B-P.07: Scaling and democratising structure-based protein function prediction with metagenomic-deepFRI
Valentyn Bezshapkin
Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland
Piotr Kucharski
Aiformatics, Krakow, Poland
Paweł Szczerbiak
Sano Centre for Computational Medicine, Krakow, Poland
Jakub W Wojciechowski
Sano Centre for Computational Medicine, Krakow, Poland
Lukasz M Szydlowski
IRA 3P Medicine Lab; Center for Space Biomedicine and Radiological Protection, Gdansk Medical University, Gdansk, Poland
Tomasz Kosciolek
Sano Centre for Computational Medicine, Krakow, Poland
Keywords
protein structure, protein function, gene ontology, function prediction
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Proteins drive the functioning of all living matter, from cell structural integrity to complex metabolic reactions. While high-throughput sequencing has revealed an large diversity of proteins, driving an exponential expansion of public databases, functional characterization lags behind sequence acquisition. To aid the experimental characterization, numerous computational approaches were developed. One example is deepFRI, a GO-term prediction tool that leverages both sequence and structure of a protein. The inclusion of structure improves both the confidence and specificity of deepFRI's prediction. For large scale metagenomic experiments however, obtaining high quality protein structures for all discovered sequences may be computationally challenging. Metagenomic-deepFRI is an extension of the original pipeline, that allows for automatic retrieval of homologous protein structures from the reference databases such as AlphaFold database or ESM atlas. It leverages lightweight storage of reference protein structures, MMSeqs2 search for scalable retrieval of proteins similar to the query, a quick global-alignment between the query and the matched protein and contact-map construction as a representation of protein structure. Current limitation of metagenomic-deepFRI is that it only predicts Gene Ontology terms, which might be insufficient for thorough investigation of a set of proteins, for example, coming from an environmental sample. Many other modalities could be explored, such as genomic context, oligomeric state of the protein or possible interactions. Metagenomic-deepFRI is therefore under ongoing development, that aims to transform it into a comprehensive pipeline for both bioinformaticians running large scale computations and wet-lab oriented scientists looking for familiarity and ease of use.
Co-authors: Valentyn Bezshapkin, Piotr Kucharski, Pawel Szczerbiak, Jakub Wojciechowski, Lukasz Szydlowski, Tomasz Kosciolek
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