Marveling at the Incredible ULK4

AI-based AlphaFold2 significantly expands the structural space of the autophagy pathway

ABBREVIATIONS

AF2: AlphaFold2; AF2-Mult: AlphaFold2 multimer; ATG: autophagy-related; CTD: C-terminal domain; ECTD: extreme C-terminal domain; FR: flexible region; MD: molecular dynamics; NTD: N-terminal domain; pLDDT: predicted local distance difference test; UBL: ubiquitin-like.

Arterial dissections: Common features and new perspectives

Arterial dissections, which involve an abrupt tear in the wall of a major artery resulting in the intramural accumulation of blood, are a family of catastrophic disorders causing major, potentially fatal sequelae. Involving diverse vascular beds, including the aorta or coronary, cervical, pulmonary, and visceral arteries, each type of dissection is devastating in its own way. Traditionally they have been studied in isolation, rather than collectively, owing largely to the distinct clinical consequences of dissections in different anatomical locations - such as stroke, myocardial infarction, and renal failure. Here, we review the shared and unique features of these arteriopathies to provide a better understanding of this family of disorders. Arterial dissections occur commonly in the young to middle-aged, and often in conjunction with hypertension and/or migraine; the latter suggesting they are part of a generalized vasculopathy. Genetic studies as well as cellular and molecular investigations of arterial dissections reveal striking similarities between dissection types, particularly their pathophysiology, which includes the presence or absence of an intimal tear and vasa vasorum dysfunction as a cause of intramural hemorrhage. Pathway perturbations common to all types of dissections include disruption of TGF-β signaling, the extracellular matrix, the cytoskeleton or metabolism, as evidenced by the finding of mutations in critical genes regulating these processes, including LRP1, collagen genes, fibrillin and TGF-β receptors, or their coupled pathways. Perturbances in these connected signaling pathways contribute to phenotype switching in endothelial and vascular smooth muscle cells of the affected artery, in which their physiological quiescent state is lost and replaced by a proliferative activated phenotype. Of interest, dissections in various anatomical locations are associated with distinct sex and age predilections, suggesting involvement of gene and environment interactions in disease pathogenesis. Importantly, these cellular mechanisms are potentially therapeutically targetable. Consideration of arterial dissections as a collective pathology allows insight from the better characterized dissection types, such as that involving the thoracic aorta, to be leveraged to inform the less common forms of dissections, including the potential to apply known therapeutic interventions already clinically available for the former.

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.

KinOrtho: a method for mapping human kinase orthologs across the tree of life and illuminating understudied kinases

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.