Measurements of time-resolved Stokes shifts on picosecond to nanosecond time scales have been used to probe the polar solvation dynamics of biological systems. Since it is difficult to decompose the measurements into protein and solvent contributions, computer simulations are useful to aid in understanding the details of the molecular behavior. Here we report the analysis of simulations of the electrostatic interactions of the rest of the protein and the solvent with 11 residues of the immunoglobulin binding domain B1 of protein G. It is shown that the polar solvation dynamics are position-dependent and highly heterogeneous. The contributions due to interactions with the protein and with the solvent are determined. The solvent contributions are found to vary from negligible after a few picoseconds to dominant on a scale of hundreds of picoseconds. The origin for the latter is found to involve coupled hydration and protein conformational dynamics. The resulting microscopic picture demonstrates that a wide range of possibilities have to be considered in the interpretation of time-resolved Stokes shift measurements.

Summary High-fidelity DNA polymerases copy DNA rapidly and accurately by adding correct deoxynucleotide triphosphates to a growing primer strand of DNA. Following nucleotide incorporation, a series of conformational changes translocate the DNA substrate by one base pair step, readying the polymerase for the next round of incorporation. Molecular dynamics simulations indicate that the translocation consists globally of a polymerase fingers-opening transition, followed by the DNA displacement and the insertion of the template base into the preinsertion site. They also show that the pyrophosphate release facilitates the opening transition and that the universally conserved Y714 plays a key role in coupling polymerase opening to DNA translocation. The transition involves several metastable intermediates in one of which the O-helix is bent in the vicinity of G711. Completion of the translocation appears to require a gating motion of the O1-helix, perhaps facilitated by the presence of G715. These roles are consistent with the high level of conservation of Y714 and the two glycine residues at these positions. It is likely that a corresponding mechanism is applicable to other polymerases.

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT.

A systematic approach to improve the short time dynamics for classical mapping treatments of nonadiabatic dynamics is developed. This approach is based on the Taylor expansion of time-dependent observables around t=0. By sampling initial conditions in a manner that renders accurate static moments of the electronic population, it is shown that the short time electronic population dynamics described by classical mapping approaches for nonadiabatic dynamics can be greatly improved. The approach is illustrated on the example of the spin-boson model. For this problem, the analysis of the expansion coefficients reveals why classical mapping approaches to nonadiabatic dynamics often perform much worse for energetically biased reactions than they do for reactions with zero bias. The analysis presented here not only allows for the improvement of short time (and often long time) behavior, but also points to a systematic way of accessing how accurate a given classical mapping approach should be for a given problem.