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Cosentino S, Sriswasdi S, Iwasaki W. SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models. Genome Biol 2024; 25:195. [PMID: 39054525 PMCID: PMC11270883 DOI: 10.1186/s13059-024-03298-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 06/04/2024] [Indexed: 07/27/2024] Open
Abstract
Accurate inference of orthologous genes constitutes a prerequisite for comparative and evolutionary genomics. SonicParanoid is one of the fastest tools for orthology inference; however, its scalability and accuracy have been hampered by time-consuming all-versus-all alignments and the existence of proteins with complex domain architectures. Here, we present a substantial update of SonicParanoid, where a gradient boosting predictor halves the execution time and a language model doubles the recall. Application to empirical large-scale and standardized benchmark datasets shows that SonicParanoid2 is much faster than comparable methods and also the most accurate. SonicParanoid2 is available at https://gitlab.com/salvo981/sonicparanoid2 and https://zenodo.org/doi/10.5281/zenodo.11371108 .
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Affiliation(s)
- Salvatore Cosentino
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, the University of Tokyo, Kashiwa, Japan
| | - Sira Sriswasdi
- Center of Excellence in Computational Molecular Biology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Wataru Iwasaki
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, the University of Tokyo, Kashiwa, Japan.
- Department of Biological Sciences, Graduate School of Science, the University of Tokyo, Bunkyo-ku, Japan.
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo, Kashiwa, Japan.
- Atmosphere and Ocean Research Institute, the University of Tokyo, Kashiwa, Japan.
- Institute for Quantitative Biosciences, the University of Tokyo, Bunkyo-ku, Japan.
- Collaborative Research Institute for Innovative Microbiology, the University of Tokyo, Bunkyo-ku, Japan.
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2
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Li J, Gong C, Zhou H, Liu J, Xia X, Ha W, Jiang Y, Liu Q, Xiong H. Kinase Inhibitors and Kinase-Targeted Cancer Therapies: Recent Advances and Future Perspectives. Int J Mol Sci 2024; 25:5489. [PMID: 38791529 PMCID: PMC11122109 DOI: 10.3390/ijms25105489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/09/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024] Open
Abstract
Over 120 small-molecule kinase inhibitors (SMKIs) have been approved worldwide for treating various diseases, with nearly 70 FDA approvals specifically for cancer treatment, focusing on targets like the epidermal growth factor receptor (EGFR) family. Kinase-targeted strategies encompass monoclonal antibodies and their derivatives, such as nanobodies and peptides, along with innovative approaches like the use of kinase degraders and protein kinase interaction inhibitors, which have recently demonstrated clinical progress and potential in overcoming resistance. Nevertheless, kinase-targeted strategies encounter significant hurdles, including drug resistance, which greatly impacts the clinical benefits for cancer patients, as well as concerning toxicity when combined with immunotherapy, which restricts the full utilization of current treatment modalities. Despite these challenges, the development of kinase inhibitors remains highly promising. The extensively studied tyrosine kinase family has 70% of its targets in various stages of development, while 30% of the kinase family remains inadequately explored. Computational technologies play a vital role in accelerating the development of novel kinase inhibitors and repurposing existing drugs. Recent FDA-approved SMKIs underscore the importance of blood-brain barrier permeability for long-term patient benefits. This review provides a comprehensive summary of recent FDA-approved SMKIs based on their mechanisms of action and targets. We summarize the latest developments in potential new targets and explore emerging kinase inhibition strategies from a clinical perspective. Lastly, we outline current obstacles and future prospects in kinase inhibition.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Huihua Xiong
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (J.L.)
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3
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Taujale R, Gravel N, Zhou Z, Yeung W, Kochut K, Kannan N. Informatic challenges and advances in illuminating the druggable proteome. Drug Discov Today 2024; 29:103894. [PMID: 38266979 DOI: 10.1016/j.drudis.2024.103894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 01/08/2024] [Accepted: 01/17/2024] [Indexed: 01/26/2024]
Abstract
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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Affiliation(s)
- Rahil Taujale
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, USA
| | - Nathan Gravel
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | | | - Wayland Yeung
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | - Krystof Kochut
- School of Computing, University of Georgia, Athens, GA, USA
| | - Natarajan Kannan
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, USA; Institute of Bioinformatics, University of Georgia, Athens, GA, USA.
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4
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Soleymani S, Gravel N, Huang LC, Yeung W, Bozorgi E, Bendzunas NG, Kochut KJ, Kannan N. Dark kinase annotation, mining, and visualization using the Protein Kinase Ontology. PeerJ 2023; 11:e16087. [PMID: 38077442 PMCID: PMC10704995 DOI: 10.7717/peerj.16087] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 08/22/2023] [Indexed: 12/18/2023] Open
Abstract
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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Affiliation(s)
- Saber Soleymani
- Department of Computer Science, University of Georgia, Athens, GA, United States
| | - Nathan Gravel
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
| | - Liang-Chin Huang
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
| | - Wayland Yeung
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
| | - Elika Bozorgi
- Department of Computer Science, University of Georgia, Athens, GA, United States
| | - Nathaniel G. Bendzunas
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
| | - Krzysztof J. Kochut
- Department of Computer Science, University of Georgia, Athens, GA, United States
| | - Natarajan Kannan
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States
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5
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Venkat A, Watterson G, Byrne DP, O'Boyle B, Shrestha S, Gravel N, Fairweather EE, Daly LA, Bunn C, Yeung W, Aggarwal I, Katiyar S, Eyers CE, Eyers PA, Kannan N. Mechanistic and evolutionary insights into isoform-specific 'supercharging' in DCLK family kinases. eLife 2023; 12:RP87958. [PMID: 37883155 PMCID: PMC10602587 DOI: 10.7554/elife.87958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2023] Open
Abstract
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 autoregulation 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.
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Affiliation(s)
- Aarya Venkat
- Department of Biochemistry and Molecular Biology, University of GeorgiaAthensUnited States
| | - Grace Watterson
- Department of Biochemistry and Molecular Biology, University of GeorgiaAthensUnited States
| | - Dominic P Byrne
- Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Brady O'Boyle
- Department of Biochemistry and Molecular Biology, University of GeorgiaAthensUnited States
| | - Safal Shrestha
- Institute of Bioinformatics, University of GeorgiaAthensUnited States
| | - Nathan Gravel
- Institute of Bioinformatics, University of GeorgiaAthensUnited States
| | - Emma E Fairweather
- Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Leonard A Daly
- Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
- Centre for Proteome Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Claire Bunn
- Department of Biochemistry and Molecular Biology, University of GeorgiaAthensUnited States
| | - Wayland Yeung
- Institute of Bioinformatics, University of GeorgiaAthensUnited States
| | - Ishan Aggarwal
- Department of Biochemistry and Molecular Biology, University of GeorgiaAthensUnited States
| | - Samiksha Katiyar
- Department of Biochemistry and Molecular Biology, University of GeorgiaAthensUnited States
| | - Claire E Eyers
- Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
- Centre for Proteome Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Patrick A Eyers
- Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUnited Kingdom
| | - Natarajan Kannan
- Institute of Bioinformatics, University of GeorgiaAthensUnited States
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6
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Venkat A, Watterson G, Byrne DP, O’Boyle B, Shrestha S, Gravel N, Fairweather EE, Daly LA, Bunn C, Yeung W, Aggarwal I, Katiyar S, Eyers CE, Eyers PA, Kannan N. Mechanistic and evolutionary insights into isoform-specific 'supercharging' in DCLK family kinases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.29.534689. [PMID: 37034755 PMCID: PMC10081240 DOI: 10.1101/2023.03.29.534689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
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.
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Affiliation(s)
- Aarya Venkat
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Grace Watterson
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Dominic P. Byrne
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Brady O’Boyle
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Safal Shrestha
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Nathan Gravel
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Emma E. Fairweather
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Leonard A. Daly
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Claire Bunn
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Wayland Yeung
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Ishan Aggarwal
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Samiksha Katiyar
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Claire E. Eyers
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Patrick A. Eyers
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Natarajan Kannan
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
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7
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Nguyen K, Boehling J, Tran MN, Cheng T, Rivera A, Collins-Burow BM, Lee SB, Drewry DH, Burow ME. NEK Family Review and Correlations with Patient Survival Outcomes in Various Cancer Types. Cancers (Basel) 2023; 15:cancers15072067. [PMID: 37046733 PMCID: PMC10093199 DOI: 10.3390/cancers15072067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 03/22/2023] [Accepted: 03/29/2023] [Indexed: 04/03/2023] Open
Abstract
The Never in Mitosis Gene A (NIMA)–related kinases (NEKs) are a group of serine/threonine kinases that are involved in a wide array of cellular processes including cell cycle regulation, DNA damage repair response (DDR), apoptosis, and microtubule organization. Recent studies have identified the involvement of NEK family members in various diseases such as autoimmune disorders, malignancies, and developmental defects. Despite the existing literature exemplifying the importance of the NEK family of kinases, this family of protein kinases remains understudied. This report seeks to provide a foundation for investigating the role of different NEKs in malignancies. We do this by evaluating the 11 NEK family kinase gene expression associations with patients’ overall survival (OS) from various cancers using the Kaplan–Meier Online Tool (KMPlotter) to correlate the relationship between mRNA expression of NEK1-11 in various cancers and patient survival. Furthermore, we use the Catalog of Somatic Mutations in Cancer (COSMIC) database to identify NEK family mutations in cancers of different tissues. Overall, the data suggest that the NEK family has varying associations with patient survival in different cancers with tumor-suppressive and tumor-promoting effects being tissue-dependent.
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Adeyelu T, Bordin N, Waman VP, Sadlej M, Sillitoe I, Moya-Garcia AA, Orengo CA. KinFams: De-Novo Classification of Protein Kinases Using CATH Functional Units. Biomolecules 2023; 13:277. [PMID: 36830646 PMCID: PMC9953599 DOI: 10.3390/biom13020277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 02/05/2023] Open
Abstract
Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence homology); however, very few systematically classify functional families (FunFams) comprising evolutionary relatives that share similar functional properties. We have developed the FunFam-MARC (Multidomain ARchitecture-based Clustering) protocol, which uses multi-domain architectures of protein kinases and specificity-determining residues for functional family classification. FunFam-MARC predicts 2210 kinase functional families (KinFams), which have increased functional coherence, in terms of EC annotations, compared to the widely used KinBase classification. Our protocol provides a comprehensive classification for kinase sequences from >10,000 organisms. We associate human KinFams with diseases and drugs and identify 28 druggable human KinFams, i.e., enriched in clinically approved drugs. Since relatives in the same druggable KinFam tend to be structurally conserved, including the drug-binding site, these KinFams may be valuable for shortlisting therapeutic targets. Information on the human KinFams and associated 3D structures from AlphaFold2 are provided via our CATH FTP website and Zenodo. This gives the domain structure representative of each KinFam together with information on any drug compounds available. For 32% of the KinFams, we provide information on highly conserved residue sites that may be associated with specificity.
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Affiliation(s)
- Tolulope Adeyelu
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
- Department of Comparative Biomedical Science, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Nicola Bordin
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Vaishali P. Waman
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Marta Sadlej
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Aurelio A. Moya-Garcia
- Departamento de Biología Molecular y Bioquímica, Universidad de Málaga, 29071 Málaga, Spain
- Laboratorio de Biología Molecular del Cáncer, Centro de Investigaciones Médico-Sanitarias (CIMES), Universidad de Málaga, 29071 Málaga, Spain
| | - Christine A. Orengo
- Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK
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Byrne DP, Shrestha S, Daly LA, Marensi V, Ramakrishnan K, Eyers CE, Kannan N, Eyers PA. Evolutionary and cellular analysis of the 'dark' pseudokinase PSKH2. Biochem J 2023; 480:141-160. [PMID: 36520605 PMCID: PMC9988210 DOI: 10.1042/bcj20220474] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 12/12/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
Pseudokinases, so named because they lack one or more conserved canonical amino acids that define their catalytically active relatives, have evolved a variety of biological functions in both prokaryotic and eukaryotic organisms. Human PSKH2 is closely related to the canonical kinase PSKH1, which maps to the CAMK family of protein kinases. Primates encode PSKH2 in the form of a pseudokinase, which is predicted to be catalytically inactive due to loss of the invariant catalytic Asp residue. Although the biological role(s) of vertebrate PSKH2 proteins remains unclear, we previously identified species-level adaptions in PSKH2 that have led to the appearance of kinase or pseudokinase variants in vertebrate genomes alongside a canonical PSKH1 paralog. In this paper we confirm that, as predicted, PSKH2 lacks detectable protein phosphotransferase activity, and exploit structural informatics, biochemistry and cellular proteomics to begin to characterise vertebrate PSKH2 orthologues. AlphaFold 2-based structural analysis predicts functional roles for both the PSKH2 N- and C-regions that flank the pseudokinase domain core, and cellular truncation analysis confirms that the N-terminal domain, which contains a conserved myristoylation site, is required for both stable human PSKH2 expression and localisation to a membrane-rich subcellular fraction containing mitochondrial proteins. Using mass spectrometry-based proteomics, we confirm that human PSKH2 is part of a cellular mitochondrial protein network, and that its expression is regulated through client-status within the HSP90/Cdc37 molecular chaperone system. HSP90 interactions are mediated through binding to the PSKH2 C-terminal tail, leading us to predict that this region might act as both a cis and trans regulatory element, driving outputs linked to the PSKH2 pseudokinase domain that are important for functional signalling.
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Affiliation(s)
- Dominic P. Byrne
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Safal Shrestha
- Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602, U.S.A
| | - Leonard A. Daly
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Vanessa Marensi
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Krithika Ramakrishnan
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Claire E. Eyers
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
| | - Natarajan Kannan
- Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602, U.S.A
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, U.S.A
| | - Patrick A. Eyers
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, U.K
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10
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O’Boyle B, Shrestha S, Kochut K, Eyers PA, Kannan N. Computational tools and resources for pseudokinase research. Methods Enzymol 2022; 667:403-426. [PMID: 35525549 PMCID: PMC9733567 DOI: 10.1016/bs.mie.2022.03.040] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Brady O’Boyle
- Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602, USA
| | - Safal Shrestha
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Krzysztof Kochut
- Department of Computer Science, University of Georgia, Athens, GA 30602, USA
| | - Patrick A Eyers
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK
| | - Natarajan Kannan
- Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602, USA,Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA,Corresponding author:
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