DC5
Artificially designed protein binders to investigate intraflagellar transport in ciliogenesis (WP1)
Supervisor: Dr Esben Lorentzen
Host Institute: Aarhus University, Denmark
Secondments: Human Technopole, Italy; University of Copenhagen, Denmark
Doctoral Program: Aarhus University
Artificially designed protein binders to investigate intraflagellar transport in ciliogenesis
AI-based methods now allow for accurate structure prediction of protein complexes using AlphaFold as well as the design of artificial proteins with specifically tailored functions. These developments will be leveraged to design artificial proteins to bind and alter the function of the intraflagellar transport (IFT) machinery, which is essential for ciliogenesis. It was recently shown using Alphafold modelling and electron tomography that the IFT complex can adopt two widely different conformations relying on different protein interfaces of the same protein subunits. We hypothesize that each of these two conformations is required for IFT to the ciliary tip (anterograde IFT) and back to the ciliary base (retrograde IFT), respectively. To investigate this hypothesis, we will design artificial proteins to bind IFT88 or the IFT52/46 sub-complex that are predicted to block each of the two observed IFT complex conformation. These binder proteins will be validated in silico using AlphaFold and purified to experimentally confirm the predicted function using pull-down assays with purified components. Successful binders will be introduced into Chlamydomonas reinhardtii and mammalian RPE cells and the impact on IFT and ciliogenesis monitored, which will allow us to unravel the function of different IFT complex formations in anterograde and retrograde IFT. Additionally, a local pipeline running AlphaFold 3 will be utilized to uncover novel ciliary cargoes of the IFT system followed by experimental investigation of predicted cargoes.
Fellow profile: Master degree in biochemistry, biophysics, bioinformatics, structural biology or related field. This project is very suitable for students with experience in biochemistry/biophysics, structural biology and/or computational biology.