Molecular dynamics simulations of the intrinsically disordered protein amelogenin

Amelogenin refers to a class of intrinsically disordered proteins that are the major constituents of enamel matrix derivative (EMD), an extract of porcine fetal teeth used in regenerative periodontal therapy. Modifications in molecular conformation induced by external stresses, such as changes in temperature or pH, are known to reduce the effectiveness of EMD. However, detailed descriptions of the conformational behavior of native amelogenin are lacking in the open literature. In the present work, a molecular model for the secondary and tertiary structure of the full-length major porcine amelogenin P173 was constructed from its primary sequence by replica exchange molecular dynamics (REMD) simulations. The REMD results for isolated amelogenin molecules at different temperatures were shown to be consistent with the available spectroscopic data. They therefore represent an important first step toward the simulation of the intra- and intermolecular interactions that mediate self-organization in amelogenin and its behavior in the presence of other EMD components under conditions representative of its therapeutic application.

Molecular Simulation Study of the Competitive Adsorption of H2O and CO2 in Zeolite 13X

Lennart Joos, Berend Smit

The presence of H2O in postcombustion gas streams is an important technical issue for deploying CO2-selective adsorbents. Because of its permanent dipole, H2O can interact strongly with materials where the selectivity for CO2 is a consequence of its quadrupole interacting with charges in the material. We performed molecular simulations to model the adsorption of pure H2O and CO2 as well as H2O/CO2 mixtures in 13X, a popular zeolite for CO2 capture processes that is commercially available. The simulations show that H2O reduces the capacity of these materials for adsorbing CO2 by an order of magnitude and that at the partial pressures of H2O relevant for postcombustion capture, 13X will be essentially saturated with H2O. © 2013 American Chemical Society.

2013

Studying membrane-protein interplay by modeling realistic conditions

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 Î³-secretase, which specific catalytic cleavage is responsible for the production of physiological or toxic amyloid Î² 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

Molecular Modeling of Membrane Embedded Proteins

Thomas Lemmin

Over the past years, molecular modeling and simulation techniques have had a major impact on experimental life sciences. They are capable of providing accurate insight into microscopic mechanisms, which are usually difficult to investigate experimentally. Moreover, the integration of experimental data with molecular modeling appears to be a promising strategy to better understand complex biological processes. In this thesis, molecular dynamics simulation has been used in combination with experimental data to investigate two transmembrane proteins: (i) the bacterial chemoreceptor PhoQ and (ii) the Amyloid Precursor Protein (APP). (i) Bacterial two-component system PhoQ and bacterial membranes. Two-component systems (TCSs) are signaling complexes essential for bacterial survival and virulence. PhoQ is the histidine kinase chemoreceptor of the PhoQ-PhoP tandem machine that detects the concentration of cationic species at the inner membrane of Gram-negative bacteria. A full understanding of the PhoQ signal transduction mechanism is currently hindered by the lack of a complete atomistic structure. In this thesis project, the first structural model of the transmembrane (TM) portion of PhoQ from Escherichia coli was assembled, by using molecular simulations integrated with cross-linking disulfide scanning data. Its structural and dynamic features induce a concerted displacement of the TM helices at the periplasmic side, which modulates a rotation at the cytoplasmic end. This supports the idea that signal transduction is promoted through a combination of scissoring and rotational movements of the TM helices. Knowledge of this complex mechanism is essential in order to understand how the chemical stimuli sensed by the periplasmic sensor domain trigger, via the relay of the HAMP domain, the histidine auto-phosphorylation and kinase/phosphatase activity at the cytoplasmic end. The PhoQ sensor domain lies in close proximity to the membrane. Interaction with anionic lipids, such as phosphophatidylglycerols (PG) and cardiolipins (CL), are thought to play a key role in PhoQ activity. Present in bacterial and mitochondrial membranes, cardiolipins have a unique dimeric structure, which carries up to two charges, i.e. one per phosphate group, and under physiological conditions, can be unprotonated or singly protonated. Exhaustive models and characterization of cardiolipins are to-date scarce; therefore an ab initio parameterization of cardiolipin species for molecular simulation consistent with commonly used force fields is proposed here. Molecular dynamics (MD) simulations based on these models indicate a protonation-dependent lipid packing. A noteworthy interaction with solvating mono- and divalent cations is also observed. The proposed models will contribute to the biophysical and biochemical characterizations of bacterial and mitochondrial membranes and membrane-embedded proteins. (ii) Structural and dynamic properties of the Amyloid Precursor Protein. The Amyloid Precursor Protein (APP) is a type I membrane glycoprotein present at the neuronal synapsis. The proteolytic cleavage of its C-terminal segment produces amyloid-β (Aβ) peptides of different lengths, the deposition of which is an early indicator of Alzheimer"s disease (AD). Recently, the backbone structure of the APP transmembrane (TM) domain in detergent micelles was determined by nuclear magnetic resonance (NMR, independently by two different experimental groups). The TM conformations of these two structures are however markedly different. One is characterized by a highly kinked α-helix, whereas the other is mainly straight. Molecular dynamics simulations showed that the APP TM region is highly flexible and its secondary structure is influenced by the surrounding lipid environment. The size of the embedding detergent micelles strongly affects the conformation of the APP α-helix, with solvation being the main driving force for the development of a helical curvature. Once embedded in a membrane bilayer, APP systematically prefers a straight helical conformation. This is also confirmed when analyzing in silico the atomistic APP population observed in double electron-electron resonance (DEER) spectroscopy. In summary, the APP transmembrane domain is highly flexible due to the presence of glycine residues and can readily respond to the lipid environment, a property that might be critical for proteolytic processing by γ-secretase enzymes. The presented thesis work clearly shows how molecular simulations and their interplay with available experimental input can help advance the understanding of the mechanism of complex biological systems and processes on a molecular scale. These results, in particular, go well beyond the current understanding of the functioning of two transmembrane proteins relevant for human health. Furthermore, the computational approaches and procedures developed in these projects will hopefully promote novel integrated strategies for investigating biological systems.