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

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

Biological & technical background

The major histocompatibility complex (MHC) is an essential set of cell surface proteins that allows the immune system to recognize foreign molecule such as viruses or cancer cells. There are three classes of MHC and studying their molecular constraints is challenging since each class is polygenic, that is, several genes encode it, and polymorphic, that is, there are multiple variants of each gene within the human population. MHC I protein is characterised by two polypeptide chains, α and β2-microglobulin allowing it to bind to 8-10 amino acid in length peptides and to inform the immune system about the presence of foreign molecules. This protein is the essential since it initiates a cascade of molecular actions that will target viral or cancerous cells. Therefore identifying the molecular constraints of this protein is helpful to elucidate why the immune system sometimes fails to detect these cells and allows the proliferation of tumour cells in the body.

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 information theory used in comparative genomics: Shannon entropy, joint entropy and mutual information mathematical. The students will used 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 will also contribute to the project. 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.