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bioRxiv · 10.1101/2021.09.10.459756

Streamlined use of protein structures in variant analysis

Kaur, S.·Sikta, N.·Schafferhans, A.·Bordin, N.·Cowley, M. J.·Thomas, D. M.·Ballinger, M. L.·O'Donoghue, S. I.
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Abstract

MotivationVariant analysis is a core task in bioinformatics that requires integrating data from many sources. This process can be helped by using 3D structures of proteins, which can provide a spatial context that can provide insight into how variants affect function. Many available tools can help with mapping variants onto structures; but each has specific restrictions, with the result that many researchers fail to benefit from valuable insights that could be gained from structural data. ResultsTo address this, we have created a streamlined system for incorporating 3D structures into variant analysis. Variants can be easily specified via URLs that are easily readable and writable, and use the notation recommended by the Human Genome Variation Society (HGVS). For example, https://aquaria.app/SARS-CoV-2/S/?N501Y specifies the N501Y variant of SARS-CoV-2 S protein. In addition to mapping variants onto structures, our system provides summary information from multiple external resources, including COSMIC, CATH-FunVar, and PredictProtein. Furthermore, our system identifies and summarizes structures containing the variant, as well as the variant-position. Our system supports essentially any mutation for any well-studied protein, and uses all available structural data -- including models inferred via very remote homology -- integrated into a system that is fast and simple to use. By giving researchers easy, streamlined access to a wealth of structural information during variant analysis, our system will help in revealing novel insights into the molecular mechanisms underlying protein function in health and disease. AvailabilityOur resource is freely available at the project home page (https://aquaria.app). After peer review, the code will be openly available via a GPL version 2 license at https://github.com/ODonoghueLab/Aquaria. PSSH2, the database of sequence-to-structure alignments, is also freely available for download at https://zenodo.org/record/4279164. Contactsean@odonoghuelab.org Supplementary informationNone.

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Kaur, S., Sikta, N., Schafferhans, A., Bordin, N., Cowley, M. J., Thomas, D. M., Ballinger, M. L., O'Donoghue, S. I.. 2021-09-11. Streamlined use of protein structures in variant analysis. https://doi.org/10.1101/2021.09.10.459756

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