Kinase mutations in human disease: interpreting genotype-phenotype relationships

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.

Molecular hybrids: A five-year survey on structures of multiple targeted hybrids of protein kinase inhibitors for cancer therapy

Protein kinases have grown over the past few years as a crucial target for different cancer types. With the multifactorial nature of cancer, and the fast development of drug resistance for conventional chemotherapeutics, a strategy for designing multi-target agents was suggested to potentially increase drug efficacy, minimize side effects and retain the proper pharmacokinetic properties. Kinase inhibitors were used extensively in such strategy. Different kinase inhibitor agents which target EGFR, VEGFR, c-Met, CDK, PDK and other targets were merged into hybrids with conventional chemotherapeutics such as tubulin polymerization and topoisomerase inhibitors. Other hybrids were designed gathering kinase inhibitors with targeted cancer therapy such as HDAC, PARP, HSP 90 inhibitors. Nitric oxide donor molecules were also merged with kinase inhibitors for cancer therapy. The current review presents the hybrids designed in the past five years discussing their design principles, results and highlights their future perspectives.

Characterizing the role of the dark kinome in neurodegenerative disease - A mini review

BACKGROUND

Drugs that modulate previously unexplored targets could potentially slow or halt the progression of neurodegenerative diseases. Several candidate proteins lie within the dark kinome, those human kinases that have not been well characterized. Much of the kinome (~80%) remains poorly studied, and these targets likely harbor untapped biological potential.

SCOPE OF REVIEW

This review highlights the significance of kinases as mediators of aberrant pathways in neurodegeneration and provides examples of published high-quality small molecules that modulate some of these kinases.

MAJOR CONCLUSIONS

There is a need for continued efforts to develop high-quality chemical tools to illuminate the function of understudied kinases in the brain. Potent and selective small molecules enable accurate pairing of an observed phenotype with a protein target.

GENERAL SIGNIFICANCE

The examples discussed herein support the premise that validation of therapeutic hypotheses surrounding kinase targets can be accomplished via small molecules and they can serve as the basis for disease-focused drug development campaigns.

Computational Analysis of Cholangiocarcinoma Phosphoproteomes Identifies Patient-Specific Drug Targets

Cholangiocarcinoma is a form of hepatobiliary cancer with an abysmal prognosis. Despite advances in our understanding of cholangiocarcinoma pathophysiology and its genomic landscape, targeted therapies have not yet made a significant impact on its clinical management. The low response rates of targeted therapies in cholangiocarcinoma suggest that patient heterogeneity contributes to poor clinical outcome. Here we used mass spectrometry-based phosphoproteomics and computational methods to identify patient-specific drug targets in patient tumors and cholangiocarcinoma-derived cell lines. We analyzed 13 primary tumors of patients with cholangiocarcinoma with matched nonmalignant tissue and 7 different cholangiocarcinoma cell lines, leading to the identification and quantification of more than 13,000 phosphorylation sites. The phosphoproteomes of cholangiocarcinoma cell lines and patient tumors were significantly correlated. MEK1, KIT, ERK1/2, and several cyclin-dependent kinases were among the protein kinases most frequently showing increased activity in cholangiocarcinoma relative to nonmalignant tissue. Application of the Drug Ranking Using Machine Learning (DRUML) algorithm selected inhibitors of histone deacetylase (HDAC; belinostat and CAY10603) and PI3K pathway members as high-ranking therapies to use in primary cholangiocarcinoma. The accuracy of the computational drug rankings based on predicted responses was confirmed in cell-line models of cholangiocarcinoma. Together, this study uncovers frequently activated biochemical pathways in cholangiocarcinoma and provides a proof of concept for the application of computational methodology to rank drugs based on efficacy in individual patients. SIGNIFICANCE: Phosphoproteomic and computational analyses identify patient-specific drug targets in cholangiocarcinoma, supporting the potential of a machine learning method to predict personalized therapies.

Identification of Novel Kinase-Transcription Factor-mRNA-miRNA Regulatory Network in Nasopharyngeal Carcinoma by Bioinformatics Analysis

Purpose

Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck. This study aimed to investigate the crucial genes and regulatory networks involved in the carcinogenesis of NPC using a bioinformatics approach.

Methods

Five mRNA and two miRNA expression datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between NPC and normal samples were analyzed using R software. The WebGestalt tool was used for functional enrichment analysis, and protein-protein interaction (PPI) network analysis of DEGs was performed using STRING database. Transcription factors (TFs) were predicted using TRRUST and Transcriptional Regulatory Element Database (TRED). Kinases were identified using X2Kgui. The miRNAs of DEGs were predicted using miRWalk database. A kinase-TF-mRNA-miRNA integrated network was constructed, and hub nodes were selected. The hub genes were validated using NPC datasets from the GEO and Oncomine databases. Finally, candidate small-molecule agents were predicted using CMap.

Results

A total of 122 DEGs and 44 DEMs were identified. DEGs were associated with the immune response, leukocyte activation, endoplasmic reticulum stress in GO analysis, and the NF-κB signaling pathway in KEGG analysis. Four significant modules were identified using PPI network analysis. Subsequently, 26 TFs, 73 kinases, and 2499 miRNAs were predicted. The predicted miRNAs were cross-referenced with DEMs, and seven overlapping miRNAs were selected. In the kinase-TF-mRNA-miRNA integrated network, eight genes (PTGS2, FN1, MMP1, PLAU, MMP3, CD19, BMP2, and PIGR) were identified as hub genes. Hub genes were validated with consistent results, indicating the reliability of our findings. Finally, six candidate small-molecule agents (phenoxybenzamine, luteolin, thioguanosine, reserpine, blebbistatin, and camptothecin) were predicted.

Conclusion

We identified DEGs and an NPC regulatory network involving kinases, TFs, mRNAs, and miRNAs, which might provide promising insight into the pathogenesis, treatment, and prognosis of NPC.

Trends in kinase drug discovery: targets, indications and inhibitor design

The FDA approval of imatinib in 2001 was a breakthrough in molecularly targeted cancer therapy and heralded the emergence of kinase inhibitors as a key drug class in the oncology area and beyond. Twenty years on, this article analyses the landscape of approved and investigational therapies that target kinases and trends within it, including the most popular targets of kinase inhibitors and their expanding range of indications. There are currently 71 small-molecule kinase inhibitors (SMKIs) approved by the FDA and an additional 16 SMKIs approved by other regulatory agencies. Although oncology is still the predominant area for their application, there have been important approvals for indications such as rheumatoid arthritis, and one-third of the SMKIs in clinical development address disorders beyond oncology. Information on clinical trials of SMKIs reveals that approximately 110 novel kinases are currently being explored as targets, which together with the approximately 45 targets of approved kinase inhibitors represent only about 30% of the human kinome, indicating that there are still substantial unexplored opportunities for this drug class. We also discuss trends in kinase inhibitor design, including the development of allosteric and covalent inhibitors, bifunctional inhibitors and chemical degraders.

Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches

The protein kinase family contains many promising drug targets. Many kinase inhibitors target the ATP-binding pocket, leading to approved drugs in past decades. Scaffold hopping is an effective approach for drug design. The kinase ATP-binding pocket is highly conserved, crossing the whole kinase family. This provides an opportunity to develop a scaffold hopping approach to explore diversified scaffolds among various kinase inhibitors. In this work, we report the SyntaLinker-Hybrid scheme for kinase inhibitor scaffold hopping. With this scheme, we replace molecular fragments bound at the conserved kinase hinge region with deep generative models. Thus, we are able to generate new kinase-inhibitor-like structures hybridizing the privileged fragments against the hinge region. We demonstrate that this scheme allows generation of kinase-inhibitor-like molecules with novel scaffolds, while retaining the binding features of existing kinase inhibitors. This work can be employed in lead identification against kinase targets.

Small Molecule Kinase Inhibitor Drugs (1995-2021): Medical Indication, Pharmacology, and Synthesis

The central role of dysregulated kinase activity in the etiology of progressive disorders, including cancer, has fostered incremental efforts on drug discovery programs over the past 40 years. As a result, kinase inhibitors are today one of the most important classes of drugs. The FDA approved 73 small molecule kinase inhibitor drugs until September 2021, and additional inhibitors were approved by other regulatory agencies during that time. To complement the published literature on clinical kinase inhibitors, we have prepared a review that recaps this large data set into an accessible format for the medicinal chemistry community. Along with the therapeutic and pharmacological properties of each kinase inhibitor approved across the world until 2020, we provide the synthesis routes originally used during the discovery phase, many of which were only available in patent applications. In the last section, we also provide an update on kinase inhibitor drugs approved in 2021.

RNA editing restricts hyperactive ciliary kinases

Protein kinase activity must be precisely regulated, but how a cell governs hyperactive kinases remains unclear. In this study, we generated a constitutively active mitogen-activated protein kinase DYF-5 (DYF-5CA) in Caenorhabditis elegans that disrupted sensory cilia. Genetic suppressor screens identified that mutations of ADR-2, an RNA adenosine deaminase, rescued ciliary phenotypes of dyf-5CA We found that dyf-5CA animals abnormally transcribed antisense RNAs that pair with dyf-5CA messenger RNA (mRNA) to form double-stranded RNA, recruiting ADR-2 to edit the region ectopically. RNA editing impaired dyf-5CA mRNA splicing, and the resultant intron retentions blocked DYF-5CA protein translation and activated nonsense-mediated dyf-5CA mRNA decay. The kinase RNA editing requires kinase hyperactivity. The similar RNA editing-dependent feedback regulation restricted the other ciliary kinases NEKL-4/NEK10 and DYF-18/CCRK, which suggests a widespread mechanism that underlies kinase regulation.

Drugging the Undruggable: How Isoquinolines and PKA Initiated the Era of Designed Protein Kinase Inhibitor Therapeutics

In 1984, Japanese researchers led by the biochemist Hiroyoshi Hidaka described the first synthetic protein kinase inhibitors based on an isoquinoline sulfonamide structure (Hidaka et al. Biochemistry, 1984 Oct 9; 23(21): 5036-41. doi: 10.1021/bi00316a032). These led to the first protein kinase inhibitor approved for medical use (fasudil), an inhibitor of the AGC subfamily Rho kinase. With potencies strong enough to compete against endogenous ATP, the isoquinoline compounds established the druggability of the ATP binding site. Crystal structures of their protein kinase complexes, including with cAMP-dependent protein kinase (PKA), showed interactions that, on the one hand, could mimic ATP but, on the other hand, could be optimized for high potency binding, kinase selectivity, and diversification away from adenosine. They also showed the flexibility of the glycine-rich loop, and PKA became a major prototype for crystallographic and nuclear magnetic resonance (NMR) studies of protein kinase mechanism and dynamic activity control. Since fasudil, more than 70 kinase inhibitors have been approved for clinical use, involving efforts that progressively have introduced new paradigms of data-driven drug discovery. Publicly available data alone comprise over 5000 protein kinase crystal structures and hundreds of thousands of binding data. Now, new methods, including artificial intelligence techniques and expansion of protein kinase targeting approaches, together with the expiration of patent protection for optimized inhibitor scaffolds, promise even greater advances in drug discovery. Looking back to the time of the first isoquinoline hinge binders brings the current state-of-the-art into stark contrast. Appropriately for this Perspective article, many of the milestone papers during this time were published in Biochemistry (now ACS Biochemistry).

Structure-Activity Studies of Novel di-substituted [1,2,5]oxadiazolo[3,4-b]pyrazine Analogs Targeting the A-loop Regulatory Site of p38 MAP Kinase

INTRODUCTION

In the quest for novel allosteric inhibitors of the p38 MAP kinase, we recently described the A-loop regulatory site, identified through molecular modeling studies together with the disclosure of a small molecule hit with a moderate inhibitory profile. Starting from this structure, we subsequently identified two additional hits with simpler molecular structures from an in silico screening study, using a substructure search in the SciFinder database. After corroboration of their inhibitory profile, analysis of their structures permitted to conclude about the suitability of the [1,2,5]oxadiazolo[3,4-b]pyrazine (furazano[3,4-b]pyrazine) scaffold for the development of potent A-loop regulatory site p38 MAP kinase inhibitors. Accordingly, we report the synthesis and pharmacological evaluation of a series of di-substituted analogs with a potent inhibitory profile of p38 MAP kinase, as shown by in vitro assays of their capability to inhibit IL-1β secretion in human monocyte-derived macrophages.

BACKGROUND

In the quest for novel allosteric inhibitors of the p38 MAP kinase, we recently described the A-loop regulatory site, identified through molecular modeling studies together with the disclosure of a small molecule hit with a moderate inhibitory profile.

OBJECTIVE

To find small molecule potent inhibitors of the p38 MAP kinase A-loop regulatory site.

METHODS

Starting from this structure, we subsequently identified two additional hits with simpler molecular structures from an in silico screening study, using a substructure search in the SciFinder database. After corroboration of their inhibitory profile, we carried out a hit-to-lead optimization process guided by molecular modeling using a [1,2,5]oxadiazolo[3,4-b]pyrazine (furazano[3,4-b]pyrazine) scaffold.

RESULTS

We report the synthesis and pharmacological evaluation of a series of di-substituted analogs with a potent inhibitory profile of p38 MAP kinase, as shown by in vitro assays of their capability to inhibit IL-1β secretion in human monocyte-derived macrophages.

CONCLUSIONS

We describe in the present work a series of [1,2,5]oxadiazolo[3,4-b]pyrazine (furazano[3,4-b]pyrazine), potent inhibitors of IL-1β secretion in human monocyte-derived macrophages allosteric modulators of the p38 MAP kinase A-loop regulatory site.

Spatiotemporally resolved subcellular phosphoproteomics

Proteome-wide profiling of protein phosphorylation has been widely used to reveal the underlying mechanism of diverse cellular signaling events. Yet, characterizing subcellular phosphoproteome with high spatial-temporal resolution has remained challenging. Herein, we developed a subcellular-specific uncaging-assisted biotinylation and mapping of phosphoproteome (SubMAPP) strategy to monitor the phosphorylation dynamics of subcellular proteome in living cells and animals. Our method capitalizes on the genetically encoded bioorthogonal decaging strategy, which enables the rapid activation of subcellular localized proximity labeling biotin ligase through either light illumination or small-molecule triggers. By further adopting an integrated orthogonal pull-down strategy with quantitative mass spectrometry, SubMAPP allowed for the investigation of subcellular phosphoproteome dynamics, revealing the altered phosphorylation patterns of endoplasmic reticulum (ER) luminal proteins under ER stress. Finally, we further expanded the scope of the SubMAPP strategy to primary neuron culture and living mice.

Targeted Therapies in Lung Cancers: Current Landscape and Future Prospects

BACKGROUND

Lung cancer is the most common and malignant cancer worldwide. Targeted therapies have emerged as a promising treatment strategy for lung cancers.

OBJECTIVE

The objective of this study is to evaluate the current landscape of targets and finding promising targets for future new drug discovery for lung cancers by identifying the science-technology-clinical development pattern and mapping the interaction network of targets.

METHODS

Targets for cancers were classified into 3 groups based on a paper published in Nature. We search for scientific literature, patent documents and clinical trials of targets in Group 1 and Group 2 for lung cancers. Then, a target-target interaction network of Group 1 was constructed, and the science-technology-clinical(S-T-C) development patterns of targets in Group 1 were identified. Finally, based on the cluster distribution and the development pattern of targets in Group 1, interactions between the targets were employed to predict potential targets in Group 2 on drug development.

RESULTS

The target-target interaction(TTI)network of group 1 resulted in 3 clusters with different developmental stages. The potential targets in Group 2 are divided into 3 ranks. Level-1 is the first priority and level-3 is the last. Level-1 includes 16 targets, such as STAT3, CRKL, and PTPN11, that are mostly involved in signaling transduction pathways. Level-2 and level-3 contain 8 and 6 targets related to various biological functions.

CONCLUSION

This study will provide references for drug development in lung cancers, emphasizing that priorities should be given to targets in Level-1, whose mechanisms are worth further exploration.

Chemical probes targeting the kinase CK2: a journey outside the catalytic box

CK2 is a protein kinase that plays important roles in many physio-pathological cellular processes. As such, the development of chemical probes for CK2 has received increasing attention in the past decade with more than 40 lead compounds developed. In this review, we aim to provide the reader with a comprehensive overview of the chemical probes acting outside the highly-conserved ATP-site developed to date. Such probes belong to different classes of molecules spanning from small molecules to peptides, act with a range of mechanisms of action and some of them present themselves as promising tools to investigate the biology of CK2 and therefore develop therapeutics for many disease areas including cancer and COVID-19.

Validation of ion mobility spectrometry - mass spectrometry as a screening tool to identify type II kinase inhibitors of FGFR1 kinase

RATIONALE

The protein kinase FGFR1 regulates cellular processes in human development. As over-activity of FGFR1 is implicated with cancer, effective inhibitors are in demand. Type I inhibitors, which bind to the active form of FGFR1, are less effective than type II inhibitors, which bind to the inactive form. Screening to distinguish between type I and type II inhibitors is required.

METHODS

X-ray crystallography was used to indicate whether a range of potential inhibitors bind to the active or inactive FGFR1 kinase conformation. The binding affinity of each ligand to FGFR1 was measured using biochemical methods. Electrospray ionisation - ion mobility spectrometry - mass spectrometry (ESI-IMS-MS) in conjunction with collision-induced protein unfolding generated a conformational profile of each FGFR1-ligand complex. The results indicate that the protein's conformational profile depends on whether the inhibitor is type I or type II.

RESULTS

X-ray crystallography confirmed which of the kinase inhibitors bind to the active or inactive form of FGFR1 kinase. Collision-induced unfolding combined with ESI-IMS-MS showed distinct differences in the FGFR1 folding landscape for type I and type II inhibitors. Biochemical studies indicated a similar range of FGFR1 affinities for both types of inhibitors, thus providing confidence that the conformational variations detected using ESI-IMS-MS can be interpretated unequivocally and that this is an effective screening method.

CONCLUSIONS

A robust ESI-IMS-MS method has been implemented to distinguish between the binding mode of type I and type II inhibitors by monitoring the conformational unfolding profile of FGFR1. This rapid method requires low sample concentrations and could be used as a high-throughput screening technique for the characterisation of novel kinase inhibitors.

A subcellular map of the human kinome

The human kinome comprises 538 kinases playing essential functions by catalyzing protein phosphorylation. Annotation of subcellular distribution of the kinome greatly facilitates investigation of normal and disease mechanisms. Here, we present Kinome Atlas (KA), an image-based map of the kinome annotated to 10 cellular compartments. 456 epitope-tagged kinases, representing 85% of the human kinome, were expressed in HeLa cells and imaged by immunofluorescent microscopy under a similar condition. KA revealed kinase family-enriched subcellular localizations and discovered a collection of new kinase localizations at mitochondria, plasma membrane, extracellular space, and other structures. Furthermore, KA demonstrated the role of liquid-liquid phase separation in formation of kinase condensates. Identification of MOK as a mitochondrial kinase revealed its function in cristae dynamics, respiration, and oxidative stress response. Although limited by possible mislocalization due to overexpression or epitope tagging, this subcellular map of the kinome can be used to refine regulatory mechanisms involving protein phosphorylation.

Kinase Inhibitors as Underexplored Antiviral Agents

Viral infections are a major health problem; therefore, there is an urgent need for novel therapeutic strategies. Antivirals used to target proteins encoded by the viral genome usually enhance drug resistance generated by the virus. A potential solution may be drugs acting at host-based targets since viruses are dependent on numerous cellular proteins and phosphorylation events that are crucial during their life cycle. Repurposing existing kinase inhibitors as antiviral agents would help in the cost and effectiveness of the process, but this strategy usually does not provide much improvement, and specific medicinal chemistry programs are needed in the field. Anyway, extensive use of FDA-approved kinase inhibitors has been quite useful in deciphering the role of host kinases in viral infection. The present perspective aims to review the state of the art of kinase inhibitors that target viral infections in different development stages.

Rapid Identification of Inhibitors and Prediction of Ligand Selectivity for Multiple Proteins: Application to Protein Kinases

Rapid identification of inhibitors for a family of proteins and prediction of ligand specificity are highly desirable for structure-based drug design. However, sequentially docking ligands into each protein target with conventional single-target docking methods is too computationally expensive to achieve these two goals, especially when the number of the targets is large. In this work, we use an efficient ensemble docking algorithm for simultaneous docking of ligands against multiple protein targets. We use protein kinases, a family of proteins that are highly important for many cellular processes and for rational drug design, as an example to demonstrate the feasibility of investigating ligand selectivity with this algorithm. Specifically, 14 human protein kinases were selected. First, native docking calculations were performed to test the ability of our energy scoring function to reproduce the experimentally determined structures of the ligand-protein kinase complexes. Next, cross-docking calculations were conducted using our ensemble docking algorithm to study ligand selectivity, based on the assumption that the native target of an inhibitor should have a more negative (i.e., favorable) energy score than the non-native targets. Staurosporine and Gleevec were studied as examples of nonselective and selective binding, respectively. Virtual ligand screening was also performed against five protein kinases that have at least seven known inhibitors. Our quantitative analysis of the results showed that the ensemble algorithm can be effective on screening for inhibitors and investigating their selectivities for multiple target proteins.

Phosphoproteomics-Based Characterization of Prostaglandin E2 Signaling in T Cells

Prostaglandin E₂ (PGE₂) is a key lipid mediator in health and disease and serves as a crucial link between the immune response and cancer. With the advent of cancer therapies targeting PGE₂ signaling pathways at different levels, there has been increased interest in mapping and understanding the complex and interconnected signaling pathways arising from the four distinct PGE₂ receptors. Here, we review phosphoproteomics studies that have investigated different aspects of PGE₂ signaling in T cells. These studies have elucidated PGE₂'s regulatory effect on T cell receptor signaling and T cell function, the key role of protein kinase A in many PGE₂ signaling pathways, the temporal regulation of PGE₂ signaling, differences in PGE₂ signaling between different T cell subtypes, and finally, the crosstalk between PGE₂ signaling pathways elicited by the four distinct PGE2 receptors present in T cells. SIGNIFICANCE STATEMENT: Through the reviewed studies, we now have a much better understanding of PGE₂'s signaling mechanisms and functional roles in T cells, as well as a solid platform for targeted and functional studies of specific PGE₂-triggered pathways in T cells.

Beyond history and "on a roll": The list of the most well-studied human protein structures and overall trends in the protein data bank

Of the roughly 20,000 canonical human protein sequences, as of January 20, 2021, 7,077 proteins have had their full or partial, medium- to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the protein data bank (the PDB) and why? In this paper, we list the 273 top human protein structures based on the number of their PDB entries. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trends as well as current status for protein structural biology. We briefly discuss the relationship which some of the prominent protein structures have with protein research as a whole and mention their relevance to human diseases. The top-10 soluble and membrane proteins are all well-known (most of their first structures being deposited more than 30 years ago). Overall, there is no dramatic change in recent trends in the PDB. Remarkably, the number of structure depositions has grown nearly exponentially over the last 10 or more years (with a doubling time of 7 years for proteins, obtained from any organism). Growth in human protein structures is slightly faster (at 5.9 years). The information in this paper may be informative to senior scientists but also inspire researchers who are new to protein science, providing the year 2021 snap-shot for the state of protein structural biology.

Sequence and Structure-Based Analysis of Specificity Determinants in Eukaryotic Protein Kinases

Protein kinases lie at the heart of cell-signaling processes and are often mutated in disease. Kinase target recognition at the active site is in part determined by a few amino acids around the phosphoacceptor residue. However, relatively little is known about how most preferences are encoded in the kinase sequence or how these preferences evolved. Here, we used alignment-based approaches to predict 30 specificity-determining residues (SDRs) for 16 preferences. These were studied with structural models and were validated by activity assays of mutant kinases. Cancer mutation data revealed that kinase SDRs are mutated more frequently than catalytic residues. We have observed that, throughout evolution, kinase specificity has been strongly conserved across orthologs but can diverge after gene duplication, as illustrated by the G protein-coupled receptor kinase family. The identified SDRs can be used to predict kinase specificity from sequence and aid in the interpretation of evolutionary or disease-related genomic variants.

DYRK1A: a down syndrome-related dual protein kinase with a versatile role in tumorigenesis

Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a dual kinase that can phosphorylate its own activation loop on tyrosine residue and phosphorylate its substrates on threonine and serine residues. It is the most studied member of DYRK kinases, because its gene maps to human chromosome 21 within the Down syndrome critical region (DSCR). DYRK1A overexpression was found to be responsible for the phenotypic features observed in Down syndrome such as mental retardation, early onset neurodegenerative, and developmental heart defects. Besides its dual activity in phosphorylation, DYRK1A carries the characteristic of duality in tumorigenesis. Many studies indicate its possible role as a tumor suppressor gene; however, others prove its pro-oncogenic activity. In this review, we will focus on its multifaceted role in tumorigenesis by explaining its participation in some cancer hallmarks pathways such as proliferative signaling, transcription, stress, DNA damage repair, apoptosis, and angiogenesis, and finally, we will discuss targeting DYRK1A as a potential strategy for management of cancer and neurodegenerative disorders.

Nanomedicine of tyrosine kinase inhibitors

Recent progress in nanomedicine and targeted therapy brings new breeze into the field of therapeutic applications of tyrosine kinase inhibitors (TKIs). These drugs are known for many side effects due to non-targeted mechanism of action that negatively impact quality of patients' lives or that are responsible for failure of the drugs in clinical trials. Some nanocarrier properties provide improvement of drug efficacy, reduce the incidence of adverse events, enhance drug bioavailability, helps to overcome the blood-brain barrier, increase drug stability or allow for specific delivery of TKIs to the diseased cells. Moreover, nanotechnology can bring new perspectives into combination therapy, which can be highly efficient in connection with TKIs. Lastly, nanotechnology in combination with TKIs can be utilized in the field of theranostics, i.e. for simultaneous therapeutic and diagnostic purposes. The review provides a comprehensive overview of advantages and future prospects of conjunction of nanotransporters with TKIs as a highly promising approach to anticancer therapy.

Lowering Sample Requirements to Study Tyrosine Kinase Signaling Using Phosphoproteomics with the TMT Calibrator Approach

Analysis of tyrosine kinase signaling is critical for the development of targeted cancer therapy. Currently, immunoprecipitation of phosphotyrosine (pY) peptides prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) is used to profile tyrosine kinase substrates. A typical protocol requests 10 mg of total protein from ≈108 cells or 50-100 mg of tissue. Large sample requirements can be cost prohibitive or not feasible for certain experiments. Sample multiplexing using chemical labeling reduces the protein amount required for each sample, and newer approaches use a material-rich reference channel as a calibrator to trigger detection and quantification for smaller samples. Here, it is demonstrated that the tandem mass tag (TMT) calibrator approach reduces the sample input for pY profiling tenfold (to ≈1 mg total protein per sample from 107 cells grown in one plate), while maintaining the depth of pY proteome sampling and the biological content of the experiment. Data are available through PRIDE (PXD019764 for label-free and PXD018952 for TMT). This strategy opens more opportunities for pY profiling of large sample cohorts and samples with limited protein quantity such as immune cells, xenograft models, and human tumors.

Global and Site-Specific Effect of Phosphorylation on Protein Turnover

To date, the effects of specific modification types and sites on protein lifetime have not been systematically illustrated. Here, we describe a proteomic method, DeltaSILAC, to quantitatively assess the impact of site-specific phosphorylation on the turnover of thousands of proteins in live cells. Based on the accurate and reproducible mass spectrometry-based method, a pulse labeling approach using stable isotope-labeled amino acids in cells (pSILAC), phosphoproteomics, and a unique peptide-level matching strategy, our DeltaSILAC profiling revealed a global, unexpected delaying effect of many phosphosites on protein turnover. We further found that phosphorylated sites accelerating protein turnover are functionally selected for cell fitness, enriched in Cyclin-dependent kinase substrates, and evolutionarily conserved, whereas the glutamic acids surrounding phosphosites significantly delay protein turnover. Our method represents a generalizable approach and provides a rich resource for prioritizing the effects of phosphorylation sites on protein lifetime in the context of cell signaling and disease biology.

Compounds from Natural Sources as Protein Kinase Inhibitors

The advantage of natural compounds is their lower number of side-effects when compared to most synthetic substances. Therefore, over the past several decades, the interest in naturally occurring compounds is increasing in the search for new potent drugs. Natural compounds are playing an important role as a starting point when developing new selective compounds against different diseases. Protein kinases play a huge role in several diseases, like cancers, neurodegenerative diseases, microbial infections, or inflammations. In this review, we give a comprehensive view of natural compounds, which are/were the parent compounds in the development of more potent substances using computational analysis and SAR studies.

Phosphoproteomics Meets Chemical Genetics: Approaches for Global Mapping and Deciphering the Phosphoproteome

Protein kinases are important enzymes involved in the regulation of various cellular processes. To function properly, each protein kinase phosphorylates only a limited number of proteins among the thousands present in the cell. This provides a rapid and dynamic regulatory mechanism that controls biological functions of the proteins. Despite the importance of protein kinases, most of their substrates remain unknown. Recently, the advances in the fields of protein engineering, chemical genetics, and mass spectrometry have boosted studies on identification of bona fide substrates of protein kinases. Among the various methods in protein kinase specific substrate identification, genetically engineered protein kinases and quantitative phosphoproteomics have become promising tools. Herein, we review the current advances in the field of chemical genetics in analog-sensitive protein kinase mutants and highlight selected strategies for identifying protein kinase substrates and studying the dynamic nature of protein phosphorylation.

Conformational states dynamically populated by a kinase determine its function

Protein kinases intrinsically sample a number of conformational states with distinct catalytic and binding activities. We used nuclear magnetic resonance spectroscopy to describe in atomic-level detail how Abl kinase interconverts between an active and two discrete inactive structures. Extensive differences in key structural elements between the conformational states give rise to multiple intrinsic regulatory mechanisms. The findings explain how oncogenic mutants can counteract inhibitory mechanisms to constitutively activate the kinase. Energetic dissection revealed the contributions of the activation loop, the Asp-Phe-Gly (DFG) motif, the regulatory spine, and the gatekeeper residue to kinase regulation. Characterization of the transient conformation to which the drug imatinib binds enabled the elucidation of drug-resistance mechanisms. Structural insight into inactive states highlights how they can be leveraged for the design of selective inhibitors.

Revealing the Unbinding Kinetics and Mechanism of Type I and Type II Protein Kinase Inhibitors by Local-Scaled Molecular Dynamics Simulations

Protein kinase inhibitors disrupt phosphorylation of the target kinases, which are an important class of drug for treating cancer and other diseases. Conventional structure-based design methods (such as molecular docking) focus on the static binding mode of the kinase inhibitor with its target. However, dissociation kinetic properties of a drug molecule are found to correlate with its residence time in vivo and thus have drawn the attention of drug designers in recent years. In this study, we have applied the local-scaled molecular dynamics (MD) simulation enabled in GROMACS software to explore the unbinding mechanism of a total of 41 type I and type II kinase inhibitors. Our simulation considered multiple starting configurations as well as possible protonation states of kinase inhibitors. Based on our local-scaled MD results, we discovered that the integrals of the favorable binding energy during dissociation correlated well (R² = 0.64) with the experimental dissociation rate constants of those kinase inhibitors on the entire data set. Given its accuracy and technical advantage, this method may serve as a practical option for estimating this important property in reality. Our simulation also provided a reasonable explanation of the dynamic properties of kinase and its inhibitor as well as the role of relevant water molecules in dissociation.

Ultrasensitive Detection of Enzymatic Activity Using Single Molecule Arrays

Enzyme assays are important for many applications including clinical diagnostics, functional proteomics, and drug discovery. Current methods for enzymatic activity measurement often suffer from low analytical sensitivity. We developed an ultrasensitive method for the detection of enzymatic activity using Single Molecule Arrays (eSimoa). The eSimoa assay is accomplished by conjugating substrates to paramagnetic beads and measuring the conversion of substrates to products using single molecule analysis. We demonstrated the eSimoa method for the detection of protein kinases, telomerase, histone H3 methyltransferase SET7/9, and polypeptide N-acetylgalactosaminyltransferase with unprecedented sensitivity. In addition, we tested enzyme inhibition and performed theoretical calculations for the binding of inhibitor to its target enzyme and show the need for an ultrasensitive enzymatic assay to evaluate the potency of tight binding inhibitors. The eSimoa assay was successfully used to determine inhibition constants of both bosutinib and dasatinib. Due to the ultrasensitivity of this method, we also were able to measure the kinase activities at the single cell level. We show that the eSimoa assay is a simple, fast, and highly sensitive approach, which can be easily extended to detect a variety of other enzymes, providing a promising platform for enzyme-related fundamental research and inhibitor screening.

Role of tyrosine kinases in bladder cancer progression: an overview

Background

Bladder cancer (BCa) is a frequent urothelial malignancy with a high ratio of morbidity and mortality. Various genetic and environmental factors are involved in BCa progression. Since, majority of BCa cases are diagnosed after macroscopic clinical symptoms, it is required to find efficient markers for the early detection. Receptor tyrosine-kinases (RTKs) and non-receptor tyrosine-kinases (nRTKs) have pivotal roles in various cellular processes such as growth, migration, differentiation, and metabolism through different signaling pathways. Tyrosine-kinase deregulations are observed during tumor progressions via mutations, amplification, and chromosomal abnormalities which introduces these factors as important candidates of anti-cancer therapies.

Main body

For the first time in present review we have summarized all of the reported tyrosine-kinases which have been significantly associated with the clinicopathological features of BCa patients.

Conclusions

This review highlights the importance of tyrosine-kinases as critical markers in early detection and therapeutic purposes among BCa patients and clarifies the molecular biology of tyrosine-kinases during BCa progression and metastasis.

KSP: an integrated method for predicting catalyzing kinases of phosphorylation sites in proteins

BACKGROUND

Protein phosphorylation by kinases plays crucial roles in various biological processes including signal transduction and tumorigenesis, thus a better understanding of protein phosphorylation events in cells is fundamental for studying protein functions and designing drugs to treat diseases caused by the malfunction of phosphorylation. Although a large number of phosphorylation sites in proteins have been identified using high-throughput phosphoproteomic technologies, their specific catalyzing kinases remain largely unknown. Therefore, computational methods are urgently needed to predict the kinases that catalyze the phosphorylation of these sites.

RESULTS

We developed KSP, a new algorithm for predicting catalyzing kinases for experimentally identified phosphorylation sites in human proteins. KSP constructs a network based on known protein-protein interactions and kinase-substrate relationships. Based on the network, it computes an affinity score between a phosphorylation site and kinases, and returns the top-ranked kinases of the score as candidate catalyzing kinases. When tested on known kinase-substrate pairs, KSP outperforms existing methods including NetworKIN, iGPS, and PKIS.

CONCLUSIONS

We developed a novel accurate tool for predicting catalyzing kinases of known phosphorylation sites. It can work as a complementary network approach for sequence-based phosphorylation site predictors.

Kinase Interaction Network Expands Functional and Disease Roles of Human Kinases

Protein kinases are essential for signal transduction and control of most cellular processes, including metabolism, membrane transport, motility, and cell cycle. Despite the critical role of kinases in cells and their strong association with diseases, good coverage of their interactions is available for only a fraction of the 535 human kinases. Here, we present a comprehensive mass-spectrometry-based analysis of a human kinase interaction network covering more than 300 kinases. The interaction dataset is a high-quality resource with more than 5,000 previously unreported interactions. We extensively characterized the obtained network and were able to identify previously described, as well as predict new, kinase functional associations, including those of the less well-studied kinases PIM3 and protein O-mannose kinase (POMK). Importantly, the presented interaction map is a valuable resource for assisting biomedical studies. We uncover dozens of kinase-disease associations spanning from genetic disorders to complex diseases, including cancer.

KinCon: Cell-based recording of full-length kinase conformations

The spectrum of kinase alterations displays distinct functional characteristics and requires kinase mutation-oriented strategies for therapeutic interference. Besides phosphotransferase activity, protein abundance, and intermolecular interactions, particular patient-mutations promote pathological kinase conformations. Despite major advances in identifying lead molecules targeting clinically relevant oncokinase functions, still many kinases are neglected and not part of drug discovery efforts. One explanation is attributed to challenges in tracking kinase activities. Chemical probes are needed to functionally annotate kinase functions, whose activities may not always depend on catalyzing phospho-transfer. Such non-catalytic kinase functions are related to transitions of full-length kinase conformations. Recent findings underline that cell-based reporter systems can be adapted to record conformation changes of kinases. Here, we discuss the possible applications of an extendable kinase conformation (KinCon) reporter toolbox for live-cell recording of kinase states. KinCon is a genetically encoded bioluminescence-based biosensor platform, which can be subjected for measurements of conformation dynamics of mutated kinases upon small molecule inhibitor exposure. We hypothesize that such biosensors can be utilized to delineate the molecular modus operandi for kinase and pseudokinase regulation. This should pave the path for full-length kinase-targeted drug discovery efforts aiming to identify single and combinatory kinase inhibitor therapies with increased specificity and efficacy.

Modular bioengineered kinase sensors via scaffold protein-mediated split-luciferase complementation

Phosphorylation is a key regulation event in cellular signaling. To sense the underlying kinase activity, we engineered modular and easy adaptable serine kinase sensors for the exemplary kinases PKA, PKB and CHK1.

Phosphorylation is a key regulation event in cellular signaling. Sensing the underlying kinase activity is of crucial importance for its fundamental understanding and for drug development. For this, modular kinase activity sensing concepts are urgently needed. We engineered modular serine kinase sensors based on complementation of split NanoBiT luciferase on protein assembly platforms generated from the scaffold protein 14-3-3. The bioengineered platforms are modular and easy adaptable as exemplary shown using novel sensors for the kinases PKA, PKB, and CHK1. Two designs were conceptualized, both relying on binding of defined mono- or bivalent kinase recognition motifs to the 14-3-3 platform upon phosphorylation, resulting in reconstitution of active split-luciferase. Especially the design based on double phosphorylation and bivalent 14-3-3 binding exhibits high efficiency for signal amplification (>1000-fold) and sensitivity to specific kinases, including in cellular lysates.

Systematic response of staurosporine scaffold-based inhibitors to drug-resistant cancer kinase mutations

Human protein kinases have been established as promising druggable targets in cancer therapy. However, a large number of acquired drug-resistant kinase mutations are observed after first- and second-line kinase inhibitor treatments, largely limiting the application of small-molecule inhibitors in the targeted cancer therapy. Previously, the pan-kinase inhibitor staurosporine and its derivatives have been reported to selectively inhibit gatekeeper mutants over wild-type kinases, suggesting that the staurosporine scaffold is potentially helpful in developing wild-type-sparing inhibitors of drug-resistant kinase mutants. Here, a systematic response profile of 32 staurosporine scaffold-based inhibitors (SSBIs) for 61 ontology-enriched drug-resistant cancer kinase mutations is created using a combination of in silico analysis and in vitro assay, from which it is possible to identify those mutations that have the potential to cause resistance or confer sensitivity to SSBIs. The profile reveals that SSBIs exhibit distinct responses to kinase gatekeeper and nongatekeeper mutations, and SSBIs bearing p7 substituents can considerably influence their response to kinase gatekeeper mutations, particularly for the mutations of the Ile residue, which possesses a Cβ methyl group that tends to cause steric clash with bound SSBIs. Nongatekeeper mutations generally have a moderate and unfavorable effect on SSBI activity, as most of them are outside the kinase active site and do not directly contact inhibitor ligands. In addition, it is found that resistance is commonly caused by mutation-induced hindrance effects, whereas sensitivity is primarily conferred by mutation-established additional interactions.

The functional landscape of the human phosphoproteome

Protein phosphorylation is a key post-translational modification regulating protein function in almost all cellular processes. Although tens of thousands of phosphorylation sites have been identified in human cells, approaches to determine the functional importance of each phosphosite are lacking. Here, we manually curated 112 datasets of phospho-enriched proteins, generated from 104 different human cell types or tissues. We re-analyzed the 6,801 proteomics experiments that passed our quality control criteria, creating a reference phosphoproteome containing 119,809 human phosphosites. To prioritize functional sites, we used machine learning to identify 59 features indicative of proteomic, structural, regulatory or evolutionary relevance and integrate them into a single functional score. Our approach identifies regulatory phosphosites across different molecular mechanisms, processes and diseases, and reveals genetic susceptibilities at a genomic scale. Several regulatory phosphosites were experimentally validated, including identifying a role in neuronal differentiation for phosphosites in SMARCC2, a member of the SWI/SNF chromatin-remodeling complex.

Phosphoproteomic Analysis of Neonatal Regenerative Myocardium Revealed Important Roles of Checkpoint Kinase 1 via Activating Mammalian Target of Rapamycin C1/Ribosomal Protein S6 Kinase b-1 Pathway

BACKGROUND

In mammals, regenerative therapy after myocardial infarction is hampered by the limited regenerative capacity of adult heart, whereas a transient regenerative capacity is maintained in the neonatal heart. Systemic phosphorylation signaling analysis on ischemic neonatal myocardium might be helpful to identify key pathways involved in heart regeneration. Our aim was to define the kinase-substrate network in ischemic neonatal myocardium and to identify key pathways involved in heart regeneration after ischemic insult.

METHODS

Quantitative phosphoproteomics profiling was performed on infarct border zone of neonatal myocardium, and kinase-substrate network analysis revealed 11 kinases with enriched substrates and upregulated phosphorylation levels, including checkpoint kinase 1 (CHK1) kinase. The effect of CHK1 on cardiac regeneration was tested on Institute of Cancer Research CD1 neonatal and adult mice that underwent apical resection or myocardial infarction.

RESULTS

In vitro, CHK1 overexpression promoted whereas CHK1 knockdown blunted cardiomyocyte proliferation. In vivo, inhibition of CHK1 hindered myocardial regeneration on resection border zone in neonatal mice. In adult myocardial infarction mice, CHK1 overexpression on infarct border zone upregulated mammalian target of rapamycin C1/ribosomal protein S6 kinase b-1 pathway, promoted cardiomyocyte proliferation, and improved cardiac function. Inhibiting mammalian target of rapamycin activity by rapamycin blunted the neonatal cardiomyocyte proliferation induced by CHK1 overexpression in vitro.

CONCLUSIONS

Our study indicates that phosphoproteome of neonatal regenerative myocardium could help identify important signaling pathways involved in myocardial regeneration. CHK1 is found to be a key signaling responsible for neonatal regeneration. Myocardial overexpression of CHK1 could improve cardiac regeneration in adult hearts by activating the mammalian target of rapamycin C1/ribosomal protein S6 kinase b-1 pathway. Thus, CHK1 might serve as a potential novel target in myocardial repair after myocardial infarction.

An alternatively spliced, non-signaling insulin receptor modulates insulin sensitivity via insulin peptide sequestration in C. elegans

In the nematode C. elegans, insulin signaling regulates development and aging in response to the secretion of numerous insulin peptides. Here, we describe a novel, non-signaling isoform of the nematode insulin receptor (IR), DAF-2B, that modulates insulin signaling by sequestration of insulin peptides. DAF-2B arises via alternative splicing and retains the extracellular ligand binding domain but lacks the intracellular signaling domain. A daf-2b splicing reporter revealed active regulation of this transcript through development, particularly in the dauer larva, a diapause stage associated with longevity. CRISPR knock-in of mScarlet into the daf-2b genomic locus confirmed that DAF-2B is expressed in vivo and is likely secreted. Genetic studies indicate that DAF-2B influences dauer entry, dauer recovery and adult lifespan by altering insulin sensitivity according to the prevailing insulin milieu. Thus, in C. elegans alternative splicing at the daf-2 locus generates a truncated IR that fine-tunes insulin signaling in response to the environment.

The Encyclopedia of Proteome Dynamics: the KinoViewer

SUMMARY

The Encyclopedia of Proteome Dynamics (EPD) 'KinoViewer' is an interactive data visualization tool designed for analysis and exploration of both protein and transcript data, showing expression of kinase genes in either human or mouse cells and tissues. The KinoViewer provides a comprehensive, updated graphical display of all human/mouse kinases and an open access analysis tool for the community with a user-friendly graphical interface.

AVAILABILITY AND IMPLEMENTATION

The KinoViewer is based on a manually drawn SVG, which is utilized with D3.js to create a dynamic visualization. It can be accessed at: https://peptracker.com/epd/analytics/. The KinoViewer is currently only accessible through the EPD, it is open access and can be used either to view internal datasets, or used to upload and visualize external user datasets.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Advances in covalent kinase inhibitors

This comprehensive review details recent advances, challenges and innovations in covalent kinase inhibition within a 10 year period (2007–2018).

A Structurally-Validated Multiple Sequence Alignment of 497 Human Protein Kinase Domains

Studies on the structures and functions of individual kinases have been used to understand the biological properties of other kinases that do not yet have experimental structures. The key factor in accurate inference by homology is an accurate sequence alignment. We present a parsimonious, structure-based multiple sequence alignment (MSA) of 497 human protein kinase domains excluding atypical kinases. The alignment is arranged in 17 blocks of conserved regions and unaligned blocks in between that contain insertions of varying lengths present in only a subset of kinases. The aligned blocks contain well-conserved elements of secondary structure and well-known functional motifs, such as the DFG and HRD motifs. From pairwise, all-against-all alignment of 272 human kinase structures, we estimate the accuracy of our MSA to be 97%. The remaining inaccuracy comes from a few structures with shifted elements of secondary structure, and from the boundaries of aligned and unaligned regions, where compromises need to be made to encompass the majority of kinases. A new phylogeny of the protein kinase domains in the human genome based on our alignment indicates that ten kinases previously labeled as "OTHER" can be confidently placed into the CAMK group. These kinases comprise the Aurora kinases, Polo kinases, and calcium/calmodulin-dependent kinase kinases.

Target-Triggered Polymerization of Branched DNA Enables Enzyme-free and Fast Discrimination of Single-Base Changes

Single-base changes lead to important biological and biomedical implications; however, the discrimination of single-base changes from normal DNA always remains a grand challenge. Herein we developed a DNA recognition and amplification system based on artificial branched DNA, namely, target-triggered polymerization (TTP), to realize enzyme-free and fast discrimination of single-base changes. Branched DNA as monomers rapidly polymerized into DNA nanospheres only with the trigger of specific DNA. Our TTP system worked reliably over a wide range of conditions. Remarkably, our TTP system was capable of discriminating base-changing DNA from normal DNA, including distinguishing 1-4 nucleotide changes and positions of single base, which was attributed to the significant amplification of small differences in hybridization thermodynamics and kinetics. We further proposed a theoretical method for calculating the hybridization probability of nucleic acids, which performed highly consistent with experimental results.