iCASE In silico characterisation of portal proteins for application as biosensors

Nanopore sequencing pioneered by Oxford Nanopore Technologies (ONT) is based on DNA threading through an engineered version of CsgG, a secretion protein from E. coli . Electric-field induced threading of DNA through the pore-shaped portal protein imbedded within an impermeable membrane produces the reduction in ionic current recorded by the apparatus. The current profile is characteristic to the nucleotide bases passing through the pore, enabling identification of the bas sequence. Nanopore bases sequencing has already proved to have multiple strengths including portability, real-time data acquisition, analysis of long and ultra-long reads, direct RNA sequencing and detection of base-modifications over other sequencing methodologies.

The scope of nanopore technology has great potential to be extended towards other biomedical applications including protein sequencing, detection of posttranslational modifications, in situ detection of toxins, viral particles and other analytes. This project aims to drive further development of advantageous nanopore biosensing opening new perspectives in molecular and cellular medicine.
Versatile biosensing requires engineering of new portal proteins with feasible properties such as effective membrane embedding, stability under the assay conditions, and proper pore-analyte complementarity. This research will apply computational methods to guide rational optimisation of physical and chemical properties of viral portal proteins allowing their application as biosensors. Several computational techniques will be combined to perform characterization of candidate proteins. Classical molecular dynamics (atomistic and coarse-grained) will be used alongside quantum mechanics calculations to provide thorough, predictive characterization. In addition, protein sequence optimisation will be facilitated by harnessing the recent progress in protein-related Deep Learning models such as AlphaFold2 . The computational experiments will be iteratively...