Fast protein folding is governed by memory-dependent friction.

When described by a low-dimensional reaction coordinate, the folding rates of most proteins are determined by a subtle interplay between free-energy barriers, which separate folded and unfolded states, and friction. While it is commonplace to extract free-energy profiles from molecular trajectories, a direct evaluation of friction is far more elusive and typically relies on fits of measured reaction rates to memoryless reaction-rate theories. Here, using memory-kernel extraction methods founded on a generalized Langevin equation (GLE) formalism, we directly calculate the time-dependent friction acting on the fraction of native contacts reaction coordinate Q, evaluated for eight fast-folding proteins, taken from a published set of large-scale molecular dynamics protein simulations. Our results reveal that, across the diverse range of proteins represented in this dataset, friction is more influential than free-energy barriers in determining protein folding rates. We also show that proteins fold in a regime where the finite decay time of friction significantly reduces the folding times, in some instances by as much as a factor of 10, compared to predictions based on memoryless friction.

Non-Markovian modeling of protein folding.

We extract the folding free energy landscape and the time-dependent friction function, the two ingredients of the generalized Langevin equation (GLE), from explicit-water molecular dynamics (MD) simulations of the α-helix forming polypeptide [Formula: see text] for a one-dimensional reaction coordinate based on the sum of the native H-bond distances. Folding and unfolding times from numerical integration of the GLE agree accurately with MD results, which demonstrate the robustness of our GLE-based non-Markovian model. In contrast, Markovian models do not accurately describe the peptide kinetics and in particular, cannot reproduce the folding and unfolding kinetics simultaneously, even if a spatially dependent friction profile is used. Analysis of the GLE demonstrates that memory effects in the friction significantly speed up peptide folding and unfolding kinetics, as predicted by the Grote-Hynes theory, and are the cause of anomalous diffusion in configuration space. Our methods are applicable to any reaction coordinate and in principle, also to experimental trajectories from single-molecule experiments. Our results demonstrate that a consistent description of protein-folding dynamics must account for memory friction effects.

Generalized Langevin equation with a nonlinear potential of mean force and nonlinear memory friction from a hybrid projection scheme.

We introduce a hybrid projection scheme that combines linear Mori projection and conditional Zwanzig projection techniques and use it to derive a generalized Langevin equation (GLE) for a general interacting many-body system. The resulting GLE includes (i) explicitly the potential of mean force (PMF) that describes the equilibrium distribution of the system in the chosen space of reaction coordinates, (ii) a random force term that explicitly depends on the initial state of the system, and (iii) a memory friction contribution that splits into two parts: a part that is linear in the past reaction-coordinate velocity and a part that is in general nonlinear in the past reaction coordinates but does not depend on velocities. Our hybrid scheme thus combines all desirable properties of the Zwanzig and Mori projection schemes. The nonlinear memory friction contribution is shown to be related to correlations between the reaction-coordinate velocity and the random force. We present a numerical method to compute all parameters of our GLE, in particular the nonlinear memory friction function and the random force distribution, from a trajectory in reaction coordinate space. We apply our method on the dihedral-angle dynamics of a butane molecule in water obtained from atomistic molecular dynamics simulations. For this example, we demonstrate that nonlinear memory friction is present and that the random force exhibits significant non-Gaussian corrections. We also present the derivation of the GLE for multidimensional reaction coordinates that are general functions of all positions in the phase-space of the underlying many-body system; this corresponds to a systematic coarse-graining procedure that preserves not only the correct equilibrium behavior but also the correct dynamics of the coarse-grained system.

Universal and Nonuniversal Aspects of Electrostatics in Aqueous Nanoconfinement.

Dielectric water properties, which significantly change in confinement, determine electrostatic interactions and thereby influence all molecular forces and chemical reactions. We present comparative simulations of water between graphene sheets, decanol monolayers, and phospholipid and glycolipid bilayers. Generally, dielectric profiles strongly differ in perpendicular and parallel surface directions and for large surface separation decay to the bulk value 1-2 nm away from the surface. Polar surface groups enhance the local interfacial dielectric response and for phospholipid bilayers induce a giant parallel contribution. A mapping on a box model with asymptotically determined effective water layer widths demonstrates that the perpendicular effective dielectric constant for all systems decreases for confinement below a nanometer, while the parallel one stays rather constant. The confinement-dependent perpendicular effective dielectric constant for graphene is in agreement with experimental data only if the effective water layer width is suitably adjusted. The interactions between two charges at small separation depend on the product of parallel and perpendicular effective water dielectric components; for large separation the interactions depend on the confining medium. For metallic confining media the interactions at large separation decay exponentially with a decay length that depends on the ratio of the effective parallel and perpendicular water dielectric components.

Giant Axial Dielectric Response in Water-Filled Nanotubes and Effective Electrostatic Ion-Ion Interactions from a Tensorial Dielectric Model.

Molecular dynamics simulations in conjunction with effective medium theory are used to investigate dielectric effects in water-filled nanotubes. The resulting effective axial dielectric constant shows a divergent increase for small nanotube radii that depends on the nanotube length, while the effective radial dielectric constant decreases significantly for thin nanotubes. By solving Poisson's equation for an anisotropic dielectric medium in cylindrical geometry, we show that the axial ion-ion interaction depends for small separations primarily on the radial dielectric constant, not on the axial one. This means that electrostatic ion-ion interactions in thin water-filled nanotubes are on the linear dielectric level significantly enhanced due to water confinement effects at small separations, while at large separations the outside medium dominates. If the outside medium is metallic, then the ion-ion interaction decays exponentially for large ion separation.

Breakdown of Linear Dielectric Theory for the Interaction between Hydrated Ions and Graphene.

Many vital processes taking place in electrolytes, such as nanoparticle self-assembly, water purification, and the operation of aqueous supercapacitors, rely on the precise many-body interactions between surfaces and ions in water. Here we study the interaction between a hydrated ion and a charge-neutral graphene layer using atomistic molecular dynamics simulations. For small separations, the ion-graphene repulsion is of nonelectrostatic nature, and for intermediate separations, van der Waals attraction becomes important. Contrary to prevailing theory, we show that nonlinear and tensorial dielectric effects become non-negligible close to surfaces, even for monovalent ions. This breakdown of standard isotropic linear dielectric theory has important consequences for the understanding and modeling of charged objects at surfaces.