Proteins mediate cellular functions by interacting with each other and with other biomolecules such as DNA, RNA, or metabolites. Thus, protein interactions determine the function of a gene and its protein product. The protein interactome describes the entirety of all protein interactions in a cell, and underlies genotype-to-phenotype relationships. Deciphering the cellular contexts under which protein interactions take place, how these interactions form, and what their functional outcome is remains inherently difficult. Yet, this knowledge is required to accurately predict how genetic mutations, toxins, and pathogens alter protein interactions and thereby perturb cellular function and cause disease (Figure 1).

Understanding genotype-to-phenotype relationships starts with identifying the underlying interactome. However, while the genomes, transcriptomes, and proteomes of entire human populations down to single cells have now been mapped, the mapping of protein interactomes remains very challenging. More recently, various major research efforts have produced the first systematic, proteome-wide maps of the human protein interactome (Figure 2, Luck et al. Nature 2020, Huttlin et al. BioRxiv 2020, Luck et al. TiBS 2017). However, due to technical limitations, these resources do not provide information on the molecular function, mode of binding, or cellular context of the interactions (Figure 2).

The aim of my lab is to develop integrative computational and experimental strategies that efficiently annotate protein interactions with information on their structure, function, and cellular context. We will then apply these approaches to predict and validate the molecular mechanisms of genome maintenance processes that are perturbed in neurodevelopmental disorders.

We are a highly interdisciplinary and collaborative lab, integrating omics data analyses with structural and network biology to build predictive models of molecular mechanisms, which we then validate using biophysical and cellular approaches. We favour data-driven approaches to make novel biological discoveries.

Projects

Prediction & experimental validation of interfaces in protein interactions

Identifying the regions and specific residues that mediate an interaction between two proteins is critical to predict which mutations will perturb the interaction, which interaction partners have overlapping binding regions (and are therefore mutually exclusive), and which interactions can co-exist (and thus mediate the assembly of larger protein complexes).

Furthermore, identifying binding regions often provides additional information on the molecular function of the interaction. Experimental characterisation of protein interaction interfaces often involves mutational scanning or protein fragmentation, which are both laborious and highly error-prone due to possible nonspecific perturbation of the entire protein fold. Many protein interactions are mediated by globular domains that either bind other types of globular domains or short stretches of amino acids (so-called linear motifs) that occur in disordered regions of proteins (Figure 3). We develop novel approaches to predict known types of domain-domain and domain-linear motif interfaces, discover novel types of interfaces in known protein interactions, and seek to experimentally validate these predictions by designing and testing compensatory mutations in the predicted interaction interface.