Classifying protein kinase conformations with machine learning.

Protein kinases are key actors of signaling networks and important drug targets. They cycle between active and inactive conformations, distinguished by a few elements within the catalytic domain. One is the activation loop, whose conserved DFG motif can occupy DFG-in, DFG-out, and some rarer conformations. Annotation and classification of the structural kinome are important, as different conformations can be targeted by different inhibitors and activators. Valuable resources exist; however, large-scale applications will benefit from increased automation and interpretability of structural annotation. Interpretable machine learning models are described for this purpose, based on ensembles of decision trees. To train them, a set of catalytic domain sequences and structures was collected, somewhat larger and more diverse than existing resources. The structures were clustered based on the DFG conformation and manually annotated. They were then used as training input. Two main models were constructed, which distinguished active/inactive and in/out/other DFG conformations. They considered initially 1692 structural variables, spanning the whole catalytic domain, then identified ("learned") a small subset that sufficed for accurate classification. The first model correctly labeled all but 3 of 3289 structures as active or inactive, while the second assigned the correct DFG label to all but 17 of 8826 structures. The most potent classifying variables were all related to well-known structural elements in or near the activation loop and their ranking gives insights into the conformational preferences. The models were used to automatically annotate 3850 kinase structures predicted recently with the Alphafold2 tool, showing that Alphafold2 reproduced the active/inactive but not the DFG-in proportions seen in the Protein Data Bank. We expect the models will be useful for understanding and engineering kinases.

DeepKa Web Server: High-Throughput Protein pKa Prediction.

DeepKa is a deep-learning-based protein pKa predictor proposed in our previous work. In this study, a web server was developed that enables online protein pKa prediction driven by DeepKa. The web server provides a user-friendly interface where a single step of entering a valid PDB code or uploading a PDB format file is required to submit a job. Two case studies have been attached in order to explain how pKa's calculated by the web server could be utilized by users. Finally, combining the web server with post processing as described in case studies, this work suggests a quick workflow of investigating the relationship between protein structure and function that are pH dependent. The web server of DeepKa is freely available at http://www.computbiophys.com/DeepKa/main.

Nanointegrative Glycoengineering-Activated Necroptosis of Triple Negative Breast Cancer Stem Cells Enables Self-Amplifiable Immunotherapy for Systemic Tumor Rejection.

Triple-negative breast cancer stem cells (TCSCs) are considered as the origin of recurrence and relapse. It is difficult to kill not only for its resistance, but also the lacking of targetable molecules on membrane. Here, it is confirmed that ST6 ß-galactoside alpha-2,6-sialyltransferase 1 (ST6Gal-1) is highly expressed in TCSCs that may be the key enzyme involved in glycoengineering via sialic acid (SA) metabolism. SA co-localizes with a microdomain on cell membrane termed as lipid rafts that enrich CSCs marker and necroptosis proteins mixed lineage kinase domain-like protein (MLKL), suggesting that TCSCs may be sensitive to necroptosis. Thus, the triacetylated N-azidoacetyl-d-mannosamine (Ac3ManNAz) is synthesized as the glycoengineering substrate and applied to introduce artificial azido receptors, dibenzocyclooctyne (DBCO)-modified liposome is used to deliver Compound 6i (C6), a receptor-interacting serine/threonine protein kinase 1(RIPL1)-RIP3K-mixed lineage kinase domain-like protein(MLKL) activator, to induce necroptosis. The pro-necroptosis effect is aggravated by nitric oxide (NO), which is released from NO-depot of cholesterol-NO integrated in DBCO-PEG-liposome@NO/C6 (DLip@NO/C6). Together with the immunogenicity of necroptosis that releases high mobility group box 1(HMGB1) of damage-associated molecular patterns, TCSCs are significantly killed in vitro and in vivo. The results suggest a promising strategy to improve the therapeutic effect on the non-targetable TCSCs with high expression of ST6Gal-1 via combination of glycoengineering and necroptosis induction.

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.

Kinase-catalyzed Biotinylation with Inactivated Lysates for Discovery of Substrates (K-BILDS).

Protein phosphorylation is catalyzed by kinases to regulate a large variety of cellular activities, including growth and signal transduction. Methods to identify kinase substrates are crucial to fully understand phosphorylation-mediated cellular events and disease states. Here, we report a set of protocols to identify substrates of a target kinase using Kinase-catalyzed Biotinylation with Inactivated Lysates for Discovery of Substrates (K-BILDS). As described in these protocols, K-BILDS involves inactivation of endogenous kinases in lysates, followed by addition of an active exogenous kinase and the γ-phosphate-modified ATP analog ATP-biotin for kinase-catalyzed biotinylation of cellular substrates. Avidin enrichment isolates biotinylated substrates of the active kinase, which can be monitored by western blot. Substrates of the target kinase can also be discovered using mass spectrometry analysis. Key advantages of K-BILDS include compatibility with any lysate, tissue homogenate, or complex mixture of biological relevance and any active kinase of interest. K-BILDS is a versatile method for studying or discovering substrates of a kinase of interest to characterize biological pathways thoroughly. © 2023 Wiley Periodicals LLC. Basic Protocol 1: FSBA treatment of lysates to inactivate kinases Basic Protocol 2: Kinase-catalyzed Biotinylation with Inactivated Lysates for Discovery of Substrates (K-BILDS).

Molecular Simulations of Conformational Transitions within the Insulin Receptor Kinase Reveal Consensus Features in a Multistep Activation Pathway.

Modulating the transitions between active and inactive conformations of protein kinases is the primary means of regulating their catalytic activity, achieved by phosphorylation of the activation loop (A-loop). To elucidate the mechanism of this conformational activation, we applied the string method to determine the conformational transition path of insulin receptor kinase between the active and inactive conformations and the corresponding free-energy profiles with and without A-loop phosphorylation. The conformational change was found to proceed in three sequential steps: first, the flipping of the DFG motif of the active site; second, rotation of the A-loop; finally, the inward movement of the αC helix. The main energetic bottleneck corresponds to the conformational change in the A-loop, while changes in the DFG motif and αC helix occur before and after A-loop conformational change, respectively. In accordance with this, two intermediate states are identified, the first state just after the DFG flipping and the second state after the A-loop rotation. These intermediates exhibit structural features characteristic of the corresponding inactive and active conformations of other protein kinases. To understand the impact of A-loop phosphorylation on kinase conformation, the free energies of A-loop phosphorylation were determined at several states along the conformational transition path using the free-energy perturbation simulations. The calculated free energies reveal that while the unphosphorylated kinase interconverts between the inactive and active conformations, A-loop phosphorylation restricts access to the inactive conformation, thereby increasing the active conformation population. Overall, this study suggests a consensus mechanism of conformational activation between different protein kinases.

GPS 6.0: an updated server for prediction of kinase-specific phosphorylation sites in proteins.

Protein phosphorylation, catalyzed by protein kinases (PKs), is one of the most important post-translational modifications (PTMs), and involved in regulating almost all of biological processes. Here, we report an updated server, Group-based Prediction System (GPS) 6.0, for prediction of PK-specific phosphorylation sites (p-sites) in eukaryotes. First, we pre-trained a general model using penalized logistic regression (PLR), deep neural network (DNN), and Light Gradient Boosting Machine (LightGMB) on 490 762 non-redundant p-sites in 71 407 proteins. Then, transfer learning was conducted to obtain 577 PK-specific predictors at the group, family and single PK levels, using a well-curated data set of 30 043 known site-specific kinase-substrate relations in 7041 proteins. Together with the evolutionary information, GPS 6.0 could hierarchically predict PK-specific p-sites for 44046 PKs in 185 species. Besides the basic statistics, we also offered the knowledge from 22 public resources to annotate the prediction results, including the experimental evidence, physical interactions, sequence logos, and p-sites in sequences and 3D structures. The GPS 6.0 server is freely available at https://gps.biocuckoo.cn. We believe that GPS 6.0 could be a highly useful service for further analysis of phosphorylation.

Single-Molecule Monitoring of Membrane Association of the Necroptosis Executioner MLKL with Discernible Anchoring and Insertion Dynamics.

The dynamics of membrane proteins that are well-folded in water and become functional after self-insertion into cell membranes is not well understood. Herein we report on single-molecule monitoring of membrane association dynamics of the necroptosis executioner MLKL. We observed that, upon landing, the N-terminal region (NTR) of MLKL anchors onto the surface with an oblique angle and then is immersed in the membrane. The anchoring end does not insert into the membrane, but the opposite end does. The protein is not static, switching slowly between water-exposed and membrane-embedded conformations. The results suggest a mechanism for the activation and function of MLKL in which exposure of H4 is critical for MLKL to adsorb on the membrane, and the brace helix H6 regulates MLKL rather than inhibits it. Our findings provide deeper insights into membrane association and function regulation of MLKL and would have impacts on biotechnological applications.

The stem cell-supporting small molecule UM171 triggers Cul3-KBTBD4-mediated degradation of ELM2 domain-harboring proteins.

To chemically modulate the ubiquitin-proteasome system for the degradation of specific target proteins is currently emerging as an alternative therapeutic modality. Earlier, we discovered such properties of the stem cell-supporting small molecule UM171 and identified that members of the CoREST complex (RCOR1 and LSD1) are targeted for degradation. UM171 supports the in vitro propagation of hematopoietic stem cells by transiently perturbing the differentiation-promoting effects of CoREST. Here, we employed global proteomics to map the UM171-targeted proteome and identified the additional target proteins, namely RCOR3, RREB1, ZNF217, and MIER2. Further, we discovered that critical elements recognized by Cul3KBTBD4 ligase in the presence of UM171 are located within the EGL-27 and MTA1 homology 2 (ELM2) domain of the substrate proteins. Subsequent experiments identified conserved amino acid sites in the N-terminus of the ELM2 domain that are essential for UM171-mediated degradation. Overall, our findings provide a detailed account on the ELM2 degrome targeted by UM171 and identify critical sites required for UM171-mediated degradation of specific substrates. Given the target profile, our results are highly relevant in a clinical context and point towards new therapeutic applications for UM171.

Norovirus MLKL-like protein initiates cell death to induce viral egress.

Non-enveloped viruses require cell lysis to release new virions from infected cells, suggesting that these viruses require mechanisms to induce cell death. Noroviruses are one such group of viruses, but there is no known mechanism that causes norovirus infection-triggered cell death and lysis1-3. Here we identify a molecular mechanism of norovirus-induced cell death. We found that the norovirus-encoded NTPase NS3 contains an N-terminal four-helix bundle domain homologous to the membrane-disruption domain of the pseudokinase mixed lineage kinase domain-like (MLKL). NS3 has a mitochondrial localization signal and thus induces cell death by targeting mitochondria. Full-length NS3 and an N-terminal fragment of the protein bound the mitochondrial membrane lipid cardiolipin, permeabilized the mitochondrial membrane and induced mitochondrial dysfunction. Both the N-terminal region and the mitochondrial localization motif of NS3 were essential for cell death, viral egress from cells and viral replication in mice. These findings suggest that noroviruses have acquired a host MLKL-like pore-forming domain to facilitate viral egress by inducing mitochondrial dysfunction.

Natural Metabolite Ursolic Acid as an Inhibitor of Dormancy Regulator DosR of Mycobacterium tuberculosis: Evidence from Molecular Docking, Molecular Dynamics Simulation and Free Energy Analysis.

BACKGROUND: DosR is a transcriptional regulator of Mycobacterium tuberculosis (MTB), governing the expression of a set of nearly 50 genes that is often referred to as 'dormancy regulon'. The inhibition of DosR expression by an appropriate inhibitor may be a crucial step against MTB. OBJECTIVE: We targeted the DosR with natural metabolites, ursolic acid (UA) and carvacrol (CV), using in silico approaches. METHODS: The molecular docking, molecular dynamics (MD) simulation for 200 ns, calculation of binding energies by MM-GBSA method, and ADMET calculation were performed to evaluate the inhibitory potential of natural metabolites ursolic acid (UA) and carvacrol (CV) against DosR of MTB. RESULTS: Our study demonstrated that UA displayed significant compatibility with DosR during the 200 ns timeframe of MD simulation. The thermodynamic binding energies by MM-GBSA also suggested UA conformational stability within the binding pocket. The SwissADME, pkCSM, and OSIRIS DataWarrior showed a drug-likeness profile of UA, where Lipinski profile was satisfied with one violation (MogP > 4.15) with no toxicities, no mutagenicity, no reproductive effect, and no irritant nature. CONCLUSION: The present study suggests that UA has the potency to inhibit the DosR expression and warrants further investigation on harnessing its clinical potential.

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

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

Construction of a phos-tag-directed self-assembled fluorescent magnetobiosensor for the simultaneous detection of multiple protein kinases.

Protein kinases play important roles in regulating various cellular processes and may function as potential diagnostic and therapeutic targets for various diseases including cancers. Herein, we construct a phos-tag-directed self-assembled fluorescent magnetobiosensor to simultaneously detect multiple protein kinases with good selectivity and high sensitivity. In the presence of protein kinases (i.e., PKA and Akt1), their substrate peptides (i.e., a FITC-labeled substrate peptide and a Cy5-labeled substrate peptide) are phosphorylated, and are then specifically recognized and captured by a biotinylated phos-tag to generate biotinylated substrate peptides for the assembly of magnetic bead (MB)-peptides-FITC/Cy5 nanostructures. After magnetic separation, the phosphorylated substrate peptides are disassembled from the MB-peptides-FITC/Cy5 nanostructures using deionized water at 80 °C, releasing FITC and Cy5 molecules. The released FITC and Cy5 molecules are detected by steady-state fluorescence measurements, with FITC indicating PKA and Cy5 indicating Akt1. This magnetobiosensor only involves one phos-tag without the requirement of radiolabeling, antibody screening, carboxypeptidase Y (CPY) cleavage, and cumbersome chemical/enzyme reactions. The introduction of magnetic separation can effectively eliminate the interference from complex real samples, generating an extremely low background signal. Moreover, this magnetobiosensor can accurately measure cellular protein kinase activities and screen inhibitors, with great potential for kinase-related biomedical research and therapeutic applications.

KID: A Kinase-Focused Interaction Database and Its Application in the Construction of Kinase-Focused Molecule Databases.

Protein kinases are important drug targets for the treatment of several diseases. The interaction between kinases and ligands is vital in the process of small-molecule kinase inhibitor (SMKI) design. In this study, we propose a method to extract fragments and amino acid residues from crystal structures for kinase-ligand interactions. In addition, core fragments that interact with the important hinge region of kinases were extracted along with their decorations. Based on the superimposed structural data of kinases from the kinase-ligand interaction fingerprint and structure database, we obtained two libraries, namely, a hinge-unfocused fragment-amino acid pair library (FAP Lib) that contains 6672 pairs of fragments and corresponding amino-acids, and a hinge-focused hinge binder library (HB Lib) of 3560 pairs of hinge-binding scaffolds with their corresponding decorations. These two libraries constitute a kinase-focused interaction database (KID). In depth analysis was conducted on KID to explore important characteristics of fragments in the design of SMKIs. With KID, we built two kinase-focused molecule databases, one called Recomb_DB, which contains 1,72,346 molecules generated through fragment recombination based on the FAP Lib, and another called RsdHB_DB, which contains 93,030 molecules generated based on our HB Lib using molecular generation methods. Compared with five databases both commercial and non-commercial, these two databases both ranked top 3 in scaffold diversity, top 4 in molecule fingerprint diversity, and are more focused on the chemical space of kinase inhibitors. Hence, KID presents a useful addition to existing databases for the exploration of novel SMKIs.

Structural features of the protein kinase domain and targeted binding by small-molecule inhibitors.

Protein kinases are key components in cellular signaling pathways as they carry out the phosphorylation of proteins, primarily on Ser, Thr, and Tyr residues. The catalytic activity of protein kinases is regulated, and they can be thought of as molecular switches that are controlled through protein-protein interactions and post-translational modifications. Protein kinases exhibit diverse structural mechanisms of regulation and have been fascinating subjects for structural biologists from the first crystal structure of a protein kinase over 30 years ago, to recent insights into kinase assemblies enabled by the breakthroughs in cryo-EM. Protein kinases are high-priority targets for drug discovery in oncology and other disease settings, and kinase inhibitors have transformed the outcomes of specific groups of patients. Most kinase inhibitors are ATP competitive, deriving potency by occupying the deep hydrophobic pocket at the heart of the kinase domain. Selectivity of inhibitors depends on exploiting differences between the amino acids that line the ATP site and exploring the surrounding pockets that are present in inactive states of the kinase. More recently, allosteric pockets outside the ATP site are being targeted to achieve high selectivity and to overcome resistance to current therapeutics. Here, we review the key regulatory features of the protein kinase family, describe the different types of kinase inhibitors, and highlight examples where the understanding of kinase regulatory mechanisms has gone hand in hand with the development of inhibitors.

Co-expression of recombinant RIPK3:MLKL complexes using the baculovirus-insect cell system.

Pseudokinase domains are found throughout the kingdoms of life and serve myriad roles in cell signaling. These domains, which resemble protein kinases but are catalytically-deficient, have been described principally as protein interaction domains. Broadly, pseudokinases have been reported to function as: allosteric regulators of conventional enzymes; scaffolds to nucleate assembly and/or localization of signaling complexes; molecular switches; or competitors of signaling complex assembly. From detailed structural and biochemical studies of individual pseudokinases, a picture of how they mediate protein interactions is beginning to emerge. Many such studies have relied on recombinant protein production in insect cells, where endogenous chaperones and modifying enzymes favor bona fide folding of pseudokinases. Here, we describe methods for co-expression of pseudokinases and their interactors in insect cells, as exemplified by the MLKL pseudokinase, which is the terminal effector in the necroptosis cell death pathway, and its upstream regulator kinase RIPK3. These methods are broadly applicable to co-expression of other pseudokinases with their interaction partners from bacmids using the baculovirus-insect cell expression system.

Conformational control and regulation of the pseudokinase KSR via small molecule binding interactions.

Pseudokinases often operate through functionally related enzymes and receptors. A prime example is the pseudokinase KSR (Kinase Suppressor of RAS), which can act as both an amplifier and inhibitor of members in the RAS-MAPK (Mitogen Activated Protein Kinase) signaling pathway. KSR is structurally related to the active RAF kinases over multiple domains; moreover, the pseudokinase domain of KSR forms physical and regulatory complexes with both RAF and MEK through distinct interfaces. Characterization of small molecule interactions on KSR has been used to uncover novel chemical tools and understand the mechanism of action of clinical drugs. Here, we elaborate on assays and structural methods for measuring binding at orthosteric and interfacial binding sites on KSR. These distinct small molecule pockets provide therapeutic paths for targeting KSR1 and KSR2 pseudokinases in disease, including in RAS and RAF mutant cancers.

Computational tools and resources for pseudokinase research.

Pseudokinases regulate diverse cellular processes associated with normal cellular functions and disease. They are defined bioinformatically based on the absence of one or more catalytic residues that are required for canonical protein kinase functions. The ability to define pseudokinases based on primary sequence comparison has enabled the systematic mapping and cataloging of pseudokinase orthologs across the tree of life. While these sequences contain critical information regarding pseudokinase evolution and functional specialization, extracting this information and generating testable hypotheses based on integrative mining of sequence and structural data requires specialized computational tools and resources. In this chapter, we review recent advances in the development and application of open-source tools and resources for pseudokinase research. Specifically, we describe the application of an interactive data analytics framework, KinView, for visualizing the patterns of conservation and variation in the catalytic domain motifs of pseudokinases and evolutionarily related canonical kinases using a consistent set of curated alignments organized based on the widely used kinome evolutionary hierarchy. We also demonstrate the application of an integrated Protein Kinase Ontology (ProKinO) and an interactive viewer, ProtVista, for mapping and analyzing primary sequence motifs and annotations in the context of 3D structures and AlphaFold2 models. We provide examples and protocols for generating testable hypotheses on pseudokinase functions both for bench biologists and advanced users.

Methods for discovering catalytic activities for pseudokinases.

Pseudoenzymes resemble active enzymes, but lack key catalytic residues believed to be required for activity. Many pseudoenzymes appear to be inactive in conventional enzyme assays. However, an alternative explanation for their apparent lack of activity is that pseudoenzymes are being assayed for the wrong reaction. We have discovered several new protein kinase-like families which have revealed how different binding orientations of adenosine triphosphate (ATP) and active site residue migration can generate a novel reaction from a common kinase scaffold. These results have exposed the catalytic versatility of the protein kinase fold and suggest that atypical kinases and pseudokinases should be analyzed for alternative transferase activities. In this chapter, we discuss a general approach for bioinformatically identifying divergent or atypical members of an enzyme superfamily, then present an experimental approach to characterize their catalytic activity.

Therapeutic Targeting the Allosteric Cysteinome of RAS and Kinase Families.

Allosteric mechanisms are pervasive in nature, but human-designed allosteric perturbagens are rare. The history of KRASG12C inhibitor development suggests that covalent chemistry may be a key to expanding the armamentarium of allosteric inhibitors. In that effort, irreversible targeting of a cysteine converted a non-deal allosteric binding pocket and low affinity ligands into a tractable drugging strategy. Here we examine the feasibility of expanding this approach to other allosteric pockets of RAS and kinase family members, given that both protein families are regulators of vital cellular processes that are often dysregulated in cancer and other human diseases. Moreover, these heavily studied families are the subject of numerous drug development campaigns that have resulted, sometimes serendipitously, in the discovery of allosteric inhibitors. We consequently conducted a comprehensive search for cysteines, a commonly targeted amino acid for covalent drugs, using AlphaFold-generated structures of those families. This new analysis presents potential opportunities for allosteric targeting of validated and understudied drug targets, with an emphasis on cancer therapy.