Protein dynamics

Résumé

Proteins are generally thought to adopt unique structures determined by their amino acid sequences. However, proteins are not strictly static objects, but rather populate ensembles of (sometimes similar) conformations. Transitions between these states occur on a variety of length scales (tenths of Å to nm) and time scales (ns to s), and have been linked to functionally relevant phenomena such as allosteric signaling and enzyme catalysis. The study of protein dynamics is most directly concerned with the transitions between these states, but can also involve the nature and equilibrium populations of the states themselves. These two perspectives—kinetics and thermodynamics, respectively—can be conceptually synthesized in an "energy landscape" paradigm: highly populated states and the kinetics of transitions between them can be described by the depths of energy wells and the heights of energy barriers, respectively. Local flexibility: atoms and residues

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https://en.wikipedia.org/wiki/Protein_dynamics

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MAS NMR Studies of Hierarchical Interplay in Protein Dynamics

Baptiste Busi

The functionality of proteins is governed by the interplay between their structure and dynamics. Thus, understanding the mechanism and nature of protein motion is essential to understand their biological activity. Here we present and evaluate a novel method to study the basic and fundamental question concerning hierarchical protein motions. What are the dynamical modes of a protein, what is the interplay of these different modes, and how are they linked to the energy landscape of the protein? It is known that different motional modes are present simultaneously in the protein system. These motions occur at different time scales and at the same and/or different regions in the protein, while simultaneously influencing each other. All these motions can be described as thermally activated fluctuations. Nuclear spin relaxation parameters measured by nuclear magnetic resonance (NMR) are modulated primary by motions around the nuclear site. Thus, they are uniquely suited to study protein dynamics since it is possible to simultaneously gather information about different motional timescales and of different parts of the protein.

EPFL2021

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Similarities and Differences among Protein Dynamics Studied by Variable Temperature Nuclear Magnetic Resonance Relaxation

Andrea Bertarello, Baptiste Busi, David Lyndon Emsley, François Freymond, Jayasubba Reddy Yarava

Understanding and describing the dynamics of proteins is one of the major challenges in biology. Here, we use multifield variable-temperature NMR longitudinal relaxation (R-1) measurements to determine the hierarchical activation energies of motions of four different proteins: two small globular proteins (GB1 and the SH3 domain of alpha-spectrin), an intrinsically disordered protein (the C-terminus of the nucleoprotein of the Sendai virus, Sendai Ntail), and an outer membrane protein (OmpG). The activation energies map the motions occurring in the side chains, in the backbone, and in the hydration shells of the proteins. We were able to identify similarities and differences in the average motions of the proteins. We find that the NMR relaxation properties of the four proteins do share similar features. The data characterizing average backbone motions are found to be very similar, the same for methyl group rotations, and similar activation energies are measured. The main observed difference occurs for the intrinsically disordered Sendai Ntail, where we observe much lower energy of activation for motions of protons associated with the protein-solvent interface as compared to the others. We also observe variability between the proteins regarding side chain N-15 relaxation of lysine residues, with a higher activation energy observed in OmpG. This hints at strong interactions with negatively charged lipids in the bilayer and provides a possible mechanistic clue for the "positive-inside" rule for helical membrane proteins. Overall, these observations refine the understanding of the similarities and differences between hierarchical dynamics in proteins.

AMER CHEMICAL SOC2021

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Characteristic timescales associated with the function of biomolecules, like proteins, range from femtoseconds up to minutes, whereas their corresponding spatial extent ranges from few ̊A to μm when associating in large macromolecular complexes. Moreover, biomolecules are functional in a large variety of different physico-chemical conditions strongly dependent on pH, ionic strength, crowding agents, etc. This huge complexity is hard to be studied with an arbitrary level of resolution embracing all these spatial and temporal scales. Molecular simulation is a well established approach to gain mechanistic insights into the function of biomolecular systems, producing atomistically detailed models of in vitro and/or in vivo conditions. I present in this thesis two projects that aim at improving on the current limitations of multiscale molecular simulations, namely (i) the sampling of large systems, and (ii) the detailed representation and description of realistic physiological conditions. Addressing the first issue, I propose a new coarse-grained model for proteins to be used in molecular dynamics simulations. This coarse-grained model is based on a more accurate description of protein electrostatics, which accounts for dipolar contributions. The parameterization of this force field is based on force-matching methods and on the use of a particle swarm optimization heuristic algorithm. The obtained results are encouraging being structural and electrostatic properties accurately reproduced with the coarse-grained model for a variety of protein folds. Moreover, the parameterization procedure can be straightforwardly applied to any protein, and can be extended to a larger dataset to generate a fully transferable coarse-grained force field, to be applied to any protein and any large macromolecular assemblies for which long all-atom simulations are still a challenge. While the development and use of coarse-grained models are important to tackle the limited sampling of large systems, it is still important to use all-atom molecular dynamics simulation to investigate with high accuracy in physiological conditions protein dynamics. For this reason, I present here the results of state-of-art molecular dynamics simulations applied to study the influence of crowding agents on the internal dynamics of the protein ubiquitin. Their analysis allows to describe how ubiquitin dynamics is slaved by crowding agents. This work demonstrates that the description of protein dynamics should take into account its intrinsic multiscale nature. The development and applications of coarse-grained models permit to simulate proteins at low computational cost, the use of atomistic simulations allows to accurately describe proteins in absence and presence of crowding agents, and both of them permit to highlight the essence of protein dynamics.

EPFL2013

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EPFL2013