Christoph Junghans

Versatile Object-Oriented Toolkit for Coarse-Graining Applications

Coarse-graining is a systematic way of reducing the number of degrees of freedom representing a system of interest. Several coarse-graining techniques have so far been developed, such as iterative Boltzmann inversion, force-matching, and inverse Monte Carlo. However, there is no unified framework that implements these methods and that allows their direct comparison. We present a versatile object-oriented toolkit for coarse-graining applications (VOTCA) that implements these techniques and that provides a flexible modular platform for the further development of coarse-graining techniques. All methods are illustrated and compared by coarse-graining the SPC/E water model, liquid methanol, liquid propane, and a single molecule of hexane.

Comparative atomistic and coarse-grained study of water: what do we lose by coarse-graining?

We employ the inverse Boltzmann method to coarse-grain three commonly used three-site water models (TIP3P, SPC and SPC/E) where one molecule is replaced with one coarse-grained particle with isotropic two-body interactions only. The shape of the coarse-grained potentials is dominated by the ratio of two lengths, which can be rationalized by the geometric constraints of the water clusters. It is shown that for simple two-body potentials either the radial distribution function or the geometrical packing can be optimized. In a similar way, as needed for multiscale methods, either the pressure or the compressibility can be fitted to the all atom liquid. In total, a speed-up by a factor of about 50 in computational time can be reached by this coarse-graining procedure.

Adaptive resolution molecular dynamics simulation through coupling to an internal particle reservoir.

For simulation studies of (macro) molecular liquids it would be of significant interest to be able to adjust or increase the level of resolution within one region of space, while allowing for the free exchange of molecules between open regions of different resolution or representation. We generalize the adaptive resolution idea and suggest an interpretation in terms of an effective generalized grand canonical approach. The method is applied to liquid water at ambient conditions.

Microcanonical analyses of peptide aggregation processes.

We propose the use of microcanonical analyses for numerical studies of peptide aggregation transitions. Performing multicanonical Monte Carlo simulations of a simple hydrophobic-polar continuum model for interacting heteropolymers of finite length, we find that the microcanonical entropy behaves convex in the transition region, leading to a negative microcanonical specific heat. As this effect is also seen in first-order-like transitions of other finite systems, our results provide clear evidence for recent hints that the characterization of phase separation in first-order-like transitions of finite systems profits from this microcanonical view.

Structure Formation of Toluene around C60: Implementation of the Adaptive Resolution Scheme (AdResS) into GROMACS

For the example of C60 solutes in toluene, we present the implementation of the adaptive resolutions scheme (AdResS) for molecular simulations into GROMACS. In AdResS a local, typically all-atom cavity is coupled to a surrounding of coarse-grained, simplified molecules. This methodology can not only be used to reduce the CPU time demand of atomistic simulations but also to systematically investigate the relative influence of different interactions on structure formation. For this, we vary the thickness of the all atom layer of toluene around the C60 and analyze the first toluene layers in comparison to a full bulk simulation.

Communication: On the locality of Hydrogen bond networks at hydrophobic interfaces

The formation of structured hydrogen bond networks in the solvation shells immediate to hydrophobic solutes is crucial for a large number of water mediated processes. A long lasting debate in this context regards the mutual influence of the hydrophobic solute into the bulk water and the role of the hydrogen bond network of the bulk in supporting the solvation structure around a hydrophobic molecule. In this context we present a molecular dynamics study of the solvation of various hydrophobic molecules where the effect of different regions around the solvent can be analyzed by employing an adaptive resolution method, which can systematically separate local and nonlocal factors in the structure of water around a hydrophobic molecule. A number of hydrophobic solutes of different sizes and two different model potential interactions between the water and the solute are investigated.

Kirkwood–Buff Coarse-Grained Force Fields for Aqueous Solutions

We present an approach to systematically coarse-grain liquid mixtures using the fluctuation solution theory of Kirkwood and Buff in conjunction with the iterative Boltzmann inversion method. The approach preserves both the liquid structure at pair level and the dependence of solvation free energies on solvent composition within a unified coarse-graining framework. To test the robustness of our approach, we simulated urea-water and benzene-water systems at different concentrations. For urea-water, three different coarse-grained potentials were developed at different urea concentrations, in order to extend the simulations of urea-water mixtures up to 8 molar urea concentration. In spite of their inherent state point dependence, we find that the single-site models for urea and water are transferable in concentration windows of approximately 2 M. We discuss the development and application of these solvent models in coarse-grained biomolecular simulations.

Thermodynamics of peptide aggregation processes: An analysis from perspectives of three statistical ensembles

We employ a mesoscopic model for studying aggregation processes of proteinlike hydrophobic-polar heteropolymers. By means of multicanonical Monte Carlo computer simulations, we find strong indications that peptide aggregation is a phase separation process, in which the microcanonical entropy exhibits a convex intruder due to non-negligible surface effects of the small systems. We analyze thermodynamic properties of the conformational transitions accompanying the aggregation process from the multicanonical, canonical, and microcanonical perspective. It turns out that the microcanonical description is particularly advantageous as it allows for unraveling details of the phase-separation transition in the thermodynamic region, where the temperature is not a suitable external control parameter anymore.

Statistical mechanics of aggregation and crystallization for semiflexible polymers

By means of multicanonical computer simulations, we investigate thermodynamic properties of the aggregation of interacting semiflexible polymers. We analyze a mesoscopic bead-stick model, where nonbonded monomers interact via Lennard-Jones forces. Aggregation turns out to be a process, in which the constituents experience strong structural fluctuations, similar to peptides in coupled folding-binding cluster formation processes. In contrast to a recently studied related proteinlike hydrophobic-polar heteropolymer model, aggregation and crystallization are separate processes for a homopolymer with the same small bending rigidity. Rather stiff semiflexible polymers form a liquid-crystal–like phase, as expected. In analogy to the heteropolymer study, we find that the first-order–like aggregation transition of the complexes is accompanied by strong system-size–dependent hierarchical surface effects. In consequence, the polymer aggregation is a phase-separation process with entropy reduction.

Molecular Dynamics in the Multicanonical Ensemble: Equivalence of Wang-Landau Sampling, Statistical Temperature Molecular Dynamics, and Metadynamics.

We show a direct formal relationship between the Wang-Landau iteration [PRL 86, 2050 (2001)], metadynamics [PNAS 99, 12562 (2002)], and statistical temperature molecular dynamics (STMD) [PRL 97, 050601 (2006)] that are the major work-horses for sampling from generalized ensembles. We demonstrate that STMD, itself derived from the Wang-Landau method, can be made indistinguishable from metadynamics. We also show that Gaussian kernels significantly improve the performance of STMD, highlighting the practical benefits of this improved formal understanding.