Coupling between protein, water, and lipid dynamics in complex biological systems: Theory and Experiments
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- Ana-Nicoleta Bondar (Free University of Berlin, Germany)
- Zoe Cournia (Academy of Athens, Greece)
- Coral del Val (University of Granada, Spain)
- Jeremy C. Smith (Oak Ridge National Laboratory, USA)
Correct operation of the cellular machinery depends on the proper functioning of proteins involved in essential cellular processes such as nutrient transport, cell signaling, or protein biosynthesis. The rapidly increasing computational power and method developments allow us now to sample at the atomic level of detail the dynamics of complex protein nanomachines on timescales relevant to biology. The remarkable complexity of protein architectures revealed by recent crystal structures raises the key question of how different components of the protein machinery communicate with each other to enable function. Moreover, the important concept emerges that coupling to lipids and water can influence significantly protein dynamics and even enzyme activity. Our workshop aims to serve as a platform where distinguished and junior theoreticians and experimentalists address in depth the state-of the art and future challenges in bridging molecular dynamics simulations to the biological context. The important new aspect brought by this highly interdisciplinary workshop is that it strives to unify concepts on lipid- and water-coupled protein dynamics.
Developments in theoretical methods and specialized computers enable us to explore efficiently the conformational fluctuations of a protein (Harder et al 2012), sample the atomic-level dynamics of proteins on biologically relevant timescales (Dror et al 2010), use molecular dynamics trajectories to describe the effect of mutations or ligand binding (Carrillo et al 2012), reconstruct the complex lipid composition of a bacterial membrane (Piggot et al 2011), or assess membrane proteins under a transmembrane voltage (Delemote et al 2011, Kutzner et al 2011). Coarse-grained simulations allow us to assess protein and lipid dynamics on long timescales, and for large systems (Rodgers et al 2012, Periole et al 2012). Recent experiments have highlighted the essential role of dynamics in enzyme function (Bhaba et al 2011, Henzler-Wildman et al 2007), but the precise role of conformational dynamics in enzyme catalysis was debated (Adamczyk et al 2011). The combination of systematic bioinformatics analyses with molecular dynamics emerges as a powerful tool not only to identify conserved amino acids and their interactions, but also to short-list promising mutants for experimental investigations (Bondar et al 2010).
The advances in computational methodologies provide the foundation to tackle complex aspects of the functioning of large biological nanomachineries. Of particular interest is to understand how large protein complexes orchestrate the communication between remote regions of the complex: A local chemical reaction or binding of a ligand can rapidly trigger large-scale conformational changes even at remote regions of the protein system. Experiments and theory have recently illustrated complex protein machineries that employ remarkable long-distance couplings – for example, the Sec translocon system (Bondar and White 2012, Zimmer et al 2008, Frauenfeld et al 2011), ion pumps from the P-type ATPase family (Palmgreen and Niessen 2011, Sonntag et al 2011), the respiratory complex I (Efremov et al 2010), cyclin-dependent kinases (de Vivo et al 2011), or metalloproteases (Wallnoefer et al 2010). But protein reaction mechanisms may rely not only on intra-protein couplings: recent data from experiments and computations document significant effects of the lipid membrane composition on the dynamics and functioning of the protein (Bondar et al 2010, Hakizimana et al 2008, Urban and Wolfe 2005), and couplings of water dynamics to enzyme reactions (Grossman et al 2011).
The need to account for environment effects and to accurately sample the long-timescale conformational dynamics makes it challenging for computational biophysics techniques to characterize the atomic-detail detailed mechanism of protein nanomachines in a physiological environment. Recent molecular dynamics simulations provide molecular pictures of how a proteins communicates with the lipid membrane environment – the P-type ATPase SERCA was found to adapt its local structure and dynamics to the thickness of the lipid membrane (Sonntag et al 2011), cholesterol is essential for the structure of the acethylcholine receptor (Brannigan et al 2008), and the GlpG intramembrane protease induces a significant thinning of the surrounding lipid bilayer (Bondar et al 2009).
The picture of how proteins function becomes even more complicated if we consider the coupling between water and enzyme dynamics (Grossman et al 2011, Kurkal-Siebert et al 2008). Dissecting the coupling between water and protein dynamics poses challenges to computer simulations: Structurally conserved waters cannot always be determined experimentally and, if observed, the dynamics of water molecules in the various conformational states of the protein is difficult to predict. To accurately account for the coupling between water and protein dynamics, a complete thermodynamic analysis may be necessary. There have been major advances in methodologies to predict water in protein-ligand complexes (see, for example, Michel et al 2009a), and in demonstrating the versatility and importance of water in ligand binding (Luccarelli et al 2010, Michel et al 2009b).
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