Biology subjects

Ellaway, J. I. J.

Publications and source records attributed to Ellaway, J. I. J..

3 recordsLinked to original sources

bioRxiv2023

Identifying Protein Conformational States in the PDB and Comparison to AlphaFold2 Predictions

Proteins, as molecular machines, are necessarily dynamic macromolecules that carry out essential cellular functions. Recognising their stable conformations is important for understanding the molecular mechanisms of disease. While AI-based computational methods have enabled protein structure prediction, the prediction of protein dynamics remains a challenge. Here, we present a deterministic pipeline that clusters experimentally determined protein structures to comprehensively recognise conformational states across the Protein Data Bank. Our approach clusters protein chains based on a GLObal CONformation (GLOCON) difference score, which is computed from pairwise C-alpha distances. By superposing the clustered structures, differences and similarities in conformational states can be observed. Additionally, we offer users the ability to superpose predicted models from the AlphaFold Database to the clusters of PDB structures. This clustering pipeline significantly advances researchers ability to explore the conformational landscape within the PDB. All clustered and superposed models can be viewed in Mol* on the PDBe Knowledge Base website, or accessed in as raw annotations via our GraphAPI and FTP server. The clustering package is made available as an open-source Python3 package under the Apache-2.0 license.

bioinformatics↗

bioRxiv2023

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

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 PDBs FAIR attributes, fostering more effective basic and translational research and education across scientific disciplines.

bioinformatics↗

bioRxiv2022

High-resolution promoter interaction analysis in Type 3 Innate Lymphoid Cells implicates Batten Disease gene CLN3 in Crohn's Disease aetiology

Innate lymphoid cells (ILCs) are rare, tissue-resident innate lymphocytes that functionally mirror CD4+ T helper cell lineages but lack antigen receptors. Type 3 ILCs (ILC3s) are enriched in the gut, airways, and mucosal lymphoid tissues, where they regulate inflammation and promote barrier integrity. To define the regulatory architecture of primary human ILC3s, we map promoter-anchored chromosomal contacts using high-resolution, low-input Promoter Capture Hi-C (PCHi-C) in these cells alongside CD4+ T cells. By combining statistical detection with a PCHi-C-adapted Activity-by-Contact approach, we link promoters to distal regulatory elements, identifying hundreds of ILC3-specific contacts. We use these maps to connect genome-wide association study (GWAS) risk variants for Crohns disease to target genes using multiCOGS, a Bayesian framework that integrates PCHi-C with summary-statistic imputation and multivariate fine-mapping. This analysis highlights both known and unanticipated candidates, including CLN3, a causal gene for the neurodevelopmental Batten disease. Using a mouse ILC3-like cell line, we show that Cln3 is downregulated upon cytokine stimulation, and Cln3 overexpression alters stimulation-induced transcriptional programmes and cytokine secretion. Extending this approach, we generate a catalogue of ILC3-linked risk genes for five additional autoimmune conditions and show that they are enriched for regulators of the ILC3 inflammatory response identified in a CRISPR interference screen. Together, these findings illuminate long-range gene control in ILC3s and prioritise known and newly implicated autoimmune risk genes with potential roles in this clinically important cell type.

genetics↗