Molecular constraints of the Major histocompatibility complex I (MHC I) protein

Understanding the molecular determinants of the Major histocompatibility complex I (MHC I) protein interactions with viral or cancer proteins.

Biological & technical background

The major histocompatibility complex (MHC) is an essential set of cell surface proteins that allows the immune system to recognize foreign molecules on the surface of virus-infected or cancer cells. In human populations, there are thousands of variants of MHCs and understanding their differences is key to predict their function and the disease susceptibility of different individuals. Using mathematical tools (mainly probabilities) to analyse large experimental datasets, we will show how we can uncover several properties of MHC molecule interactions and how this can inform us about the key properties of these molecules in immune mechanisms to fight diseases.

Goal

This project will investigate the molecular constraints of MHC I protein when it binds to peptides of foreign molecules.

Methods

The student will get familiar to protein sequence analysis (conservation, entropy and mutual information), as well as basic principles of protein structure and interaction analysis in medically relevant cases (cancer + viral infection). The students will use implemented software available on web portails and R.

Things to be learned from this

R coding, comparative genomics, bioinformatics and information theory. The project will overall offer additional experience using R, protein sequences alignment.

Supervisor

Linda Dib, Computation biologist, post-doc in David Gfeller Lab (Department of Oncology, Computational cancer group, LUDWIG, UNIL). David Gfeller: head of Computational Cancer Biology (Department of Oncology, LUDWIG, UNIL). Both supervisors are english and french speakers.

References

Carbone A, Dib L. Coevolution and information signals in biological sequences. Theor. Comput. Sc. (2011), 412: 2486-2495. Cover TM. and Thomas JA. Elements of Information Theory. John Wiley, 1991. Dib L, Carbone A. (2012a). Protein fragments: functional and structural roles of their coevolution networks. PLoS One, 7: e48124. Dib L, Silvestro D, Salamin N. (2014). Evolutionary footprint of coevolving positions in genes. Bioinformatics, 30 (9): 1241-1249. Lichtarge O., Bourne H.R., Cohen F.E., An evolutionary trace method defines binding surfaces common to protein families, J. Mol. Biol. 257 (1996). 342–358. Morcos F, Pagnanib A, Lunta B, Bertolinoc A, Marksd D, Sander C, Zecchinab R, Onuchica J, Hwaa T, Weigt M. (2011). Direct-coupling analysis of residue coevolution captures native contacts across many protein families. Proc. Natl. Acad. Sci. USA 108, E1293-1301.