12P - Swiss-PO: Molecular modelling for precision oncology

Background

Swiss-PO is a web tool to map gene mutations on the 3D structure of corresponding proteins and to intuitively assess the structural implications of protein variants for precision oncology. Swiss-PO is constructed around a manually curated database of 3D structures, variant annotations, and sequence alignments, for a list of 50 genes taken from the Ion AmpliSeq^TM Custom Cancer Hotspot Panel. The website was designed to guide users in the choice of the most appropriate structure to analyze regarding the mutated residue, the role of the protein domain it belongs to, or the drug that could be selected to treat the patient. The importance of the mutated residue for the structure and activity of the protein can be assessed based on the molecular interactions exchanged with neighbor residues in 3D within the same protein or between different biomacromolecules, its conservation in orthologs, or the known effect of reported mutations in its 3D or sequence-based vicinity.

Methods

The data, retrieved from UniProt/Swiss-Prot, the PDB, and the CKB CORE, were used and manually curated to create Swiss-PO databases.

Results

Swiss-PO proposes a database that currently covers 50 oncodriver genes, +7000 mutations and PTMs, +400 amino acid sequences, +1700 experimental structures extracted from PDB.

Conclusions

Swiss-PO has been designed to be used interactively in the preparation or during MTBs, where key aspects of decision support are made available to the medical oncologist, pathologist or biologist. As such, this web service should facilitate the complex therapeutic choices needed to guide precision oncology. The Swiss-PO database should be enriched in future releases to cover 624 genes. We will also be adding structural models generated by Swiss-Model and AlphaFold. We will also complement the variant panels with other databases. Finally, a new structure-based scoring function for predicting potentially damaging mutations in kinases will be added, a function capitalizing on known structures extracted from the PDB. In addition, a prediction tool for the BRAF mutation class will be introduced, and a new section dedicated to kinases will be offered with useful information concerning kinase inhibitors, families and mutations.

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

University of Lausanne.

Disclosure

All authors have declared no conflicts of interest.