Molecular Effects of Concentrated Solutes on Protein Hydration, Dynamics, and Electrostatics

Most studies of protein structure and function are performed in dilute conditions, but proteins typically experience high solute concentrations in their physiological scenarios and biotechnological applications. High solute concentrations have well-known effects on coarse protein traits like stability, diffusion, and shape, but likely also perturb other traits through finer effects pertinent at the residue and atomic levels. Here, NMR and molecular dynamics investigations on ubiquitin disclose variable interactions with concentrated solutes that lead to localized perturbations of the protein's surface, hydration, electrostatics, and dynamics, all dependent on solute size and chemical properties. Most strikingly, small polar uncharged molecules are sticky on the protein surface, whereas charged small molecules are not, but the latter still perturb the internal protein electrostatics as they diffuse nearby. Meanwhile, interactions with macromolecular crowders are favored mainly through hydrophobic, but not through polar, surface patches. All the tested small solutes strongly slow down water exchange at the protein surface, whereas macro molecular crowders do not exert such strong perturbation. Finally, molecular dynamics simulations predict that unspecific interactions slow down microsecond- to millisecond-timescale protein dynamics despite having only mild effects on pico- to nanosecond fluctuations as corroborated by NMR. We discuss our results in the light of recent advances in understanding proteins inside living cells, focusing on the physical chemistry of quinary structure and cellular organization, and we reinforce the idea that proteins should be studied in native-like media to achieve a faithful description of their function.

Multiscale simulations of protein dynamics

Enrico Spiga

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

Combining RNAi and in vivo confocal microscopy analysis of the photoconvertible fluorescent protein Dendra2 to study a DNA repair protein

Matteo Di Piazza

Clinical approaches for tumor treatment often rely on combination therapy where a DNA damaging agent is used in combination with a DNA repair protein inhibitor. For this reason, great efforts have been made during the last decade to identify inhibitors of DNA repair proteins or, alternatively, small molecules that specifically alter protein stability or trafficking. Unfortunately, when studying these drug candidates, classical biochemical approaches are prone to artifacts. The apurinic/apyrimidinic endonuclease (APE1) protein is an essential component of the base excision repair (BER) pathway that is responsible for repairing DNA damage caused by oxidative and alkylating agents. In this work, we combined conditional gene expression knockdown of APE1 protein by RNA interference (RNAi) technology with re-expression of an ectopic recombinant form of APE1 fused with the photoconvertible fluorescent protein (PCFP) Dendra2. Dendra2 did not alter the subcellular localization or endonuclease activity of APEI. We calculated APE1 half-life and compared these results with the classical biochemical approach, which is based on cycloheximide (CHX) treatment. In conclusion, we combined RNAi and in vivo confocal microscopy to study a DNA repair protein demonstrating the feasibility and the advantage of this approach for the study of the cellular dynamic of a DNA repair protein

Biotechniques Office2013

Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules

Stefano Zamuner

Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins, if the average over buried fragments collected from different non-redundant native structures is considered. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, although with significant deviations at short spatial scales, we use it to define a 'bona fide' reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored.

PUBLIC LIBRARY SCIENCE2022

Multiscale simulations of protein dynamics

Enrico Spiga

EPFL2013