arXiv subjects

Gerhard Stock

Publications and source records attributed to Gerhard Stock.

25 records · Page 2Linked to original sources

arXiv2021

Data-driven Langevin modeling of nonequilibrium processes

Given nonstationary data from molecular dynamics simulations, a Markovian Langevin model is constructed that aims to reproduce the time evolution of the underlying process. While at equilibrium the free energy landscape is sampled, nonequilibrium processes can be associated with a biased energy landscape, which accounts for finite sampling effects and external driving. Extending the data-driven Langevin equation (dLE) approach [Phys.\ Rev.\ Lett.\ {\bf 115}, 050602 (2015)] to the modeling of nonequilibrium processes, an efficient way to calculate multidimensional Langevin fields is outlined. The dLE is shown to correctly account for various nonequilibrium processes, including the enforced dissociation of sodium chloride in water, the pressure-jump induced nucleation of a liquid of hard spheres, and the conformational dynamics of a helical peptide sampled from nonstationary short trajectories.

physics.comp-ph↗

arXiv2020

Real-time observation of ligand-induced allosteric transitions in a PDZ domain

While allostery is of paramount importance for protein regulation, the underlying dynamical process of ligand (un)binding at one site, resulting time evolution of the protein structure, and change of the binding affinity at a remote site is not well understood. Here the ligand-induced conformational transition in a widely studied model system of allostery, the PDZ2 domain, is investigated by transient infrared spectroscopy accompanied by molecular dynamics simulations. To this end, an azobenzene derived photoswitch is linked to a peptide ligand in a way that its binding affinity to the PDZ2 domain changes upon switching, thus initiating an allosteric transition in the PDZ2 domain protein. The subsequent response of the protein, covering four decades of time ranging from $\sim$1~ns to $\sim$10~$μ$s, can be rationalize by a remodelling of its rugged free energy landscape, with ver subtle shifts in the populations of a small number of structurally well defined states. It is proposed that structurally and dynamically driven allostery, often discussed as limiting scenarios of allosteric communication, actually go hand-in-hand, allowing the protein to adapt its free energy landscape to incoming signals.

physics.bio-ph↗

arXiv2020

Multisecond ligand dissociation dynamics from atomistic simulations

Coarse-graining of fully atomistic molecular dynamics simulations is a long-standing goal in order to allow the description of processes occurring on biologically relevant timescales. For example, the prediction of pathways, rates and rate-limiting steps in protein-ligand unbinding is crucial for modern drug discovery. To achieve the enhanced sampling, we first perform dissipation-corrected targeted molecular dynamics simulations, which yield free energy and friction profiles of the molecular process under consideration. In a second step, we use these fields to perform temperature-boosted Langevin simulations which account for the desired molecular kinetics occurring on multisecond timescales and beyond. Adopting the dissociation of solvated sodium chloride as well as trypsin-benzamidine and Hsp90-inhibitor protein-ligand complexes as test problems, we are able to reproduce rates from molecular dynamics simulation and experiments within a factor of 2-20, and dissociation constants within a factor of 1-4. Analysis of the friction profiles reveals that binding and unbinding dynamics are mediated by changes of the surrounding hydration shells in all investigated systems.

physics.bio-ph↗

arXiv2019

Principal component analysis of nonequilibrium molecular dynamics simulations

Principal component analysis (PCA) represents a standard approach to identify collective variables $\{x_i\}\!=\!\boldsymbol{x}$, which can be used to construct the free energy landscape $ΔG(\boldsymbol{x})$ of a molecular system. While PCA is routinely applied to equilibrium molecular dynamics (MD) simulations, it is less obvious how to extend the approach to nonequilibrium simulation techniques. This includes, e.g., the definition of the statistical averages employed in PCA, as well as the relation between the equilibrium free energy landscape $ΔG(\boldsymbol{x})$ and energy landscapes $Δ{\cal G} (\boldsymbol{x})$ obtained from nonequilibrium MD. As an example for a nonequilibrium method, `targeted MD' is considered which employs a moving distance constraint to enforce rare transitions along some biasing coordinate $s$. The introduced bias can be described by a weighting function $P(s)$, which provides a direct relation between equilibrium and nonequilibrium data, and thus establishes a well-defined way to perform PCA on nonequilibrium data. While the resulting distribution ${\cal P}(\boldsymbol{x})$ and energy $Δ{\cal G} \propto \ln {\cal P}$ will not reflect the equilibrium state of the system, the nonequilibrium energy landscape $Δ{\cal G} (\boldsymbol{x})$ may directly reveal the molecular reaction mechanism. Applied to targeted MD simulations of the unfolding of decaalanine, for example, a PCA performed on backbone dihedral angles is shown to discriminate several unfolding pathways. Although the formulation is in principle exact, its practical use depends critically on the choice of the biasing coordinate $s$, which should account for a naturally occurring motion between two well-defined end-states of the system.

q-bio.BM↗

arXiv2015

Inferring transition rates on networks with incomplete knowledge

Across many fields, a problem of interest is to predict the transition rates between nodes of a network, given limited stationary state and dynamical information. We give a solution using the principle of Maximum Caliber. We find the transition rate matrix by maximizing the path entropy of a random walker on the network constrained to reproducing a stationary distribution and a few dynamical averages. A main finding here is that when constrained only by the mean jump rate, the rate matrix is given by a square-root dependence of the rate, $ω_{ab} \propto \sqrt{p_b/p_a}$, on $p_a$ and $p_b$, the stationary state populations at nodes a and b. We give two examples of our approach. First, we show that this method correctly predicts the correlated rates in a biochemical network of two genes, where we know the exact results from prior simulation. Second, we show that it correctly predicts rates of peptide conformational transitions, when compared to molecular dynamics simulations. This method can be used to infer large numbers of rates on known networks where smaller numbers of steady-state node populations are known.

q-bio.MN↗

arXiv2008

Quantum and classical vibrational relaxation dynamics of N-methylacetamide on ab initio potential energy surfaces

Employing extensive quantum-chemical calculations at the DFT/B3LYP and MP2 level, a quartic force field of isolated N-methylacetamide is constructed. Taking into account 24 vibrational degrees of freedom, the model is employed to perform numerically exact vibrational configuration interaction calculations of the vibrational energy relaxation of the amide I mode. It is found that the energy transfer pathways may sensitively depend on details of the theoretical description. Moreover, the exact reference calculations were used to study the applicability and accuracy of (i) the quasiclassical trajectory method, (ii) time-dependent second-order perturbation theory, and (iii) the instantaneous normal mode description of frequency fluctuations. Based on the results, several strategies to describe vibrational energy relaxation in biomolecular systems are discussed.

physics.chem-ph↗

arXiv2008

Dynamic treatment of vibrational energy relaxation in a heterogeneous and fluctuating environment

A computational approach to describe the energy relaxation of a high-frequency vibrational mode in a fluctuating heterogeneous environment is outlined. Extending previous work [H. Fujisaki, Y. Zhang, and J.E. Straub, J. Chem. Phys. {\bf 124}, 144910 (2006)], second-order time-dependent perturbation theory is employed which includes the fluctuations of the parameters in the Hamiltonian within the vibrational adiabatic approximation. This means that the time-dependent vibrational frequencies along an MD trajectory are obtained via a partial geometry optimization of the solute with fixed solvent and a subsequent normal mode calculation. Adopting the amide I mode of N-methylacetamide in heavy water as a test problem, it is shown that the inclusion of dynamic fluctuations may significantly change the vibrational energy relaxation. In particular, it is found that relaxation occurs in two phases, because for short times ($\lesssim$ 200 fs) the spectral density appears continuous due to the frequency-time uncertainty relation, while at longer times the discrete nature of the bath becomes apparent. Considering the excellent agreement between theory and experiment, it is speculated if this behavior can explain the experimentally obtained biphasic relaxation the amide I mode of N-methylacetamide.

physics.chem-ph↗