The dysregulation of this pathway is implicated in the pathogenesis of several diseases and is even exploited by some pathogens. These qualities make ubiquitin (and other proteins involved in the ubiquitin-proteasome pathway) convincing targets for further therapeutic investigation. By utilising bioinformatic techniques, we can analyse the natural variation of ubiquitin and its evolution across the eukaryotic tree of life to aid in drug discovery.

The student will work with a dataset from one of the ~1.7 billion clusters generated by DIAMOND DeepClust, a project which sought to cluster the ‘protein universe’ of ~19 billion known protein sequences (1). They will utilise R for effective data handling and will construct multiple sequence alignments to uncover novel motifs and significant mutations. Tertiary structures will be investigated through in-silico predictions using the predictive model, AlphaFold3.

This project will equip the student with detailed understanding of the ubiquitin-proteasome pathway and allow them to gain experience in R, sequence analysis and structural bioinformatics. There will also be opportunities to improve their skills in presenting through participation in lab meetings and scientific writing.

The dysregulation of this pathway is implicated in the pathogenesis of several diseases and is even exploited by some pathogens. These qualities make ubiquitin (and other proteins involved in the ubiquitin-proteasome pathway) convincing targets for further therapeutic investigation. By utilising bioinformatic techniques, we can analyse the natural variation of ubiquitin and its evolution across the eukaryotic tree of life to aid in drug discovery.

The student will work with a dataset from one of the ~1.7 billion clusters generated by DIAMOND DeepClust, a project which sought to cluster the ‘protein universe’ of ~19 billion known protein sequences (1). They will utilise R for effective data handling and will construct multiple sequence alignments to uncover novel motifs and significant mutations. Tertiary structures will be investigated through in-silico predictions using the predictive model, AlphaFold3.

This project will equip the student with detailed understanding of the ubiquitin-proteasome pathway and allow them to gain experience in R, sequence analysis and structural bioinformatics. There will also be opportunities to improve their skills in presenting through participation in lab meetings and scientific writing.