann cells, inflammation factors, kinases, and growth factors. As crucial mediators of cellular communication, kinases exert regulatory control over numerous signaling cascades, thereby participating in various vital biological processes, including peripheral nerve regeneration after nerve injury. In this review, we examined diverse kinase classifications, distinct nerve injury types, and the intricate mechanisms involved in peripheral nerve regeneration. Then we stressed the significance of kinases in regulating autophagy, inflammatory response, apoptosis, cell cycle, oxidative processes, and other aspects in establishing conductive microenvironments for nerve tissue regeneration. Finally, we briefly discussed the functional roles of kinases in different types of cells involved in peripheral nerve regeneration.

Phosphorylation of the compartmentalized PKA substrate TAF15 regulates RNA-protein interactions

Spatiotemporal-controlled second messengers alter molecular interactions of central signaling nodes for ensuring physiological signal transmission. One prototypical second messenger molecule which modulates kinase signal transmission is the cyclic-adenosine monophosphate (cAMP). The main proteinogenic cellular effectors of cAMP are compartmentalized protein kinase A (PKA) complexes. Their cell-type specific compositions precisely coordinate substrate phosphorylation and proper signal propagation which is indispensable for numerous cell-type specific functions. Here we present evidence that TAF15, which is implicated in the etiology of amyotrophic lateral sclerosis, represents a novel nuclear PKA substrate. In cross-linking and immunoprecipitation experiments (iCLIP) we showed that TAF15 phosphorylation alters the binding to target transcripts related to mRNA maturation, splicing and protein-binding related functions. TAF15 appears to be one of multiple PKA substrates that undergo RNA-binding dynamics upon phosphorylation. We observed that the activation of the cAMP-PKA signaling axis caused a change in the composition of a collection of RNA species that interact with TAF15. This observation appears to be a broader principle in the regulation of molecular interactions, as we identified a significant enrichment of RNA-binding proteins within endogenous PKA complexes. We assume that phosphorylation of RNA-binding domains adds another layer of regulation to binary protein-RNAs interactions with consequences to RNA features including binding specificities, localization, abundance and composition.

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.

Steady State and Time-Dependent Fluorescent Peptide Assays for Protein Kinases

Protein kinases catalyze the phosphorylation of proteins most commonly on Ser, Thr, and Tyr residues and regulate many cellular events in eukaryotic cells, such as cell cycle progression, transcription, metabolism, and apoptosis. Protein kinases each have a conserved ATP-binding site and one or more substrate-binding site(s) that exhibit recognition features for different protein substrates. By bringing ATP and a substrate into proximity, each protein kinase can transfer the γ phosphate of the ATP molecule to a hydroxyl group of the target residue on the substrate. In such a way, signaling pathways downstream from the substrate can be regulated based on the phosphorylated versus dephosphorylated status of the substrate. Although there are a number of ways to assay the activity of protein kinases, most of them are technically cumbersome and/or are indirect or based on quenched reactions. This protocol describes an assay employing a fluorescent peptide substrate to detect phosphorylation by protein kinases in real time. The assay is based on the principle that the phosphorylation of the peptide substrate leads to an increase in the fluorescence emission intensity of an appended fluorophore. We extend the application of this assay to an example of how to assess time-dependent covalent inhibition of kinases as well. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Measuring protein kinase activity using fluorescent peptides Alternate Protocol: Measuring protein kinase activity using a fluorescence plate reader Support Protocol: Labeling peptides with sox fluorophore Basic Protocol 2: Measuring time-dependent ATP-competitive inhibition of protein kinases using fluorescent peptides.

Targeting Receptor Tyrosine Kinases as a Novel Strategy for the Treatment of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) comprises a group of aggressive and heterogeneous breast carcinoma. Chemotherapy is the mainstay for the treatment of triple-negative tumors. Nevertheless, the success of chemotherapeutic treatments is limited by their toxicity and development of acquired resistance leading to therapeutic failure and tumor relapse. Hence, there is an urgent need to explore novel targeted therapies for TNBC. Receptor tyrosine kinases (RTKs) are a family of transmembrane receptors that are key regulators of intracellular signaling pathways controlling cell proliferation, differentiation, survival, and motility. Aberrant activity and/or expression of several types of RTKs have been strongly connected to tumorigenesis. RTKs are frequently overexpressed and/or deregulated in triple-negative breast tumors and are further associated with tumor progression and reduced survival in patients. Therefore, targeting RTKs could be an appealing therapeutic strategy for the treatment of TNBC. This review summarizes the current evidence regarding the antitumor activity of RTK inhibitors in preclinical models of TNBC. The review also provides insights into the clinical trials evaluating the use of RTK inhibitors for the treatment of patients with TNBC.

SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).

Comparative Atomistic Insights on Apo and ATP-I1171N/S/T in Nonsmall-Cell Lung Cancer

Anaplastic lymphoma kinase (ALK) rearrangements occur in about 5% of nonsmall cell lung cancer (NSCLC) patients. Despite being first recognized as EML4-ALK, fusions with several additional genes have been identified, all of which cause constitutive activation of the ALK kinase and subsequently lead to tumor development. ALK inhibitors first-line crizotinib, second-line ceritinib, and alectinib are effective against NSCLC patients with these rearrangements. Patients progressing on crizotinib had various mutations in the ALK kinase domain. ALK fusion proteins are activated by oligomerization through the fusion partner, which leads to the autophosphorylation of the kinase's domain and consequent downstream activation. The proposed computational study focuses on understanding the activation mechanism of ALK and ATP binding of wild-type (WT) and I1171N/S/T mutations. We analyzed the conformational change of ALK I1171N/S/T mutations and ATP binding using molecular docking and molecular dynamics simulation approaches. According to principal component analysis and free energy landscape, it is clear that I1171N/S/T mutations in Apo and ATP showed different energy minima/unstable structures compared to WT-Apo. The results revealed that I1171N/S/T mutations and ATP binding significantly supported a change toward an active-state conformation, whereas WT-Apo remained inactive. We demonstrated that I1171N/S/T mutations are persistent in an active state and independent of ATP. The I1171S/T mutations showed greater intermolecular H-bonds with ATP than WT-ATP. The molecular mechanics Poisson-Boltzmann surface area analysis revealed that the I1171N/S/T mutation binding energy was similar to that of WT-ATP. This study shows that I1171N/S/T can form stable bonds with ATP and may contribute to a constitutively active kinase. Based on the Y1278-C1097 H-bond and E1167-K1150 salt bridge interaction, I1171N strongly promotes the constitutively active kinase independent of ATP. This structural mechanism study will aid in understanding the oncogenic activity of ALK and the basis for improving the ALK inhibitors.

Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding

The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied "dark" members. Accurate prediction of dark kinase functions is a major bioinformatics challenge. Here, we employ a graph mining approach that uses the evolutionary and functional context encoded in knowledge graphs (KGs) to predict protein and pathway associations for understudied kinases. We propose a new scalable graph embedding approach, RegPattern2Vec, which employs regular pattern constrained random walks to sample diverse aspects of node context within a KG flexibly. RegPattern2Vec learns functional representations of kinases, interacting partners, post-translational modifications, pathways, cellular localization, and chemical interactions from a kinase-centric KG that integrates and conceptualizes data from curated heterogeneous data resources. By contextualizing information relevant to prediction, RegPattern2Vec improves accuracy and efficiency in comparison to other random walk-based graph embedding approaches. We show that the predictions produced by our model overlap with pathway enrichment data produced using experimentally validated Protein-Protein Interaction (PPI) data from both publicly available databases and experimental datasets not used in training. Our model also has the advantage of using the collected random walks as biological context to interpret the predicted protein-pathway associations. We provide high-confidence pathway predictions for 34 dark kinases and present three case studies in which analysis of meta-paths associated with the prediction enables biological interpretation. Overall, RegPattern2Vec efficiently samples multiple node types for link prediction on biological knowledge graphs and the predicted associations between understudied kinases, pseudokinases, and known pathways serve as a conceptual starting point for hypothesis generation and testing.

Discovery of oncogenic ROS1 missense mutations with sensitivity to tyrosine kinase inhibitors

ROS1 is the largest receptor tyrosine kinase in the human genome. Rearrangements of the ROS1 gene result in oncogenic ROS1 kinase fusion proteins that are currently the only validated biomarkers for targeted therapy with ROS1 TKIs in patients. While numerous somatic missense mutations in ROS1 exist in the cancer genome, their impact on catalytic activity and pathogenic potential is unknown. We interrogated the AACR Genie database and identified 34 missense mutations in the ROS1 tyrosine kinase domain for further analysis. Our experiments revealed that these mutations have varying effects on ROS1 kinase function, ranging from complete loss to significantly increased catalytic activity. Notably, Asn and Gly substitutions at Asp2113 in the ROS1 kinase domain were found to be TKI-sensitive oncogenic variants in cell-based model systems. In vivo experiments showed that ROS1 D2113N induced tumor formation that was sensitive to crizotinib and lorlatinib, FDA-approved ROS1-TKIs. Collectively, these findings highlight the tumorigenic potential of specific point mutations within the ROS1 kinase domain and their potential as therapeutic targets with FDA-approved ROS1-TKIs.

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.

Exploring the Druggable Conformational Space of Protein Kinases Using AI-Generated Structures

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs, which enable kinases to adopt various conformational states. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the kinase conformation(s) they bind. However, the limited availability of experimentally determined structural data for kinases in inactive states restricts drug discovery efforts for this major protein family. Modern AI-based structural modeling methods hold potential for exploring the previously experimentally uncharted druggable conformational space for kinases. Here, we first evaluated the currently explored conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) (1) and ESMFold (2), two prominent AI-based structure prediction methods. We then investigated AF2's ability to predict kinase structures in different conformations at various multiple sequence alignment (MSA) depths, based on this parameter's ability to explore conformational diversity. Our results showed a bias within the PDB and predicted structural models generated by AF2 and ESMFold toward structures of kinases in the active state over alternative conformations, particularly those conformations controlled by the DFG motif. Finally, we demonstrate that predicting kinase structures using AF2 at lower MSA depths allows the exploration of the space of these alternative conformations, including identifying previously unobserved conformations for 398 kinases. The results of our analysis of structural modeling by AF2 create a new avenue for the pursuit of new therapeutic agents against a notoriously difficult-to-target family of proteins.

Significance Statement

Greater abundance of kinase structural data in inactive conformations, currently lacking in structural databases, would improve our understanding of how protein kinases function and expand drug discovery and development for this family of therapeutic targets. Modern approaches utilizing artificial intelligence and machine learning have potential for efficiently capturing novel protein conformations. We provide evidence for a bias within AlphaFold2 and ESMFold to predict structures of kinases in their active states, similar to their overrepresentation in the PDB. We show that lowering the AlphaFold2 algorithm's multiple sequence alignment depth can help explore kinase conformational space more broadly. It can also enable the prediction of hundreds of kinase structures in novel conformations, many of whose models are likely viable for drug discovery.

Pathogenic mutation hotspots in protein kinase domain structure

Control of eukaryotic cellular function is heavily reliant on the phosphorylation of proteins at specific amino acid residues, such as serine, threonine, tyrosine, and histidine. Protein kinases that are responsible for this process comprise one of the largest families of evolutionarily related proteins. Dysregulation of protein kinase signaling pathways is a frequent cause of a large variety of human diseases including cancer, autoimmune, neurodegenerative, and cardiovascular disorders. In this study, we mapped all pathogenic mutations in 497 human protein kinase domains from the ClinVar database to the reference structure of Aurora kinase A (AURKA) and grouped them by the relevance to the disease type. Our study revealed that the majority of mutation hotspots associated with cancer are situated within the catalytic and activation loops of the kinase domain, whereas non-cancer-related hotspots tend to be located outside of these regions. Additionally, we identified a hotspot at residue R371 of the AURKA structure that has the highest number of exclusively non-cancer-related pathogenic mutations (21) and has not been previously discussed.

Development and Applications of Chimera Platforms for Tyrosine Phosphorylation

Chimeric small molecules that induce post-translational modification (PTM) on a target protein by bringing it into proximity to a PTM-inducing enzyme are furnishing novel modalities to perturb protein function. Despite recent advances, such molecules are unavailable for a critical PTM, tyrosine phosphorylation. Furthermore, the contemporary design paradigm of chimeric molecules, formed by joining a noninhibitory binder of the PTM-inducing enzyme with the binder of the target protein, prohibits the recruitment of most PTM-inducing enzymes as their noninhibitory binders are unavailable. Here, we report two platforms to generate phosphorylation-inducing chimeric small molecules (PHICS) for tyrosine phosphorylation. We generate PHICS from both noninhibitory binders (scantily available, platform 1) and kinase inhibitors (abundantly available, platform 2) using cysteine-based group transfer chemistry. PHICS triggered phosphorylation on tyrosine residues in diverse sequence contexts and target proteins (e.g., membrane-associated, cytosolic) and displayed multiple bioactivities, including the initiation of a growth receptor signaling cascade and the death of drug-resistant cancer cells. These studies provide an approach to induce biologically relevant PTM and lay the foundation for pharmacologic PTM editing (i.e., induction or removal) of target proteins using abundantly available inhibitors of PTM-inducing or -erasing enzymes.

Rigid Scaffolds Are Promising for Designing Macrocyclic Kinase Inhibitors

Macrocyclic kinase inhibitors (MKIs) are gaining attention due to their favorable selectivity and potential to overcome drug resistance, yet they remain challenging to design because of their novel structures. To facilitate the design and discovery of MKIs, we investigate MKI rational design starting from initial acyclic compounds by performing microsecond-scale atomistic simulations for multiple MKIs, constructing an MKI database, and analyzing MKIs using hierarchical cluster analysis. Our studies demonstrate that the binding modes of MKIs are like those of their corresponding acyclic counterparts against the same kinase targets. Importantly, within the respective binding sites, the MKI scaffolds retain the same conformations as their corresponding acyclic counterparts, demonstrating the rigidity of scaffolds before and after molecular cyclization. The MKI database includes 641 nanomole-level MKIs from 56 human kinases elucidating the features of rigid scaffolds and the core structures of MKIs. Collectively these results and resources can facilitate MKI development.

Frequency and type of cancers in myotonic dystrophy: A retrospective cross-sectional study

INTRODUCTION/AIMS

Myotonic dystrophies (DMs) are autosomal dominant diseases in which expression of a mutant expanded repeat mRNA leads to abnormal splicing of downstream effector genes thought to be responsible for their multisystem involvement. Cancer risk and cancer-related deaths are increased in DM patients relative to the general population. We aimed at determining the frequency and type of cancers in both DM1 and DM2 vs a non-DM muscular dystrophy cohort.

METHODS

A retrospective, cross-sectional study was carried out on patients with genetically confirmed DM1, DM2, facioscapulohumeral muscular dystrophy (FSHD), and oculopharyngeal muscular dystrophy (OPMD) at our institutions from 2000 to 2020.

RESULTS

One hundred eighty-five DM1, 67 DM2, 187 FSHD, and 109 OPMD patients were included. Relative to non-DM, DM patients had an increased cancer risk that was independent of age and sex. Specifically, an increased risk of sex-related (ovarian) and non-sex-related (non-melanoma skin, urological, and hematological) cancers was observed in DM1 and DM2, respectively. The length of CTG repeat expansion was not associated with cancer occurrence in the DM1 group.

DISCUSSION

In addition to current consensus-based care recommendations, our findings prompt consideration of screening for skin, urological, and hematological cancers in DM2 patients, and screening of ovarian malignancies in DM1 female patients.

Therapeutic Potential of Protein Tyrosine Kinase 6 in Colorectal Cancer

PTK6, a non-receptor tyrosine kinase, modulates the pathogenesis of breast and prostate cancers and is recognized as a biomarker of breast cancer prognosis. There are over 30 known substrates of PTK6, including signal transducers, transcription factors, and RNA-binding proteins. Many of these substrates are known drivers of other cancer types, such as colorectal cancer. Colon and rectal tumors also express higher levels of PTK6 than the normal intestine suggesting a potential role in tumorigenesis. However, the importance of PTK6 in colorectal cancer remains unclear. PTK6 inhibitors such as XMU-MP-2 and Tilfrinib have demonstrated potency and selectivity in breast cancer cells when used in combination with chemotherapy, indicating the potential for PTK6 targeted therapy in cancer. However, most of these inhibitors are yet to be tested in other cancer types. Here, we discuss the current understanding of the function of PTK6 in normal intestinal cells compared with colorectal cancer cells. We review existing PTK6 targeting therapeutics and explore the possibility of PTK6 inhibitory therapy for colorectal cancer.

Protein posttranslational modifications in health and diseases: Functions, regulatory mechanisms, and therapeutic implications

Protein posttranslational modifications (PTMs) refer to the breaking or generation of covalent bonds on the backbones or amino acid side chains of proteins and expand the diversity of proteins, which provides the basis for the emergence of organismal complexity. To date, more than 650 types of protein modifications, such as the most well-known phosphorylation, ubiquitination, glycosylation, methylation, SUMOylation, short-chain and long-chain acylation modifications, redox modifications, and irreversible modifications, have been described, and the inventory is still increasing. By changing the protein conformation, localization, activity, stability, charges, and interactions with other biomolecules, PTMs ultimately alter the phenotypes and biological processes of cells. The homeostasis of protein modifications is important to human health. Abnormal PTMs may cause changes in protein properties and loss of protein functions, which are closely related to the occurrence and development of various diseases. In this review, we systematically introduce the characteristics, regulatory mechanisms, and functions of various PTMs in health and diseases. In addition, the therapeutic prospects in various diseases by targeting PTMs and associated regulatory enzymes are also summarized. This work will deepen the understanding of protein modifications in health and diseases and promote the discovery of diagnostic and prognostic markers and drug targets for diseases.

Angiogenic signaling pathways and anti-angiogenic therapy for cancer

Angiogenesis, the formation of new blood vessels, is a complex and dynamic process regulated by various pro- and anti-angiogenic molecules, which plays a crucial role in tumor growth, invasion, and metastasis. With the advances in molecular and cellular biology, various biomolecules such as growth factors, chemokines, and adhesion factors involved in tumor angiogenesis has gradually been elucidated. Targeted therapeutic research based on these molecules has driven anti-angiogenic treatment to become a promising strategy in anti-tumor therapy. The most widely used anti-angiogenic agents include monoclonal antibodies and tyrosine kinase inhibitors (TKIs) targeting vascular endothelial growth factor (VEGF) pathway. However, the clinical benefit of this modality has still been limited due to several defects such as adverse events, acquired drug resistance, tumor recurrence, and lack of validated biomarkers, which impel further research on mechanisms of tumor angiogenesis, the development of multiple drugs and the combination therapy to figure out how to improve the therapeutic efficacy. Here, we broadly summarize various signaling pathways in tumor angiogenesis and discuss the development and current challenges of anti-angiogenic therapy. We also propose several new promising approaches to improve anti-angiogenic efficacy and provide a perspective for the development and research of anti-angiogenic therapy.

Development of an enzyme-coupled activity assay for Janus kinase 2 inhibitor screening

JAK2 transmits signals of several important cytokines, such as growth hormone and erythropoietin. The interest toward the therapeutic targeting of JAK2 was boosted in 2005, when the somatic JAK2 V617F mutation, responsible for the majority of myeloproliferative neoplasms (MPNs) was discovered. JAK2 inhibitors have been approved for MPN therapy and they are effective in alleviating symptoms and improving the quality of life of the patients, but they do not lead to molecular remission. This calls for the discovery of new compounds for JAK2-targeted therapeutic approaches. Here we describe the development of a fluorescence-based activity assay for the screening of versatile inhibitor types against JAK2. The assay was utilized to screen a diverse set of small molecule weight natural products and the assay performance was compared to that of differential scanning fluorimetry. We identified 37 hits and further analysis of the most potent hits revealed that most of them displayed non-ATP competitive binding modes. The hits were profiled against other JAK family members and showed distinctive selectivity profiles. The developed assay is consistent, simple and inexpensive to use, and can be utilized for inhibitor screening of diverse compound classes against all JAK family members.

Chemotherapy Induced Cardiotoxicity: A State of the Art Review on General Mechanisms, Prevention, Treatment and Recent Advances in Novel Therapeutics

As medicine advances to employ sophisticated anticancer agents to treat a vast array of oncological conditions, it is worth considering side effects associated with several chemotherapeutics. One adverse effect observed with several classes of chemotherapy agents is cardiotoxicity which leads to reduced ejection fraction (EF), cardiac arrhythmias, hypertension and Ischemia/myocardial infarction that can significantly impact the quality of life and patient outcomes. Research into possible mechanisms has elucidated several mechanisms, such as ROS generation, calcium overload and apoptosis. However, there is a relative scarcity of literature detailing the relationship between the exact mechanism of cardiotoxicity for each anticancer agent and observed clinical effects. This review comprehensively describes cardiotoxicity associated with various classes of anticancer agents and possible mechanisms. Further research exploring possible mechanisms for cardiotoxicity observed with anticancer agents could provide valuable insight into susceptibility for developing symptoms and management guidelines. Chemotherapeutics are associated with several side effects. Several classes of chemotherapy agents cause cardiotoxicity leading to a reduced ejection fraction (EF), cardiac arrhythmias, hypertension, and Ischemia/myocardial infarction. Research into possible mechanisms has elucidated several mechanisms, such as ROS generation, calcium overload, and apoptosis. However, there is a relative scarcity of literature detailing the relationship between the exact mechanism of cardiotoxicity for each anticancer agent and observed clinical effects. This review describes cardiotoxicity associated with various classes of anticancer agents and possible mechanisms. Further research exploring mechanisms for cardiotoxicity observed with anticancer agents could provide insight that will guide management.

Silmitasertib (CX-4945), a Clinically Used CK2-Kinase Inhibitor with Additional Effects on GSK3β and DYRK1A Kinases: A Structural Perspective

A clinical casein kinase 2 inhibitor, CX-4945 (silmitasertib), shows significant affinity toward the DYRK1A and GSK3β kinases, involved in down syndrome phenotypes, Alzheimer's disease, circadian clock regulation, and diabetes. This off-target activity offers an opportunity for studying the effect of the DYRK1A/GSK3β kinase system in disease biology and possible line extension. Motivated by the dual inhibition of these kinases, we solved and analyzed the crystal structures of DYRK1A and GSK3β with CX-4945. We built a quantum-chemistry-based model to rationalize the compound affinity for CK2α, DYRK1A, and GSK3β kinases. Our calculations identified a key element for CK2α's subnanomolar affinity to CX-4945. The methodology is expandable to other kinase selectivity modeling. We show that the inhibitor limits DYRK1A- and GSK3β-mediated cyclin D1 phosphorylation and reduces kinase-mediated NFAT signaling in the cell. Given the CX-4945's clinical and pharmacological profile, this inhibitory activity makes it an interesting candidate with potential for application in additional disease areas.

Multi-omics analysis identifies drivers of protein phosphorylation

BACKGROUND

Phosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated.

RESULTS

We quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ~700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes.

CONCLUSIONS

Together, this integrative multi-omics analysis in genetically diverse CC strains provides a powerful tool to identify regulators of protein phosphorylation. The data generated in this study provides a resource for further exploration.

Strategy toward Kinase-Selective Drug Discovery

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

Targeting Human Proteins for Antiviral Drug Discovery and Repurposing Efforts: A Focus on Protein Kinases

Despite the great technological and medical advances in fighting viral diseases, new therapies for most of them are still lacking, and existing antivirals suffer from major limitations regarding drug resistance and a limited spectrum of activity. In fact, most approved antivirals are directly acting antiviral (DAA) drugs, which interfere with viral proteins and confer great selectivity towards their viral targets but suffer from resistance and limited spectrum. Nowadays, host-targeted antivirals (HTAs) are on the rise, in the drug discovery and development pipelines, in academia and in the pharmaceutical industry. These drugs target host proteins involved in the virus life cycle and are considered promising alternatives to DAAs due to their broader spectrum and lower potential for resistance. Herein, we discuss an important class of HTAs that modulate signal transduction pathways by targeting host kinases. Kinases are considered key enzymes that control virus-host interactions. We also provide a synopsis of the antiviral drug discovery and development pipeline detailing antiviral kinase targets, drug types, therapeutic classes for repurposed drugs, and top developing organizations. Furthermore, we detail the drug design and repurposing considerations, as well as the limitations and challenges, for kinase-targeted antivirals, including the choice of the binding sites, physicochemical properties, and drug combinations.

Kinome inhibition states and multiomics data enable prediction of cell viability in diverse cancer types

Protein kinases play a vital role in a wide range of cellular processes, and compounds that inhibit kinase activity emerging as a primary focus for targeted therapy development, especially in cancer. Consequently, efforts to characterize the behavior of kinases in response to inhibitor treatment, as well as downstream cellular responses, have been performed at increasingly large scales. Previous work with smaller datasets have used baseline profiling of cell lines and limited kinome profiling data to attempt to predict small molecule effects on cell viability, but these efforts did not use multi-dose kinase profiles and achieved low accuracy with very limited external validation. This work focuses on two large-scale primary data types, kinase inhibitor profiles and gene expression, to predict the results of cell viability screening. We describe the process by which we combined these data sets, examined their properties in relation to cell viability and finally developed a set of computational models that achieve a reasonably high prediction accuracy (R2 of 0.78 and RMSE of 0.154). Using these models, we identified a set of kinases, several of which are understudied, that are strongly influential in the cell viability prediction models. In addition, we also tested to see if a wider range of multiomics data sets could improve the model results and found that proteomic kinase inhibitor profiles were the single most informative data type. Finally, we validated a small subset of the model predictions in several triple-negative and HER2 positive breast cancer cell lines demonstrating that the model performs well with compounds and cell lines that were not included in the training data set. Overall, this result demonstrates that generic knowledge of the kinome is predictive of very specific cell phenotypes, and has the potential to be integrated into targeted therapy development pipelines.

Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches

BACKGROUND

Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed.

METHODS

In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb's free energy landscape.

RESULTS

Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors.

Application of hybrid biophysical-biochemical methods to unravel the molecular basis for auto-inhibition and activation of protein tyrosine phosphatase TCPTP/PTPN2

Since the discovery of protein tyrosine phosphorylation as one of the critical post-translational modifications, it has been well known that the activity of protein tyrosine kinases (PTKs) is tightly regulated. On the other hand, protein tyrosine phosphatases (PTPs) are often regarded to act constitutively active, but recently we and others have shown that many PTPs are expressed in an inactive form due to allosteric inhibition by their unique structural features. Furthermore, their cellular activity is highly regulated in a spatiotemporal manner. In general, PTPs share a conserved catalytic domain comprising about 280 residues that is flanked by either an N-terminal or a C-terminal non-catalytic segment, which differs significantly in size and structure from each other and is known to regulate specific PTP's catalytic activity. The well-characterized non-catalytic segments can be globular or intrinsically disordered. In this work, we have focused on the T-Cell Protein Tyrosine Phosphatase (TCPTP/PTPN2) and demonstrated how the hybrid biophysical-biochemical methods can be applied to unravel the underlying mechanism through which TCPTP's catalytic activity is regulated by the non-catalytic C-terminal segment. Our analysis showed that TCPTP is auto-inhibited by its intrinsically disordered tail and trans-activated by Integrin alpha-1's cytosolic region.

Can Nanomedicinal Approaches Provide an Edge to the Efficacy of Tyrosine Kinase Inhibitors?

Tyrosine kinase inhibitors (TKIs) are effective drug molecules for the treatment of various cancers. Nanomedicinal interventions and approaches may not only provide carrying capacities for TKIs but also potentially target tumor-specific environments and even cellular compartments. Nano-inspired drug delivery systems may hence enhance the efficacy of the drugs through enhanced tumour-availability resulting in greater efficacy and decreased side effects. A variety of nanosystems have been developed for the delivery of TKIs for the enhanced treatment of cancers, each with their own preparation methods and physicochemical properties. This review will therefore discuss the applicability of nano-interventions towards combination therapies, dose reduction, and greater potential treatment outcomes. The individual nanosystems have been highlighted with emphasis on the developed systems and their efficacy against various cancer cell lines and models.

Active-site cysteine 215 sulfonation targets protein tyrosine phosphatase PTP1B for Cullin1 E3 ligase-mediated degradation

Reactive oxygen species (ROS), released as byproducts of mitochondrial metabolism or as products of NADPH oxidases and other processes, can directly oxidize the active-site cysteine (Cys) residue of protein tyrosine phosphatases (PTPs) in a mammalian cell. Robust degradation of irreversibly oxidized PTPs is essential for preventing accumulation of these permanently inactive enzymes. However, the mechanism underlying the degradation of these proteins was unknown. In this study, we found that the active-site Cys215 of endogenous PTP1B is sulfonated in H9c2 cardiomyocytes under physiological conditions. The sulfonation of Cys215 led PTP1B to exhibit a conformational change, and drive the subsequent ubiquitination and degradation of this protein. We then discovered that Cullin1, an E3 ligase, interacts with the Cys215-sulfonated PTP1B. The functional impairment of Cullin1 prevented PTP1B from oxidation-dependent ubiquitination and degradation in H9c2 cells. Moreover, delivery of the terminally oxidized PTP1B resulted in proteotoxicity-caused injury in the affected cells. In conclusion, we elucidate how sulfonation of the active-site Cys215 can direct turnover of endogenous PTP1B through the engagement of ubiquitin-proteasome system. These data highlight a novel mechanism that maintains PTP homeostasis in cardiomyocytes with constitutive ROS production.

An atlas of substrate specificities for the human serine/threonine kinome

Protein phosphorylation is one of the most widespread post-translational modifications in biology1,2. With advances in mass-spectrometry-based phosphoproteomics, 90,000 sites of serine and threonine phosphorylation have so far been identified, and several thousand have been associated with human diseases and biological processes3,4. For the vast majority of phosphorylation events, it is not yet known which of the more than 300 protein serine/threonine (Ser/Thr) kinases encoded in the human genome are responsible3. Here we used synthetic peptide libraries to profile the substrate sequence specificity of 303 Ser/Thr kinases, comprising more than 84% of those predicted to be active in humans. Viewed in its entirety, the substrate specificity of the kinome was substantially more diverse than expected and was driven extensively by negative selectivity. We used our kinome-wide dataset to computationally annotate and identify the kinases capable of phosphorylating every reported phosphorylation site in the human Ser/Thr phosphoproteome. For the small minority of phosphosites for which the putative protein kinases involved have been previously reported, our predictions were in excellent agreement. When this approach was applied to examine the signalling response of tissues and cell lines to hormones, growth factors, targeted inhibitors and environmental or genetic perturbations, it revealed unexpected insights into pathway complexity and compensation. Overall, these studies reveal the intrinsic substrate specificity of the human Ser/Thr kinome, illuminate cellular signalling responses and provide a resource to link phosphorylation events to biological pathways.

Analysis of DYRK1B, PPARG, and CEBPB Expression Patterns in Adipose-Derived Stem Cells from Patients Carrying DYRK1B R102C and Healthy Individuals During Adipogenesis

Background: Metabolic syndrome (MetS) is a group of signs and symptoms that are associated with a higher risk of type 2 diabetes mellitus and cardiovascular diseases. The major risk factor for developing MetS is abdominal obesity, which is caused by an increase in adipocyte size or quantity. Increased adipocyte quantity is a result of differentiation of stem cells into adipose tissue. Numerous studies have investigated the expression of key transcription factors, including PPARG and CEBPB during adipocyte differentiation in murine cells such as 3T3-L1 cell lines. To better understand the expression changes during the process of fat accumulation in adipose-derived stem cells (ASCs), we compared the expression of DYRK1B, PPARG, and ẟB in ASCs between the patient (harboring DYRK1B R102C) and control (healthy individuals) groups. Methods: Gene expression was evaluated on the eighth day before induction and days 1, 5, and 15 postinduction. The pluripotent capacity of ASCs and the potential for differentiation into adipocytes were confirmed by flow cytometry analysis of surface markers (CD34, CD44, CD105, and CD90), and Oil Red O staining, respectively. The Expression of DYRK1B, PPARG, and CEBPB were assessed by real-time-polymerase chain reaction in patients and normal individuals. The effects of AZ191, a potent small molecule inhibitor on DYRK1B and CEBPB expression in patients' samples were studied. Result: The expression of DYRK1B kinase and transcription factors (CEBPB and PPARG) are higher in ASCs harboring DYRK1B R102C compared with noncarriers on days 5 and 15 during adipocyte differentiation. These proteins may be helpful to elucidate the mechanisms underlying obesity and obesity-related disorders like MetS. Furthermore, the new compound AZ191 exhibited inhibitory activity toward DYRK1B and CEBPB. We suggest that AZ191 may be helpful in defining the potential roles of DYRK1B and CEBPB in adipogenesis.

Evolutionary Divergence of Phosphorylation to Regulate Interactive Protein Networks in Lower and Higher Species

The phosphorylation of proteins affects their functions in extensively documented circumstances. However, the role of phosphorylation in many interactive networks of proteins remains very elusive due to the experimental limits of exploring the transient interaction in a large complex of assembled proteins induced by stimulation. Previous studies have suggested that phosphorylation is a recent evolutionary process that differently regulates ortholog proteins in numerous lineages of living organisms to create new functions. Despite the fact that numerous phospho-proteins have been compared between species, little is known about the organization of the full phospho-proteome, the role of phosphorylation to orchestrate large interactive networks of proteins, and the intertwined phospho-landscape in these networks. In this report, we aimed to investigate the acquired role of phosphate addition in the phenomenon of protein networking in different orders of living organisms. Our data highlighted the acquired status of phosphorylation in organizing large, connected assemblages in Homo sapiens. The protein networking guided by phosphorylation turned out to be prominent in humans, chaotic in yeast, and weak in flies. Furthermore, the molecular functions of GO annotation enrichment regulated by phosphorylation were found to be drastically different between flies, yeast, and humans, suggesting an evolutionary drift specific to each species.

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.

Accessing isotopically labeled proteins containing genetically encoded phosphoserine for NMR with optimized expression conditions

Phosphoserine (pSer) sites are primarily located within disordered protein regions, making it difficult to experimentally ascertain their effects on protein structure and function. Therefore, the production of ¹⁵N- (and ¹³C)-labeled proteins with site-specifically encoded pSer for NMR studies is essential to uncover molecular mechanisms of protein regulation by phosphorylation. While genetic code expansion technologies for the translational installation of pSer in Escherichia coli are well established and offer a powerful strategy to produce site-specifically phosphorylated proteins, methodologies to adapt them to minimal or isotope-enriched media have not been described. This shortcoming exists because pSer genetic code expansion expression hosts require the genomic ΔserB mutation, which increases pSer bioavailability but also imposes serine auxotrophy, preventing growth in minimal media used for isotopic labeling of recombinant proteins. Here, by testing different media supplements, we restored normal BL21(DE3) ΔserB growth in labeling media but subsequently observed an increase of phosphatase activity and mis-incorporation not typically seen in standard rich media. After rounds of optimization and adaption of a high-density culture protocol, we were able to obtain ≥10 mg/L homogenously labeled, phosphorylated superfolder GFP. To demonstrate the utility of this method, we also produced the intrinsically disordered serine/arginine-rich region of the SARS-CoV-2 Nucleocapsid protein labeled with ¹⁵N and pSer at the key site S188 and observed the resulting peak shift due to phosphorylation by 2D and 3D heteronuclear single quantum correlation analyses. We propose this cost-effective methodology will pave the way for more routine access to pSer-enriched proteins for 2D and 3D NMR analyses.

Validation of an allosteric binding site of Src kinase identified by unbiased ligand binding simulations

Allostery plays a primary role in regulating protein activity, making it an important mechanism in human disease and drug discovery. Identifying allosteric regulatory sites to explore their biological significance and therapeutic potential is invaluable to drug discovery; however, identification remains a challenge. Allosteric sites are often "cryptic" without clear geometric or chemical features. Since allosteric regulatory sites are often less conserved in protein kinases than the orthosteric ATP binding site, allosteric ligands are commonly more specific than ATP competitive inhibitors. We present a generalizable computational protocol to predict allosteric ligand binding sites based on unbiased ligand binding simulation trajectories. We demonstrate the feasibility of this protocol by revisiting our previously published ligand binding simulations using the first identified viral proto-oncogene, Src kinase, as a model system. The binding paths for kinase inhibitor PP1 uncovered three metastable intermediate states before binding the high-affinity ATP-binding pocket, revealing two previously known allosteric sites and one novel site. Herein, we validate the novel site using a combination of virtual screening and experimental assays to identify a v-type allosteric small-molecule inhibitor that targets this novel site with specificity for Src over closely related kinases. This study provides a proof-of-concept for employing unbiased ligand binding simulations to identify cryptic allosteric binding sites and is widely applicable to other protein-ligand systems.

Naphthoquinone as a New Chemical Scaffold for Leishmanicidal Inhibitors of Leishmania GSK-3

More than 1 billion people live in areas endemic for leishmaniasis, which is a relevant threat for public health worldwide. Due to the inadequate treatments, there is an urgent need to develop novel alternative drugs and to validate new targets to fight this disease. One appealing approach is the selective inhibition of protein kinases (PKs), enzymes involved in a wide range of processes along the life cycle of Leishmania. Several PKs, including glycogen synthase kinase 3 (GSK-3), have been validated as essential for this parasite by genetic or pharmacological methods. Recently, novel chemical scaffolds have been uncovered as Leishmania GSK-3 inhibitors with antiparasitic activity. In order to find new inhibitors of this enzyme, a virtual screening of our in-house chemical library was carried out on the structure of the Leishmania GSK-3. The virtual hits identified were experimentally assayed both for leishmanicidal activity and for in vitro inhibition of the enzyme. The best hits have a quinone scaffold. Their optimization through a medicinal chemistry approach led to a set of new compounds, provided a frame to establish biochemical and antiparasitic structure–activity relationships, and delivered molecules with an improved selectivity index. Altogether, this study paves the way for a systemic search of this class of inhibitors for further development as potential leishmanicidal drugs.

A suite of in vitro and in vivo assays for monitoring the activity of the pseudokinase Bud32

Bud32 is a member of the protein kinase superfamily that is invariably conserved in all eukaryotic and archaeal organisms. In both of these kingdoms, Bud32 forms part of the KEOPS (Kinase, Endopeptidase and Other Proteins of Small size) complex together with the three other core subunits Kae1, Cgi121 and Pcc1. KEOPS functions to generate the universal and essential tRNA post-transcriptional modification N⁶-theronylcarbamoyl adenosine (t⁶A), which is present at position A37 in all tRNAs that bind to codons with an A in the first position (ANN decoding tRNAs) and is essential for the fidelity of translation. Mutations in KEOPS genes in humans underlie the severe genetic disease Galloway-Mowat syndrome, which results in childhood death. KEOPS activity depends on two major functions of Bud32. Firstly, Bud32 facilitates efficient tRNA substrate recruitment to KEOPS and helps in positioning the A37 site of the tRNA in the active site of Kae1, which carries out the t⁶A modification reaction. Secondly, the enzymatic activity of Bud32 is required for the ability of KEOPS to modify tRNA. Unlike conventional protein kinases, which employ their enzymatic activity for phosphorylation of protein substrates, Bud32 employs its enzymatic activity to function as an ATPase. Herein, we present a comprehensive suite of assays to monitor the activity of Bud32 in KEOPS in vitro and in vivo. We present protocols for the purification of the archaeal KEOPS proteins and of a tRNA substrate, as well as protocols for monitoring the ATPase activity of Bud32 and for analyzing its role in tRNA binding. We further present a complementary protocol for monitoring the role Bud32 has in cell growth in yeast.

Interrogating Kinase-Substrate Relationships with Proximity Labeling and Phosphorylation Enrichment

Kinases govern many cellular responses through the reversible transfer of a phosphate moiety to their substrates. However, pairing a substrate with a kinase is challenging. In proximity labeling experiments, proteins proximal to a target protein are marked by biotinylation, and mass spectrometry can be used for their identification. Here, we combine ascorbate peroxidase (APEX) proximity labeling and a phosphorylation enrichment-based workflow, Phospho-APEX (pAPEX), to rapidly identify phosphorylated and biotinylated neighbor proteins which can be considered for candidate substrates. The pAPEX strategy enriches and quantifies differences in proximity for proteins and phosphorylation sites proximal to an APEX2-tagged kinase under the kinase "ON" and kinase "OFF" conditions. As a proof of concept, we identified candidate substrates of MAPK1 in HEK293T and HCT116 cells and candidate substrates of PKA in HEK293T cells. In addition to many known substrates, C15orf39 was identified and confirmed as a novel MAPK1 substrate. In all, we adapted the proximity labeling-based platform to accommodate phosphorylation analysis for kinase substrate identification.

A Gain-of-Function Mutation on BCKDK Gene and Its Possible Pathogenic Role in Branched-Chain Amino Acid Metabolism

BCKDK is an important key regulator of branched-chain ketoacid dehydrogenase complex activity by phosphorylating and so inactivating branched-chain ketoacid dehydrogenases, the rate-limiting enzyme of the branched-chain amino acid metabolism. We identified, by whole exome-sequencing analysis, the p.His162Gln variant of the BCKDK gene in a neonate, picked up by newborn screening, with a biochemical phenotype of a mild form of maple syrup urine disease (MSUD). The same biochemical and genetic picture was present in the father. Computational analysis of the mutation was performed to better understand its role. Extensive atomistic molecular dynamics simulations showed that the described mutation leads to a conformational change of the BCKDK protein, which reduces the effect of inhibitory binding bound to the protein itself, resulting in its increased activity with subsequent inactivation of BCKDC and increased plasmatic branched-chain amino acid levels. Our study describes the first evidence of the involvement of the BCKDK gene in a mild form of MSUD. Although further data are needed to elucidate the clinical relevance of the phenotype caused by this variant, awareness of this regulatory activation of BCKDK is very important, especially in newborn screening data interpretation.

Advancements, Challenges, and Future Directions in Tackling Glioblastoma Resistance to Small Kinase Inhibitors

Simple Summary

Drug resistance is a major issue in brain tumor therapy. Despite novel promising therapeutic approaches, glioblastoma (GBM) remains refractory in showing beneficial responses to anticancer agents, as demonstrated by the failure in clinical trials of small kinase inhibitors. One of the reasons may lie in the development of different types of drug resistance mechanisms derived from the intrinsic heterogeneous nature of GBM. Obtaining insights into these mechanisms could improve the management of the clinical intervention and monitoring. Such insights could be achieved with the improvement of preclinical in vitro models for studying drug resistance.

Abstract

Despite clinical intervention, glioblastoma (GBM) remains the deadliest brain tumor in adults. Its incurability is partly related to the establishment of drug resistance, both to standard and novel treatments. In fact, even though small kinase inhibitors have changed the standard clinical practice for several solid cancers, in GBM, they did not fulfill this promise. Drug resistance is thought to arise from the heterogeneity of GBM, which leads the development of several different mechanisms. A better understanding of the evolution and characteristics of drug resistance is of utmost importance to improve the current clinical practice. Therefore, the development of clinically relevant preclinical in vitro models which allow careful dissection of these processes is crucial to gain insights that can be translated to improved therapeutic approaches. In this review, we first discuss the heterogeneity of GBM, which is reflected in the development of several resistance mechanisms. In particular, we address the potential role of drug resistance mechanisms in the failure of small kinase inhibitors in clinical trials. Finally, we discuss strategies to overcome therapy resistance, particularly focusing on the importance of developing in vitro models, and the possible approaches that could be applied to the clinic to manage drug resistance.

Unraveling unique and common cell type-specific mechanisms in glioblastoma multiforme

Glioblastoma multiforme persists to be an enigmatic distress in neuro-oncology. Its untethering capacity to thrive in a confined microenvironment, metastasize intracranially, and remain resistant to the systemic treatments, renders this tumour incurable. The glial cell type specificity in GBM remains exploratory. In our study, we aimed to address this problem by studying the GBM at the cell type level in the brain. The cellular makeup of this tumour is composed of genetically altered glial cells which include astrocyte, microglia, oligodendrocyte precursor cell, newly formed oligodendrocyte and myelinating oligodendrocyte. We extracted cell type-specific solid tumour as well as recurrent solid tumour glioma genes, and studied their functional networks and contribution towards gliomagenesis. We identified the principal transcription factors that are found to be regulating vital tumorigenic processes. We also assessed the protein-protein interaction networks at their domain level to get a more microscopic view of the structural and functional operations that transpire in these cells. This yielded the eminent protein regulators exhibiting their regulation in signaling pathways. Overall, our study unveiled regulatory mechanisms in glioma cell types that can be targeted for a more efficient glioma therapy.

KRSA: An R package and R Shiny web application for an end-to-end upstream kinase analysis of kinome array data

Phosphorylation by serine-threonine and tyrosine kinases is critical for determining protein function. Array-based platforms for measuring reporter peptide signal levels allow for differential phosphorylation analysis between conditions for distinct active kinases. Peptide array technologies like the PamStation12 from PamGene allow for generating high-throughput, multi-dimensional, and complex functional proteomics data. As the adoption rate of such technologies increases, there is an imperative need for software tools that streamline the process of analyzing such data. We present Kinome Random Sampling Analyzer (KRSA), an R package and R Shiny web-application for analyzing kinome array data to help users better understand the patterns of functional proteomics in complex biological systems. KRSA is an All-In-One tool that reads, formats, fits models, analyzes, and visualizes PamStation12 kinome data. While the underlying algorithm has been experimentally validated in previous publications, we demonstrate KRSA workflow on dorsolateral prefrontal cortex (DLPFC) in male (n = 3) and female (n = 3) subjects to identify differential phosphorylation signatures and upstream kinase activity. Kinase activity differences between males and females were compared to a previously published kinome dataset (11 female and 7 male subjects) which showed similar global phosphorylation signals patterns.