Joanne M. Carr

Global optimization and folding pathways of selected α-helical proteins

The results of basin-hopping global optimization simulations are presented for four small, α-helical proteins described by a coarse-grained potential. A step-taking scheme that incorporates the local conformational preferences extracted from a large number of high-resolution protein structures is compared with an unbiased scheme. In addition, the discrete path sampling method is used to investigate the folding of one of the proteins, namely, the villin headpiece subdomain. Folding times from kinetic Monte Carlo simulations and iterative calculations based on a Markovian first-step analysis for the resulting stationary-point database are in good mutual agreement, but differ significantly from the experimental values, probably because the native state is not the global free energy minimum for the potential employed.

Folding Pathways and Rates for the Three-Stranded β-Sheet Peptide Beta3s using Discrete Path Sampling

The discrete path sampling method was used to investigate the folding of a three-stranded antiparallel beta-sheet peptide, Beta3s, described by an empirical potential and implicit solvent model. After application of a coarse-graining scheme that groups together sets of minima in local equilibrium, the calculated folding time was in reasonable agreement with other simulations and consistent with the experimental upper bound. The folding mechanism exhibited by the most significant discrete paths involves early formation of the C-terminal hairpin followed by docking of the N-terminal strand.

Quasi-Continuous Interpolation Scheme for Pathways between Distant Configurations

A quasi-continuous interpolation (QCI) scheme is introduced for characterizing physically realistic initial pathways from which to initiate transition state searches and construct kinetic transition networks. Applications are presented for peptides, proteins, and a morphological transformation in an atomic cluster. The first step in each case involves end point alignment, and we describe the use of a shortest augmenting path algorithm for optimizing permutational isomers. The QCI procedure then employs an interpolating potential, which preserves the covalent bonding framework for the biomolecules and includes repulsive terms between unconstrained atoms. This potential is used to identify an interpolating path by minimizing contributions from a connected set of images, including terms corresponding to minima in the interatomic distances between them. This procedure detects unphysical geometries in the line segments between images. The most difficult cases, where linear interpolation would involve chain crossings, are treated by growing the structure an atom at a time using the interpolating potential. To test the QCI procedure, we carry through a series of benchmark calculations where the initial interpolation is coupled to explicit transition state searches to produce complete pathways between specified local minima.

Energy landscapes and persistent minima.

We consider a coarse-graining of high-dimensional potential energy landscapes based upon persistences, which correspond to lowest barrier heights to lower-energy minima. Persistences can be calculated efficiently for local minima in kinetic transition networks that are based on stationary points of the prevailing energy landscape. The networks studied here represent peptides, proteins, nucleic acids, an atomic cluster, and a glassy system. Minima with high persistence values are likely to represent some form of alternative structural morphology, which, if appreciably populated at the prevailing temperature, could compete with the global minimum (defined as infinitely persistent). Threshold values on persistences (and in some cases equilibrium occupation probabilities) have therefore been used in this work to select subsets of minima, which were then analysed to see how well they can represent features of the full network. Simplified disconnectivity graphs showing only the selected minima can convey the funnelling (including any multiple-funnel) characteristics of the corresponding full graphs. The effect of the choice of persistence threshold on the reduced disconnectivity graphs was considered for a system with a hierarchical, glassy landscape. Sets of persistent minima were also found to be useful in comparing networks for the same system sampled under different conditions, using minimum oriented spanning forests.

Proton transfer pathways, energy landscape, and kinetics in creatine-water systems.

We study the exchange processes of the metabolite creatine, which is present in both tumorous and normal tissues and has NH2 and NH groups that can transfer protons to water. Creatine produces chemical exchange saturation transfer (CEST) contrast in magnetic resonance imaging (MRI). The proton transfer pathway from zwitterionic creatine to water is examined using a kinetic transition network constructed from the discrete path sampling approach and an approximate quantum-chemical energy function, employing the self-consistent-charge density-functional tight-binding (SCC-DFTB) method. The resulting potential energy surface is visualized by constructing disconnectivity graphs. The energy landscape consists of two distinct regions corresponding to the zwitterionic creatine structures and deprotonated creatine. The activation energy that characterizes the proton transfer from the creatine NH2 group to water was determined from an Arrhenius fit of rate constants as a function of temperature, obtained from harmonic transition state theory. The result is in reasonable agreement with values obtained in water exchange spectroscopy (WEX) experiments.

Overcoming Energetic and Time Scale Barriers Using the Potential Energy Surface

Sampling stationary points of the potential energy surface provides an intuitive way to coarse-grain calculations of both thermodynamic and dynamic properties. Functions such as internal energy, entropy, free energy and the heat capacity can be obtained from the superposition approximation, where the total partition function is written as a sum of contributions from a database of local minima. Rates can be calculated if the database is augmented to include transition states that connect the minima, and the discrete path sampling method provides a systematic approach to this problem. Transforming the potential energy surface into the basins of attraction of local minima also provides a powerful global optimisation algorithm via the basin-hopping approach.