Martina Audagnotto
Realistic models of cellular environments have long captured the imagination of biologists and physical scientists. More than 20 years ago, Goodshellâs inspiring rendering of cellular environments provided the foundation for the idea of capturing the full complexity of biological cells. Since then, increasingly realistic simulations of subcellular models have appeared, showing that we are rapidly moving towards comprehensive, as well as physically and biologically accurate cellular models. The major challenge in developing such models is the necessity to cover a wide range of scales. Indeed, atomistic details of molecular processes are on the length scale of 0.1 nm, while cellular dimensions range from 300 nm (for the smallest bacterial cells) up to 100 ÎŒm (for large eukaryotic cells). The biological range also encompasses the internal dynamics of individual molecules (from ns to ms) as well as entire biological processes (ms to hours). Although an atomistic representation of an entire cell is conceivable, the cost for achieving biologically significant timescales with most advanced computers is very high or nearly impossible currently. Therefore, the combination of in silico approaches with in vivo and in vitro experimental data, allows gaining further insights into the biophysics of the cell. In this thesis, a multi-scale approach was applied to investigate the interplay between proteins and their respective biological environments. In particular, two specific systems were the objects of my Ph.D. project: (i) the amyloid precursor protein (APP) and its interactions at the synaptic plasma membrane, and (ii) the human acyl-protein thioesterase I (hAPT1) and its role in protein depalmitoylation cycle across the Golgi and plasma membranes. Combining atomistic and coarse-grained molecular dynamics (MD) simulations, the stability of the dimeric conformation of APP in a realistic model of the synaptic plasma membrane was investigated. Within this approach, the stable dimeric conformation of the APP as a function of lipid membrane composition was identified, highlighting the important role of lipids unsaturation in protein stability and function. In detail, this indicated not only the preferential dimerization motif of the protein, but also the possible recruiting mode of cholesterol, which has previously been experimentally observed to correlate with Alzheimerâs disease. Furthermore, the role of the synaptic plasma membrane and its ability to form raft microdomains was explored for the interactions of APP with γ-secretase, which specific catalytic cleavage is responsible for the production of physiological or toxic amyloid β peptides, responsible for the Alzheimerâs disease onset. This same multi-scale approach was applied to understand the role of S-acylation in the trafficking and function of hAPT1. In particular, the combination of experimental techniques (i.e., cell biology, biochemistry, microscopy and structural biology) with molecular modeling and simulation disclosed the substrate/enzyme interaction mode, the enzyme/membrane interface, and the role for hAPT1 for a key post-translational modification as S-palmitoylation. Based on our findings, we provided for the first time an atomistic representation of the hAPT1 enzyme mechanism, suggesting that hAPT1 is active in the monomeric form. In conclusion, these studies demonstrate once more the importance of modeling the molecular details of the biological environment at the most accu
EPFL2017
