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Biology subjects

Meyer, D. F.

Publications and source records attributed to Meyer, D. F..

2 recordsLinked to original sources

HInt: interaction-based homology discovery through accelerated genome-scale AlphaFold screening

Identifying homologous proteins across deep evolutionary distances remains a major challenge because sequence and structural similarity progressively become undetectable over time. Although protein-protein interactions (PPIs) are often constrained by function and evolution, whether conserved interaction interfaces can provide an independent signal for homology detection has remained largely unexplored owing to the computational cost of proteome-scale interaction prediction. Here we introduce HInt (Homology by Interaction), an accelerated AlphaFold-based framework that enables practical proteome-scale PPI prediction through biologically informed pre-filtering and optimised high-throughput structure modelling. Using HInt, we establish interaction-based similarity as a third axis of homology detection. We show that conserved interaction interfaces reveal homologous relationships that remain inaccessible to conventional sequence- and structure-based approaches. Application of HInt to both prokaryotic and eukaryotic systems, together with experimental validation, uncovered a previously unrecognised VirB5 pilus-tip protein in the F-plasmid type IV secretion system and a previously unannotated F-box-like protein in the Saccharomyces cerevisiae ubiquitin-proteasome system. By enabling practical proteome-scale interaction screening, HInt provides a general framework for uncovering hidden homologues and expands the conceptual landscape of protein homology inference.

molecular biology↗

Searching Algorithm for Type IV Effector proteins (S4TE) 2.0: improved tools for type IV effector prediction, analysis and comparison

Bacterial pathogens have evolved numerous strategies to corrupt, hijack or mimic cellular processes in order to survive and proliferate. Among those strategies, Type IV effectors (T4Es) are proteins secreted by pathogenic bacteria to manipulate host cell processes during infection. They are delivered into eukaryotic cells in an ATP-dependent manner via the type IV secretion system, a specialized multiprotein complex. T4Es contain a wide spectrum of features including eukaryotic-like domains, localization signals or a C-terminal translocation signal. A combination of these features enables prediction of T4Es in a given bacterial genome. In this study, we developed a web-based comprehensive suite of tools with a user-friendly graphical interface. This version 2.0 of S4TE (Searching Algorithm for Type IV Effector Proteins; http://sate.cirad.fr) enables accurate prediction and comparison of T4Es. Search parameters and threshold can be customized by the user to work with any genome sequence, whether publicly available or not. Applications range from characterizing effector features and identifying potential T4Es to analyzing the effectors based on the genome G+C composition and local gene density. S4TE 2.0 allows the comparison of putative T4E repertoires of up to four bacterial strains at the same time. The software identifies T4E orthologs among strains and provides a Venn diagram and lists of genes for each intersection. New interactive features offer the best visualization of the location of candidate T4Es and hyperlinks to NCBI and Pfam databases. S4TE 2.0 is designed to evolve rapidly with the publication of new experimentally validated T4Es, which will reinforce the predictive power of the algorithm. The computational methodology can be used to identify a wide spectrum of candidate bacterial effectors that lack sequence conservation but have similar amino acid characteristics. This approach will provide very valuable information about bacterial host-specificity and virulence factors, and help identify host targets for the development of new anti-bacterial molecules.

bioinformatics↗