Projects Offered

1 PhD project offered in the IPP summer call Molecular Mechanisms in Genome Stability & Gene Regulation

Scientific Background

Protein-protein interactions (PPIs) mediate most cellular processes and are key in understanding disease mechanisms. Various high throughput (HTP) methods map at increasing depth and breadth PPIs, yet do not provide information on how proteins interact with each other. In fact, only for about 5% of all known human PPIs a structure of the interaction has been resolved. This lack in structural information hinders our mechanistic understanding of physiological and pathological processes and limits our understanding of the structural diversity with which proteins interact with each other as well as how protein binding evolves. Experimental approaches will not be able to close this knowledge gap in structural information soon. Artificial intelligence (AI)-based approaches gain huge momentum in the ability to learn from experimental data and make meaningful predictions, taking AlphaFold and its highly accurate protein structure prediction as an example. However, the training of powerful AI tools requires comprehensive and unbiased datasets, which we lack for the prediction of protein complex structures. Many PPIs involve disordered regions that mediate binding, however, due to their conformational flexibility and transient mode of binding, are particularly underrepresented in current protein structure datasets. To advance in our understanding of modes of protein binding involving disordered regions of proteins, how they contribute to human disease, and to generate the data that we need to obtain more potent AI tools, we need novel computational and experimental approaches to efficiently chart the landscape of protein-protein binding.

PhD Project: Systematic discovery of novel modes of protein-protein binding involving intrinsically disordered protein regions

This PhD project will combine primarily experimental but also computational approaches to discover novel modes of protein-protein binding and characterize their interaction specificities in a quantitative way. To this end, we will leverage existing expertise in the Luck lab on the use of AlphaFold and other structure prediction methods to prioritize PPIs that are likely mediated by a novel mode of protein binding. A new assay will be implemented enabling HTP identification of interacting protein regions using pooled fragment screens and sequencing as readout. Identified interacting regions will be further validated with site-directed mutagenesis and bioluminescence resonance energy transfer measurements in live cells in 96 well format. High-content screening microscopy will be employed to further characterize interfaces and disease-associated mutations overlapping with these interfaces. A focus on PPIs functioning in mRNA splicing or proteostasis with functional follow-ups is possible via existing collaborations. No prior knowledge in programming or bioinformatics as well as structural biology is required but an interest in learning the basics of those as well as in systematic, HTP approaches would be important. 

If you are interested in this project, please select Luck as your group preference in the IPP application platform.

Publications relevant to this project

Lee CY, Hubrich D, Varga JK, Schäfer C, Welzel M, Schumbera E, Djokic M, Strom JM, Schönfeld J, Geist JL, Polat F, Gibson TJ, Keller Valsecchi CI, Kumar M, Schueler-Furman O, Luck K (2024) Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation. Mol Syst Biol, 20:75-97 Link

Luck K, Kim DK, Lambourne L, Spirohn K, …, Hill DE, Vidal M, Roth FP, Calderwood MA (2020) A reference map of the human binary protein interactome. Nature 580:402-408 Link

Strom JM, Luck K. (2025) Bias in, bias out - AlphaFold-Multimer and the structural complexity of protein interfaces.Curr Opin Struct Biol, 91:103002 Link

Geist JL, Lee CY, Strom JM, de Jesús Naveja J, Luck K. (2024) Generation of a high confidence set of domain-domain interface types to guide protein complex structure predictions by AlphaFold. Bioinformatics, 40(8):btae482 Link

Ebersberger S, Hipp C, Mulorz MM, Buchbender A, Hubrich D, Kang HS, Martínez-Lumbreras S, Kristofori P, Sutandy FXR, Llacsahuanga Allcca L, Schönfeld J, Bakisoglu C, Busch A, Hänel H, Tretow K, Welzel M, Di Liddo A, Möckel MM, Zarnack K, Ebersberger I, Legewie S, Luck K, Sattler M, König J (2023) FUBP1 is a general splicing factor facilitating 3' splice site recognition and splicing of long introns. Mol Cell, 83:2653-2672 Link

Arroyo M, Casas-Delucchi CS, Pabba MK, Prorok P, Pradhan SK, Rausch C, Lehmkuhl A, Maiser A, Buschbeck M, Pasque V, Bernstein E, Luck K, Cardoso MC  (2024) Histone variant macroH2A1 regulates synchronous firing of replication origins in the inactive X chromosome. Nucleic Acids Res, 27:gkae734 Link