Hierarchical pattern of microfibrils in a 3D fluorapatite-gelatine nanocomposite: simulation of a bio-related structure building process.

The shape development of a biomimetic fluorapatite-gelatine nanocomposite on the mum scale is characterised by a fractal mechanism with the origin being intrinsically coded in a (central) elongated hexagonal-prismatic seed. The 3D superstructure of the seed is distinctively overlaid by a pattern consisting of gelatine microfibrils. The orientation of the microfibrils is assumed to be controlled by an intrinsic electrical field generated by the nanocomposite during development and growth of the seed. In order to confirm this assumption and to get more detailed information on orientational relations of the complex nanocomposite we simulated the pattern formation process up to the microm scale. The results from experimental studies and simulation results on an atomistic level support a model scenario wherein the elementary building blocks for the aggregation are represented by elongated hexagonal-prismatic objects (A-units), with the embedded collagen triple-helices in their centers. The interactions of the A-units are consequently modelled by three contributions: the crystal energy part (originating from the pair-wise interactions of the "apatite shells" of the prismatic units), the electrostatic interaction (originating from the unit charges located at the ends of the collagen triple helices), and the interaction energy of the A-units mediated by the solvent. The next level of complexity is related to the fact that micro fibrils were found in the fluorapatite-gelatine nanocomposites. They consist of bundles of triple helical protein molecules, which are embedded within the 3D-hexagonal prismatic arrangement of the A-units. In our approach we consider the microfibrils as chains of flexible dipoles with effective dipole moments. The crystal growth processes is modelled as an energetically controlled stepwise association of elementary building blocks of different kind on a 3D-grid. The remarkable and excellent qualitative agreement between the simulated fibril patterns and the observations made by SEM and TEM support the concept of an intrinsic electric field driven morphogenesis of the fluorapatite-gelatine nanocomposite. The simulated fibril pattern also bears the chance to make fresh attempts in order to find explanations for experimental observations which are not understood up to now.

Molecular visualization in the rational drug design process.

The visualization of molecular scenarios on an atomic level can help to interpret experimental and theoretical findings. This is demonstrated in this review article with the specific field of drug design. State-of-the-art visualization techniques are described and applied to the different stages of the rational design process. Numerous examples from the literature, in which visualization was used as a major tool in the data analysis and interpretation, are provided to show that images are not only useful for drawing the attention of the reader to a specific paper in a scientific journal.

Parameterization of an empirical model for the prediction of n-octanol, alkane and cyclohexane/water as well as brain/blood partition coefficients.

Quantitative information of solvation and transfer free energies is often needed for the understanding of many physicochemical processes, e.g the molecular recognition phenomena, the transport and diffusion processes through biological membranes and the tertiary structure of proteins. Recently, a concept for the localization and quantification of hydrophobicity has been introduced (Jäger et al. J Chem Inf Comput Sci 43:237-247, 2003). This model is based on the assumptions that the overall hydrophobicity can be obtained as a superposition of fragment contributions. To date, all predictive models for the logP have been parameterized for n-octanol/water (logP(oct)) solvent while very few models with poor predictive abilities are available for other solvents. In this work, we propose a parameterization of an empirical model for n-octanol/water, alkane/water (logP(alk)) and cyclohexane/water (logP(cyc)) systems. Comparison of both logP(alk) and logP(cyc) with the logarithms of brain/blood ratios (logBB) for a set of structurally diverse compounds revealed a high correlation showing their superiority over the logP(oct) measure in this context.

Hybrid integral equation/simulation model for enhancing free energy computations.

Integral equation theory is used for extrapolating free energy data from molecular simulations of a reference state with respect to a modification of the interaction potential. The methodology is applied to the correction of artefacts arising from potential shifting and truncation. Corrective contributions for the hydration free energy with respect to the full potential are analysed for the case that both the solute-solvent as well as the solvent-solvent potentials are truncated and modified by a shifted-force term, reaching beyond the range of the dielectric continuum approximation and simple long-range correction expressions. The model systems argon in water and pure water are used as examples for apolar and polar solutes, revealing significant correction contributions even for the short-ranged dispersive interactions and the magnitude of solute-solvent and solvent-solvent components. In comparison with simulation-based extrapolation techniques the integral equation method is shown to be capable of quantitatively predicting truncation artefacts at negligible computational overhead.

An atomistic simulation scheme for modeling crystal formation from solution.

We present an atomistic simulation scheme for investigating crystal growth from solution. Molecular-dynamics simulation studies of such processes typically suffer from considerable limitations concerning both system size and simulation times. In our method this time-length scale problem is circumvented by an iterative scheme which combines a Monte Carlo-type approach for the identification of ion adsorption sites and, after each growth step, structural optimization of the ion cluster and the solvent by means of molecular-dynamics simulation runs. An important approximation of our method is based on assuming full structural relaxation of the aggregates between each of the growth steps. This concept only holds for compounds of low solubility. To illustrate our method we studied CaF2 aggregate growth from aqueous solution, which may be taken as prototypes for compounds of very low solubility. The limitations of our simulation scheme are illustrated by the example of NaCl aggregation from aqueous solution, which corresponds to a solute/solvent combination of very high salt solubility.

Determination of the interfacial water content in protein-protein complexes from free energy simulations.

The question as to how many tightly or weakly bound water molecules are located in interfaces between protein-protein complex constituents is addressed from a phase equilibrium point of view by developing a theory in the canonical ensemble. A fast method based on free energy simulations is described for computing the number of water molecules in the interface regions. Results are given for 211 interfacial cavities of 26 antigen-antibody complexes for which experimentally determined structures are found in the Protein Data Bank. The accuracy of the method is assessed and the computational water content is compared with experimental data, revealing the amount of water molecules not resolved by experimental approaches.

Pattern recognition strategies for molecular surfaces: III. Binding site prediction with a neural network.

An algorithm for the identification of possible binding sites of biomolecules, which are represented as regions of the molecular surface, is introduced. The algorithm is based on the segmentation of the molecular surface into overlapping patches as described in the first article of this series.1 The properties of these patches (calculated on the basis of physical and chemical properties) are used for the analysis of the molecular surfaces of 7821 proteins and protein complexes. Special attention is drawn to known protein binding sites. A binding site identification algorithm is realized on the basis of the calculated data using a neural network strategy. The neural network is able to classify surface patches as protein-protein, protein-DNA, protein-ligand, or nonbinding sites. To show the capability of the algorithm, results of the surface analysis and the predictions are presented and discussed with representative examples.

Parametrization strategy for the MolFESD concept: quantitative surface representation of local hydrophobicity.

We derive a new model for the established concept of the molecular free energy surface density (MolFESD) yielding a more rigorous representation of local surface contributions to the overall hydrophobicity of a molecule. The model parametrization makes efficient use of both local and global information about solvation thermodynamics, as formulated earlier for the problem of predicting free energies of hydration. The free energy of transfer is separated into an interaction contribution and a term related to the cavity formation. Interaction and cavity components are obtained from the statistical three-dimensional (3D) free energy density and a linear combination of surface and volume terms, respectively. An appropriate molecular interaction field generated by the program Grid is used as an approximate representation of the interaction part of the 3D free energy density. We further compress the 3D density by means of a linear combination of localized surface functions allowing for the derivation of local hydrophobic contributions in the form of a free energy surface density. For a set of 400 compounds our model yields significant correlation (R(2) = 0.95, sigma = 0.57) between experimental and calculated log P values. The final model is applied to establish a correlation between partial free energies of transfer for a series of sucrose derivatives and their relative sweetness, as studied earlier in the group of the authors. We find considerable improvement regarding the rms error of the regression thus validating the presented approach.

Molecular dynamics studies on the aggregation of Y-shaped fluoroalkanes.

Molecular dynamics (MD) calculations have been performed on the aggregation of clusters with up to 128 Y-shaped perfluoroalkylated molecules of the type C10F20[C7H15]2 (Y-A/128) and C10H20[C7F15]2 (Y-B/128) as well as mixed clusters (Y-A/64+Y-B/64) using the AMBER 5 program. The effect of the segregation tendency of the chemically different parts and the influence of the steric repulsion due to the wedge shape of the molecules on the structure formation have been studied. The results have been analyzed by snapshots, radial atom pair distribution functions, orientational correlation functions as well as diffusion coefficients and are compared with the corresponding findings on clusters of alkanes and perfluoroalkanes. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s008940020092y.

Pattern recognition strategies for molecular surfaces. I. Pattern generation using fuzzy set theory.

A new method for the characterization of molecules based on the model approach of molecular surfaces is presented. We use the topographical properties of the surface as well as the electrostatic potential, the local lipophilicity/hydrophilicity, and the hydrogen bond density on the surface for characterization. The definition and the calculation method for these properties are reviewed shortly. The surface is segmented into overlapping patches with similar molecular properties. These patches can be used to represent the characteristic local features of the molecule in a way that is beyond the atomistic resolution but can nevertheless be applied for the analysis of partial similarities of different molecules as well as for the identification of molecular complementarity in a very general sense. The patch representation can be used for different applications, which will be demonstrated in subsequent articles.

Pattern recognition strategies for molecular surfaces. II. Surface complementarity.

Fuzzy logic based algorithms for the quantitative treatment of complementarity of molecular surfaces are presented. Therein, the overlapping surface patches defined in article I1 of this series are used. The identification of complementary surface patches can be considered as a first step for the solution of molecular docking problems. Standard technologies can then be used for further optimization of the resulting complex structures. The algorithms are applied to 33 biomolecular complexes. After the optimization with a downhill simplex method, for all these complexes one structure was found, which is in very good agreement with the experimental results.