RESUMEN
Protein language modeling is a fast-emerging deep learning method in bioinformatics with diverse applications such as structure prediction and protein design. However, application toward estimating sequence conservation for functional site prediction has not been systematically explored. Here, we present a method for the alignment-free estimation of sequence conservation using sequence embeddings generated from protein language models. Comprehensive benchmarks across publicly available protein language models reveal that ESM2 models provide the best performance to computational cost ratio for conservation estimation. Applying our method to full-length protein sequences, we demonstrate that embedding-based methods are not sensitive to the order of conserved elements-conservation scores can be calculated for multidomain proteins in a single run, without the need to separate individual domains. Our method can also identify conserved functional sites within fast-evolving sequence regions (such as domain inserts), which we demonstrate through the identification of conserved phosphorylation motifs in variable insert segments in protein kinases. Overall, embedding-based conservation analysis is a broadly applicable method for identifying potential functional sites in any full-length protein sequence and estimating conservation in an alignment-free manner. To run this on your protein sequence of interest, try our scripts at https://github.com/esbgkannan/kibby.
Asunto(s)
Biología Computacional , Proteínas , Secuencia de Aminoácidos , Proteínas/genética , Proteínas/química , Biología Computacional/métodos , Secuencia ConservadaRESUMEN
Protein language models, trained on millions of biologically observed sequences, generate feature-rich numerical representations of protein sequences. These representations, called sequence embeddings, can infer structure-functional properties, despite protein language models being trained on primary sequence alone. While sequence embeddings have been applied toward tasks such as structure and function prediction, applications toward alignment-free sequence classification have been hindered by the lack of studies to derive, quantify and evaluate relationships between protein sequence embeddings. Here, we develop workflows and visualization methods for the classification of protein families using sequence embedding derived from protein language models. A benchmark of manifold visualization methods reveals that Neighbor Joining (NJ) embedding trees are highly effective in capturing global structure while achieving similar performance in capturing local structure compared with popular dimensionality reduction techniques such as t-SNE and UMAP. The statistical significance of hierarchical clusters on a tree is evaluated by resampling embeddings using a variational autoencoder (VAE). We demonstrate the application of our methods in the classification of two well-studied enzyme superfamilies, phosphatases and protein kinases. Our embedding-based classifications remain consistent with and extend upon previously published sequence alignment-based classifications. We also propose a new hierarchical classification for the S-Adenosyl-L-Methionine (SAM) enzyme superfamily which has been difficult to classify using traditional alignment-based approaches. Beyond applications in sequence classification, our results further suggest NJ trees are a promising general method for visualizing high-dimensional data sets.
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Secuencia de Aminoácidos , Proteínas , Análisis por Conglomerados , Proteínas/química , Alineación de SecuenciaRESUMEN
MOTIVATION: Phosphorylation, a post-translational modification regulated by protein kinase enzymes, plays an essential role in almost all cellular processes. Understanding how each of the nearly 500 human protein kinases selectively phosphorylates their substrates is a foundational challenge in bioinformatics and cell signaling. Although deep learning models have been a popular means to predict kinase-substrate relationships, existing models often lack interpretability and are trained on datasets skewed toward a subset of well-studied kinases. RESULTS: Here we leverage recent peptide library datasets generated to determine substrate specificity profiles of 300 serine/threonine kinases to develop an explainable Transformer model for kinase-peptide interaction prediction. The model, trained solely on primary sequences, achieved state-of-the-art performance. Its unique multitask learning paradigm built within the model enables predictions on virtually any kinase-peptide pair, including predictions on 139 kinases not used in peptide library screens. Furthermore, we employed explainable machine learning methods to elucidate the model's inner workings. Through analysis of learned embeddings at different training stages, we demonstrate that the model employs a unique strategy of substrate prediction considering both substrate motif patterns and kinase evolutionary features. SHapley Additive exPlanation (SHAP) analysis reveals key specificity determining residues in the peptide sequence. Finally, we provide a web interface for predicting kinase-substrate associations for user-defined sequences and a resource for visualizing the learned kinase-substrate associations. AVAILABILITY AND IMPLEMENTATION: All code and data are available at https://github.com/esbgkannan/Phosformer-ST. Web server is available at https://phosformer.netlify.app.
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Biblioteca de Péptidos , Proteínas Quinasas , Humanos , Proteínas Quinasas/metabolismo , Fosforilación , Péptidos/química , Aprendizaje AutomáticoRESUMEN
MOTIVATION: The human genome encodes over 500 distinct protein kinases which regulate nearly all cellular processes by the specific phosphorylation of protein substrates. While advances in mass spectrometry and proteomics studies have identified thousands of phosphorylation sites across species, information on the specific kinases that phosphorylate these sites is currently lacking for the vast majority of phosphosites. Recently, there has been a major focus on the development of computational models for predicting kinase-substrate associations. However, most current models only allow predictions on a subset of well-studied kinases. Furthermore, the utilization of hand-curated features and imbalances in training and testing datasets pose unique challenges in the development of accurate predictive models for kinase-specific phosphorylation prediction. Motivated by the recent development of universal protein language models which automatically generate context-aware features from primary sequence information, we sought to develop a unified framework for kinase-specific phosphosite prediction, allowing for greater investigative utility and enabling substrate predictions at the whole kinome level. RESULTS: We present a deep learning model for kinase-specific phosphosite prediction, termed Phosformer, which predicts the probability of phosphorylation given an arbitrary pair of unaligned kinase and substrate peptide sequences. We demonstrate that Phosformer implicitly learns evolutionary and functional features during training, removing the need for feature curation and engineering. Further analyses reveal that Phosformer also learns substrate specificity motifs and is able to distinguish between functionally distinct kinase families. Benchmarks indicate that Phosformer exhibits significant improvements compared to the state-of-the-art models, while also presenting a more generalized, unified, and interpretable predictive framework. AVAILABILITY AND IMPLEMENTATION: Code and data are available at https://github.com/esbgkannan/phosformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Proteínas Quinasas , Procesamiento Proteico-Postraduccional , Humanos , Fosforilación , Proteínas Quinasas/metabolismo , Proteínas/metabolismoRESUMEN
Hydrophobic cores are fundamental structural properties of proteins typically associated with protein folding and stability; however, how the hydrophobic core shapes protein evolution and function is poorly understood. Here, we investigated the role of conserved hydrophobic cores in fold-A glycosyltransferases (GT-As), a large superfamily of enzymes that catalyze formation of glycosidic linkages between diverse donor and acceptor substrates through distinct catalytic mechanisms (inverting versus retaining). Using hidden Markov models and protein structural alignments, we identify similarities in the phosphate-binding cassette (PBC) of GT-As and unrelated nucleotide-binding proteins, such as UDP-sugar pyrophosphorylases. We demonstrate that GT-As have diverged from other nucleotide-binding proteins through structural elaboration of the PBC and its unique hydrophobic tethering to the F-helix, which harbors the catalytic base (xED-Asp). While the hydrophobic tethering is conserved across diverse GT-A fold enzymes, some families, such as B3GNT2, display variations in tethering interactions and core packing. We evaluated the structural and functional impact of these core variations through experimental mutational analysis and molecular dynamics simulations and find that some of the core mutations (T336I in B3GNT2) increase catalytic efficiency by modulating the conformational occupancy of the catalytic base between "D-in" and acceptor-accessible "D-out" conformation. Taken together, our studies support a model of evolution in which the GT-A core evolved progressively through elaboration upon an ancient PBC found in diverse nucleotide-binding proteins, and malleability of this core provided the structural framework for evolving new catalytic and substrate-binding functions in extant GT-A fold enzymes.
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Glicosiltransferasas , Pliegue de Proteína , Glicosiltransferasas/metabolismo , Humanos , Conformación Molecular , Simulación de Dinámica Molecular , NucleótidosRESUMEN
The emergence of multicellularity is strongly correlated with the expansion of tyrosine kinases, a conserved family of signaling enzymes that regulates pathways essential for cell-to-cell communication. Although tyrosine kinases have been classified from several model organisms, a molecular-level understanding of tyrosine kinase evolution across all holozoans is currently lacking. Using a hierarchical sequence constraint-based classification of diverse holozoan tyrosine kinases, we construct a new phylogenetic tree that identifies two ancient clades of cytoplasmic and receptor tyrosine kinases separated by the presence of an extended insert segment in the kinase domain connecting the D and E-helices. Present in nearly all receptor tyrosine kinases, this fast-evolving insertion imparts diverse functionalities, such as post-translational modification sites and regulatory interactions. Eph and EGFR receptor tyrosine kinases are two exceptions which lack this insert, each forming an independent lineage characterized by unique functional features. We also identify common constraints shared across multiple tyrosine kinase families which warrant the designation of three new subgroups: Src module (SrcM), insulin receptor kinase-like (IRKL), and fibroblast, platelet-derived, vascular, and growth factor receptors (FPVR). Subgroup-specific constraints reflect shared autoinhibitory interactions involved in kinase conformational regulation. Conservation analyses describe how diverse tyrosine kinase signaling functions arose through the addition of family-specific motifs upon subgroup-specific features and coevolving protein domains. We propose the oldest tyrosine kinases, IRKL, SrcM, and Csk, originated from unicellular premetazoans and were coopted for complex multicellular functions. The increased frequency of oncogenic variants in more recent tyrosine kinases suggests that lineage-specific functionalities are selectively altered in human cancers.
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Evolución Molecular , Proteínas Tirosina Quinasas , Tirosina , Fosforilación , Filogenia , Proteínas Tirosina Quinasas/genética , Proteínas Tirosina Quinasas/metabolismo , Proteínas Tirosina Quinasas Receptoras/genética , Proteínas Tirosina Quinasas Receptoras/metabolismo , Transducción de Señal , Tirosina/metabolismoRESUMEN
The pleckstrin homology (PH) domain is well known for its phospholipid targeting function. The PH-TEC homology (PHTH) domain within the TEC family of tyrosine kinases is also a crucial component of the autoinhibitory apparatus. The autoinhibitory surface on the PHTH domain has been previously defined, and biochemical investigations have shown that PHTH-mediated inhibition is mutually exclusive with phosphatidylinositol binding. Here we use hydrogen/deuterium exchange mass spectrometry, nuclear magnetic resonance (NMR), and evolutionary sequence comparisons to map where and how the PHTH domain affects the Bruton's tyrosine kinase (BTK) domain. The data map a PHTH-binding site on the activation loop face of the kinase C lobe, suggesting that the PHTH domain masks the activation loop and the substrate-docking site. Moreover, localized NMR spectral changes are observed for non-surface-exposed residues in the active site and on the distal side of the kinase domain. These data suggest that the association of PHTH induces allosteric conformational shifts in regions of the kinase domain that are critical for catalysis. Through statistical comparisons of diverse tyrosine kinase sequences, we identify residues unique to BTK that coincide with the experimentally determined PHTH-binding surface on the kinase domain. Our data provide a more complete picture of the autoinhibitory conformation adopted by full-length TEC kinases, creating opportunities to target the regulatory domains to control the function of these kinases in a biological setting.
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Agammaglobulinemia Tirosina Quinasa/química , Agammaglobulinemia Tirosina Quinasa/metabolismo , Agammaglobulinemia Tirosina Quinasa/genética , Regulación Alostérica , Sitios de Unión , Humanos , Metabolismo de los Lípidos , Lípidos/química , Espectroscopía de Resonancia Magnética , Modelos Moleculares , Dominios Homólogos a Pleckstrina , Dominios Proteicos , Proteínas Tirosina Quinasas/química , Proteínas Tirosina Quinasas/genética , Proteínas Tirosina Quinasas/metabolismoRESUMEN
BACKGROUND: Protein kinases are among the largest druggable family of signaling proteins, involved in various human diseases, including cancers and neurodegenerative disorders. Despite their clinical relevance, nearly 30% of the 545 human protein kinases remain highly understudied. Comparative genomics is a powerful approach for predicting and investigating the functions of understudied kinases. However, an incomplete knowledge of kinase orthologs across fully sequenced kinomes severely limits the application of comparative genomics approaches for illuminating understudied kinases. Here, we introduce KinOrtho, a query- and graph-based orthology inference method that combines full-length and domain-based approaches to map one-to-one kinase orthologs across 17 thousand species. RESULTS: Using multiple metrics, we show that KinOrtho performed better than existing methods in identifying kinase orthologs across evolutionarily divergent species and eliminated potential false positives by flagging sequences without a proper kinase domain for further evaluation. We demonstrate the advantage of using domain-based approaches for identifying domain fusion events, highlighting a case between an understudied serine/threonine kinase TAOK1 and a metabolic kinase PIK3C2A with high co-expression in human cells. We also identify evolutionary fission events involving the understudied OBSCN kinase domains, further highlighting the value of domain-based orthology inference approaches. Using KinOrtho-defined orthologs, Gene Ontology annotations, and machine learning, we propose putative biological functions of several understudied kinases, including the role of TP53RK in cell cycle checkpoint(s), the involvement of TSSK3 and TSSK6 in acrosomal vesicle localization, and potential functions for the ULK4 pseudokinase in neuronal development. CONCLUSIONS: In sum, KinOrtho presents a novel query-based tool to identify one-to-one orthologous relationships across thousands of proteomes that can be applied to any protein family of interest. We exploit KinOrtho here to identify kinase orthologs and show that its well-curated kinome ortholog set can serve as a valuable resource for illuminating understudied kinases, and the KinOrtho framework can be extended to any protein-family of interest.
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Evolución Biológica , Genómica , Humanos , Anotación de Secuencia Molecular , Proteínas Quinasas/genética , Proteínas Serina-Treonina Quinasas , ProteínasRESUMEN
Glycosyltransferases (GTs) play a central role in sustaining all forms of life through the biosynthesis of complex carbohydrates. Despite significant strides made in recent years to establish computational resources, databases and tools to understand the nature and role of carbohydrates and related glycoenzymes, a data analytics framework that connects the sequence-structure-function relationships to the evolution of GTs is currently lacking. This hinders the characterization of understudied GTs and the synthetic design of GTs for medical and biotechnology applications. Here, we present GTXplorer as an integrated platform that presents evolutionary information of GTs adopting a GT-A fold in an intuitive format enabling in silico investigation through comparative sequence analysis to derive informed hypotheses about their function. The tree view mode provides an overview of the evolutionary relationships of GT-A families and allows users to select phylogenetically relevant families for comparisons. The selected families can then be compared in the alignment view at the residue level using annotated weblogo stacks of the GT-A core specific to the selected clade, family, or subfamily. All data are easily accessible and can be downloaded for further analysis. GTXplorer can be accessed at https://vulcan.cs.uga.edu/gtxplorer/ or from GitHub at https://github.com/esbgkannan/GTxplorer to deploy locally. By packaging multiple data streams into an accessible, user-friendly format, GTXplorer presents the first evolutionary data analytics platform for comparative glycomics.
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Biología Computacional , Glicosiltransferasas/química , Biocatálisis , Carbohidratos/biosíntesis , Carbohidratos/química , Glicómica , Glicosiltransferasas/metabolismo , Pliegue de ProteínaRESUMEN
BACKGROUND: Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential response shown by altered kinases to drug treatment in patients and cell-based assays. However, an incomplete understanding of the relationships connecting genome, proteome and drug sensitivity profiles present a major bottleneck in targeting kinases for personalized medicine. RESULTS: In this study, we propose a multi-component Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model and neural networks framework for providing explainable models of protein kinase inhibition and drug response ([Formula: see text]) profiles in cell lines. Using non-small cell lung cancer as a case study, we show that interaction terms that capture associations between drugs, pathways, and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib). In particular, protein-protein interactions associated with the JNK apoptotic pathway, associations between lung development and axon extension, and interaction terms connecting drug substructures and the volume/charge of mutant residues at specific structural locations contribute significantly to the observed [Formula: see text] values in cell-based assays. CONCLUSIONS: By integrating multi-omics data in the QSMART model, we not only predict drug responses in cancer cell lines with high accuracy but also identify features and explainable interaction terms contributing to the accuracy. Although we have tested our multi-component explainable framework on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles.
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Redes Neurales de la Computación , Inhibidores de Proteínas Quinasas/química , Relación Estructura-Actividad Cuantitativa , Afatinib/farmacología , Carcinoma de Pulmón de Células no Pequeñas/metabolismo , Carcinoma de Pulmón de Células no Pequeñas/patología , Línea Celular Tumoral , Receptores ErbB/antagonistas & inhibidores , Receptores ErbB/genética , Receptores ErbB/metabolismo , Humanos , Lapatinib/farmacología , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/patología , Sistema de Señalización de MAP Quinasas/efectos de los fármacos , Mutación , Medicina de Precisión , Mapas de Interacción de Proteínas/efectos de los fármacos , Inhibidores de Proteínas Quinasas/metabolismo , Inhibidores de Proteínas Quinasas/farmacologíaRESUMEN
The homeodomain-interacting protein kinase (HIPK) family is comprised of four nuclear protein kinases, HIPK1-4. HIPK proteins phosphorylate a diverse range of transcription factors involved in cell proliferation, differentiation, and apoptosis. HIPK2, thus far the best-characterized member of this largely understudied family of protein kinases, plays a role in the activation of p53 in response to DNA damage. Despite this tumor-suppressor function, HIPK2 is also found overexpressed in several cancers, and its hyperactivation causes chronic fibrosis. There are currently no structures of HIPK2 or of any other HIPK kinase. Here, we report the crystal structure of HIPK2's kinase domain bound to CX-4945, a casein kinase 2α (CK2α) inhibitor currently in clinical trials against several cancers. The structure, determined at 2.2 Å resolution, revealed that CX-4945 engages the HIPK2 active site in a hybrid binding mode between that seen in structures of CK2α and Pim1 kinases. The HIPK2 kinase domain crystallized in the active conformation, which was stabilized by phosphorylation of the activation loop. We noted that the overall kinase domain fold of HIPK2 closely resembles that of evolutionarily related dual-specificity tyrosine-regulated kinases (DYRKs). Most significant structural differences between HIPK2 and DYRKs included an absence of the regulatory N-terminal domain and a unique conformation of the CMGC-insert region and of a newly defined insert segment in the αC-ß4 loop. This first crystal structure of HIPK2 paves the way for characterizing the understudied members of the HIPK family and for developing HIPK2-directed therapies for managing cancer and fibrosis.
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Proteínas Portadoras/química , Proteínas Serina-Treonina Quinasas/química , Secuencia de Aminoácidos , Sitios de Unión , Proteínas Portadoras/clasificación , Proteínas Portadoras/metabolismo , Dominio Catalítico , Cristalografía por Rayos X , Evolución Molecular , Humanos , Simulación de Dinámica Molecular , Naftiridinas/química , Naftiridinas/metabolismo , Fenazinas , Filogenia , Unión Proteica , Proteínas Serina-Treonina Quinasas/clasificación , Proteínas Serina-Treonina Quinasas/metabolismo , Estructura Terciaria de Proteína , Proteínas Recombinantes/biosíntesis , Proteínas Recombinantes/química , Proteínas Recombinantes/aislamiento & purificación , Alineación de SecuenciaRESUMEN
The faithful propagation of cellular signals in most organisms relies on the coordinated functions of a large family of protein kinases that share a conserved catalytic domain. The catalytic domain is a dynamic scaffold that undergoes large conformational changes upon activation. Most of these conformational changes, such as movement of the regulatory αC-helix from an "out" to "in" conformation, hinge on a conserved, but understudied, loop termed the αC-ß4 loop, which mediates conserved interactions to tether flexible structural elements to the kinase core. We previously showed that the αC-ß4 loop is a unique feature of eukaryotic protein kinases. Here, we review the emerging roles of this loop in kinase structure, function, regulation, and diseases. Through a kinome-wide analysis, we define the boundaries of the loop for the first time and show that sequence and structural variation in the loop correlate with conformational and regulatory variation. Many recurrent disease mutations map to the αC-ß4 loop and contribute to drug resistance and abnormal kinase activation by relieving key auto-inhibitory interactions associated with αC-helix and inter-lobe movement. The αC-ß4 loop is a hotspot for post-translational modifications, protein-protein interaction, and Hsp90 mediated folding. Our kinome-wide analysis provides insights for hypothesis-driven characterization of understudied kinases and the development of allosteric protein kinase inhibitors.
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Mutación , Proteínas Quinasas/química , Proteínas Quinasas/metabolismo , Secuencias de Aminoácidos , Resistencia a Antineoplásicos/genética , Evolución Molecular , Humanos , Conformación Proteica , Dominios y Motivos de Interacción de Proteínas , Proteínas Quinasas/genética , Procesamiento Proteico-PostraduccionalRESUMEN
We describe the application of T4 DNA ligase-catalyzed DNA templated oligonucleotide polymerization toward the evolution of a diversely functionalized nucleic acid aptamer for human α-thrombin. Using a 256-membered ANNNN comonomer library comprising 16 sublibraries modified with different functional groups, a highly functionalized aptamer for thrombin was raised with a dissociation constant of 1.6 nM. The aptamer was found to be selective for thrombin and required the modifications for binding affinity. This study demonstrates the most differentially functionalized nucleic acid aptamer discovered by in vitro selection and should enable the future exploration of functional group dependence during the evolution of nucleic acid polymer activity.
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Aptámeros de Nucleótidos/química , Técnica SELEX de Producción de Aptámeros/métodos , Trombina/análisis , Aptámeros de Nucleótidos/metabolismo , Secuencia de Bases , ADN Ligasas/metabolismo , Biblioteca de Genes , Humanos , Trombina/metabolismoRESUMEN
The development and in-depth analysis of T4 DNA ligase-catalyzed DNA templated oligonucleotide polymerization toward the generation of diversely functionalized nucleic acid polymers is described. The NNNNT codon set enables low codon bias, high fidelity, and high efficiency for the polymerization of ANNNN libraries comprising various functional groups. The robustness of the method was highlighted in the copolymerization of a 256-membered ANNNN library comprising 16 sub-libraries modified with different functional groups. This enabled the generation of diversely functionalized synthetic nucleic acid polymer libraries with 93.8 % fidelity. This process should find ready application in DNA nanotechnology, DNA computing, and inâ vitro evolution of functional nucleic acid polymers.
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ADN Ligasas/metabolismo , ADN/biosíntesis , Polímeros/metabolismo , ADN/química , Polímeros/químicaRESUMEN
The understudied members of the druggable proteomes offer promising prospects for drug discovery efforts. While large-scale initiatives have generated valuable functional information on understudied members of the druggable gene families, translating this information into actionable knowledge for drug discovery requires specialized informatics tools and resources. Here, we review the unique informatics challenges and advances in annotating understudied members of the druggable proteome. We demonstrate the application of statistical evolutionary inference tools, knowledge graph mining approaches, and protein language models in illuminating understudied protein kinases, pseudokinases, and ion channels.
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Informática , ProteomaRESUMEN
In eukaryotes, protein kinase signaling is regulated by a diverse array of post-translational modifications (PTMs), including phosphorylation of Ser/Thr residues and oxidation of cysteine (Cys) residues. While regulation by activation segment phosphorylation of Ser/Thr residues is well understood, relatively little is known about how oxidation of cysteine residues modulate catalysis. In this study, we investigate redox regulation of the AMPK-related Brain-selective kinases (BRSK) 1 and 2, and detail how broad catalytic activity is directly regulated through reversible oxidation and reduction of evolutionarily conserved Cys residues within the catalytic domain. We show that redox-dependent control of BRSKs is a dynamic and multilayered process involving oxidative modifications of several Cys residues, including the formation of intramolecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys within an unusual CPE motif at the end of the activation segment. Consistently, mutation of the CPE-Cys increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family.
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The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships among protein kinase sequence, structure, function, and disease in a human and machine-readable format. In this study, we have significantly expanded ProKinO by incorporating additional data on expression patterns and drug interactions. Furthermore, we have developed a completely new browser from the ground up to render the knowledge graph visible and interactive on the web. We have enriched ProKinO with new classes and relationships that capture information on kinase ligand binding sites, expression patterns, and functional features. These additions extend ProKinO's capabilities as a discovery tool, enabling it to uncover novel insights about understudied members of the protein kinase family. We next demonstrate the application of ProKinO. Specifically, through graph mining and aggregate SPARQL queries, we identify the p21-activated protein kinase 5 (PAK5) as one of the most frequently mutated dark kinases in human cancers with abnormal expression in multiple cancers, including a previously unappreciated role in acute myeloid leukemia. We have identified recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation. Additionally, we have identified common ligand/drug binding residues in PAK family kinases, underscoring ProKinO's potential application in drug discovery. The updated ontology browser and the addition of a web component, ProtVista, which enables interactive mining of kinase sequence annotations in 3D structures and Alphafold models, provide a valuable resource for the signaling community. The updated ProKinO database is accessible at https://prokino.uga.edu.
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Neoplasias , Proteínas Quinasas , Humanos , Proteínas Quinasas/genética , Ligandos , Proteínas/genética , FosforilaciónRESUMEN
The current understanding of farnesyltransferase (FTase) specificity was pioneered through investigations of reporters like Ras and Ras-related proteins that possess a C-terminal CaaX motif that consists of 4 amino acid residues: cysteine-aliphatic1-aliphatic2-variable (X). These studies led to the finding that proteins with the CaaX motif are subject to a 3-step post-translational modification pathway involving farnesylation, proteolysis, and carboxylmethylation. Emerging evidence indicates, however, that FTase can farnesylate sequences outside the CaaX motif and that these sequences do not undergo the canonical 3-step pathway. In this work, we report a comprehensive evaluation of all possible CXXX sequences as FTase targets using the reporter Ydj1, an Hsp40 chaperone that only requires farnesylation for its activity. Our genetic and high-throughput sequencing approach reveals an unprecedented profile of sequences that yeast FTase can recognize in vivo, which effectively expands the potential target space of FTase within the yeast proteome. We also document that yeast FTase specificity is majorly influenced by restrictive amino acids at a2 and X positions as opposed to the resemblance of CaaX motif as previously regarded. This first complete evaluation of CXXX space expands the complexity of protein isoprenylation and marks a key step forward in understanding the potential scope of targets for this isoprenylation pathway.
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Transferasas Alquil y Aril , Saccharomyces cerevisiae , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Farnesiltransferasa/genética , Farnesiltransferasa/metabolismo , Secuencia de Aminoácidos , Transferasas Alquil y Aril/genética , Transferasas Alquil y Aril/metabolismo , Prenilación de Proteína , Proteínas/genética , Especificidad por SustratoRESUMEN
Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The Doublecortin Like Kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory 'tail' segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to 'supercharge' the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other Calcium Calmodulin Kinases (CAMKs), and a 'Swiss-army' assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for auto-regulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor-binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome-wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically-divergent DCLK1 modulators, stabilizers or degraders.
RESUMEN
Autophosphorylation controls the transition between discrete functional and conformational states in protein kinases, yet the structural and molecular determinants underlying this fundamental process remain unclear. Here we show that c-terminal Tyr 530 is a de facto c-Src autophosphorylation site with slow time-resolution kinetics and a strong intermolecular component. On the contrary, activation-loop Tyr 419 undergoes faster kinetics and a cis-to-trans phosphorylation switch that controls c-terminal Tyr 530 autophosphorylation, enzyme specificity, and strikingly, c-Src non-catalytic function as a substrate. In line with this, we visualize by X-ray crystallography a snapshot of Tyr 530 intermolecular autophosphorylation. In an asymmetric arrangement of both catalytic domains, a c-terminal palindromic phospho-motif flanking Tyr 530 on the substrate molecule engages the G-loop of the active kinase adopting a position ready for entry into the catalytic cleft. Perturbation of the phospho-motif accounts for c-Src dysfunction as indicated by viral and colorectal cancer (CRC)-associated c-terminal deleted variants. We show that c-terminal residues 531 to 536 are required for c-Src Tyr 530 autophosphorylation, and such a detrimental effect is caused by the substrate molecule inhibiting allosterically the active kinase. Our work reveals a crosstalk between the activation and c-terminal segments that control the allosteric interplay between substrate- and enzyme-acting kinases during autophosphorylation.