ADAM17 mediates proteolytic maturation of voltage-gated calcium channel auxiliary α2δ subunits, and enables calcium current enhancement

The auxiliary alpha(2)delta subunits of voltage-gated calcium (Ca-V) channels are key to augmenting expression and function of Ca(V)1 and Ca(V)2 channels, and are also important drug targets in several therapeutic areas, including neuropathic pain. The alpha(2)delta proteins are translated as pre-proteins encoding both alpha(2) and delta, and post-translationally proteolysed into alpha(2) and delta subunits, which remain associated as a complex. In this study we have identified ADAM17 as a key protease involved in proteolytic processing of pro-alpha(2)delta-1 and alpha(2)delta-3 subunits. We provide three lines of evidence: firstly, proteolytic cleavage is inhibited by chemical inhibitors of particular metalloproteases, including ADAM17. Secondly, proteolytic cleavage of both alpha(2)delta-1 and alpha(2)delta-3 is markedly reduced in cell lines by knockout of ADAM17 but not ADAM10. Thirdly, proteolytic cleavage is reduced by the N-terminal active domain of TIMP-3 (N-TIMP-3), which selectively inhibits ADAM17. We have found previously that proteolytic cleavage into mature alpha(2)delta is essential for the enhancement of Ca-V function, and in agreement, knockout of ADAM17 inhibited the ability of alpha(2)delta-1 to enhance both Ca(V)2.2 and Ca(V)1.2 calcium currents. Finally, our data also indicate that the main site of proteolytic cleavage of alpha(2)delta-1 is the Golgi apparatus, although cleavage may also occur at the plasma membrane. Thus, our study identifies ADAM17 as a key protease required for proteolytic maturation of alpha(2)delta-1 and alpha(2)delta-3, and thus a potential drug target in neuropathic pain

The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies

Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology

Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies

Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe – Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms

Annotating Macromolecular Complexes in the Protein Data Bank: Improving the FAIRness of Structure Data

Abstract Macromolecular complexes are essential functional units in nearly all cellular processes, and their atomic-level understanding is critical for elucidating and modulating molecular mechanisms. The Protein Data Bank (PDB) serves as the global repository for experimentally determined structures of macromolecules. Structural data in the PDB offer valuable insights into the dynamics, conformation, and functional states of biological assemblies. However, the current annotation practices lack standardised naming conventions for assemblies in the PDB, complicating the identification of instances representing the same assembly. In this study, we introduce a method leveraging resources external to PDB, such as the Complex Portal, UniProt and Gene Ontology, to describe assemblies and contextualise them within their biological settings accurately. Employing the proposed approach, we assigned standard names and provided value-added annotations to over 90% of unique assemblies in the PDB. This standardisation of assembly data enhances the PDB, facilitating a deeper understanding of these cellular components. Furthermore, the data standardisation improves the PDB’s FAIR attributes, fostering more effective basic and translational research and education across scientific disciplines

Annotating Macromolecular Complexes in the Protein Data Bank: Improving the FAIRness of Structure Data

Abstract Macromolecular complexes are essential functional units in nearly all cellular processes, and their atomic-level understanding is critical for elucidating and modulating molecular mechanisms. The Protein Data Bank (PDB) serves as the global repository for experimentally determined structures of macromolecules. Structural data in the PDB offer valuable insights into the dynamics, conformation, and functional states of biological assemblies. However, the current annotation practices lack standardised naming conventions for assemblies in the PDB, complicating the identification of instances representing the same assembly. In this study, we introduce a method leveraging resources external to PDB, such as the Complex Portal, UniProt and Gene Ontology, to describe assemblies and contextualise them within their biological settings accurately. Employing the proposed approach, we assigned standard names to over 90% of unique assemblies in the PDB and provided persistent identifiers for each assembly. This standardisation of assembly data enhances the PDB, facilitating a deeper understanding of macromolecular complexes. Furthermore, the data standardisation improves the PDB’s FAIR attributes, fostering more effective basic and translational research and scientific education