Biology subjects

Evans, G. L.

Publications and source records attributed to Evans, G. L..

4 recordsLinked to original sources

bioRxiv2026

PDBe-SIFTS: an open-source tool for Structure Integration with Function, Taxonomy, and Sequences, featuring improved alignment, scoring scheme, and accelerated search

Structure Integration with Function, Taxonomy and Sequences (SIFTS) provides residue-level mappings between UniProt Knowledgebase sequences and Protein Data Bank structures and has historically been generated through internal Protein Data Bank in Europe (PDBe) pipelines. Here, PDBe-SIFTS is presented as a fully open-source, locally deployable implementation of this mapping framework. The pipeline combines fast, scalable sequence search using MMseqs2, an improved bounded scoring scheme for ranking candidate mappings, and residue-level mapping refinement based on backbone connectivity. PDBe-SIFTS is distributed as a Python package with command-line tools for 1) building a sequence search database, 2) identifying the best sequence-structure match, 3) one-to-one mapping at the residue level, and 4) generating SIFTS annotations in PDBx/mmCIF format. Benchmarking on the complete Protein Data Bank archive showed that MMseqs2 reduced archive-scale UniProtKB searches from hours with BLASTP to minutes, approximately 22-36 times faster, while curated mappings were recovered at top rank in 93.1% of cases. The remaining discrepancies mainly involved biologically ambiguous cases such as highly conserved proteins, chimeric constructs, or closely related orthologs. These results show that PDBe-SIFTS enables fast mapping, improving structural coherence in residue-level alignments while delivering the most up-to-date and accurate mappings, comparable to expert curation. Tool: https://github.com/PDBeurope/SIFTS Quick start notebook with example: https://github.com/PDBeurope/SIFTS/tree/master/notebooks Broader audience statementMatching protein sequences to their three-dimensional structures, and mapping annotations across both, is essential for understanding protein function, interactions, and molecular mechanisms. This integrated view enables richer interpretation of biological data and underpins advances in drug discovery, disease research, and protein engineering. PDBe-SIFTS provides an open and functional framework for structure-sequence mapping, allowing researchers and databases to run, inspect, and extend these mappings locally, while benefiting from faster searches, transparent scoring, and structurally informed residue-level alignments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/721839v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@5e6ea6org.highwire.dtl.DTLVardef@1b2754dorg.highwire.dtl.DTLVardef@1334f9forg.highwire.dtl.DTLVardef@1b083a1_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Human-in-the-loop approach to identify functionally important residues of proteins from literature

We present a novel system that leverages curators in the loop to develop a dataset and model for detecting residue-level functional annotations and other protein structure features from standard publication text. Our approach involves the integration of data from multiple resources, including PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidelines from UniProt, while employing LitSuggest and Huggingface models as tools in the annotation process. A team of seven annotators manually curated ten articles for named entities, which we utilized to train a starting PubmedBert model from Huggingface. Using a human-in-the-loop annotation system, we developed the best model with commendable performance metrics of 0.90 for precision, 0.92 for recall, and 0.91 for F1-measure. Our proposed system showcases a successful synergy of machine learning techniques and human expertise in curating a dataset for residue-level functional annotations and protein structure features. The results demonstrate the potential for broader applications in protein research, bridging the gap between advanced machine learning models and the indispensable insights of domain experts.

bioinformatics↗

bioRxiv2023

Structural analysis of the Sterile alpha motif (SAM) domain of the Arabidopsis mitochondrial tRNA import receptor

Mitochondria are membrane bound organelles of endosymbiotic origin with limited protein coding capacity. As a consequence, the continual import of nuclear-encoded protein and nucleic acids such as DNA and small non-coding RNA is required and essential for maintaining organelle mass, number and activity. As plant mitochondria do not encode all the necessary tRNA types required, the import of cytosolic tRNA is vital for organelle maintenance. Recently, two mitochondrial outer membrane proteins, named Tric1 and Tric2, for tRNA import component, were shown to be involved in the import of cytosolic tRNA. Tric1/2 binds tRNAala via conserved residues in the C-terminal Sterile Alpha Motif (SAM) domain. Here we report the X-ray crystal structure of the Tric1 SAM domain. We identified the ability of the SAM domain to form a helical superstructure with 6 SAM domains per helical turn and key amino acid residues responsible for its formation. We determined that the oligomerization of Tric1 SAM domain was essential for protein function whereby mutation of Gly241 resulted in the disruption of the oligomer and the loss of RNA binding capability in Tric1. Furthermore, complementation of Arabidopsis thaliana Tric1/2 knockout lines with a mutated Tric1 failed to restore the defective plant phenotype suggesting the oligomerization is essential for function in planta. AlphaFold2 structure prediction of the SAM domain and Tric1 support a cyclic hexamer generating a pore of sufficient dimensions to transfer tRNA across the mitochondrial membrane. Our results highlight the importance of oligomerization of Tric1 for protein function.

biochemistry↗

bioRxiv2019

A functionally conserved mechanism of modulation via a vestibule site in pentameric ligand-gated ion channels

Pentameric ligand-gated ion channels (pLGICs) belong to a class of ion channels involved in fast synaptic signaling in the central and peripheral nervous systems. Molecules acting as allosteric modulators target binding sites that are remote from the neurotransmitter binding site, but functionally affect coupling of ligand binding to channel opening. Here, we investigated an allosteric binding site in the ion channel vestibule, which has converged from a series of studies on prokaryote and eukaryote channel homologs. We discovered single domain antibodies, called nanobodies, which are functionally active as allosteric modulators, and solved co-crystal structures of the prokaryote channel ELIC bound either to a positive (PAM) or a negative (NAM) allosteric modulator. We extrapolate the functional importance of the vestibule binding site to eukaryote ion channels, suggesting a conserved mechanism of allosteric modulation. This work identifies key elements of allosteric binding sites and extends drug design possibilities in pLGICs using nanobodies.

neuroscience↗