TFD: Torsion Fingerprints as a new measure to compare small molecule conformations

Advantages like intuitive interpretation, objectivity, general applicability, and its easy, automated calculation make the rmsd (root-mean-squared deviation) the measure of choice for the investigation of the accuracy of conformational model generators. For comparing conformations of a single molecule this is a clearly superior method. Single molecule analysis is, however, a rare scenario. Typically, conformations are generated for huge corporate or external vendor databases of high diversity which are then further investigated with high-throughput computational methods like docking or pharmacophore searching, in virtual screening campaigns. Representative subsets for accuracy investigations of computational methods need to mimic this diversity. Averaged rmsd values over these data sets are frequently used to assess the accuracy of the methods. There are, however, significant weaknesses in rmsd comparisons for such kind of data sets. The interpretation is for example no longer intuitive because what can be expected in terms of good or bad rmsd values crucially depends on the data set composition like size or number of rotatable bonds of the underlying molecules. Further, rmsd lacks normalization which might result in very high averaged rmsd values for highly flexible molecules and thus might completely skew results. We have developed a novel measure to compare conformations of molecules called Torsion Fingerprint Deviation (TFD). It extracts, weights, and compares Torsion Fingerprints from a query molecule and generated conformations under consideration of acyclic bonds as well as ring systems. TFD is alignment-free and overcomes major limitations of rmsd while retaining its advantages.     

Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function

The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes. The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. In this study, we validated our new scoring function by applying it in large-scale docking experiments. We could successfully predict the correct binding mode in 93% of complexes in redocking calculations on the Astex diverse set, while our performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls, which we highlight here and which should be addressed in future benchmark datasets.     

Vapor-liquid equilibria for the system water + tert.-pentanol at 4 temperatures

Precise isothermal vapor-liquid equilibrium data at 10, 30, 55 and 70°C for the system water + tert.-pentanol were measured using a computer-operated differential static apparatus. Activity coefficients at infinite dilution were derived from the experimental P − x data in the dilute region using a flexible Legendre polynomial, and the vapor-liquid-liquid locus was derived directly from the P − x data near the liquid-liquid phase boundary. Heteroazeotropic points were measured directly by distillation using a rotating band column. Furthermore the UNIQUAC and the NRTL models were used to correlate the experimental P − x data and to derive the azeotropic data.

Experimental H^E data were taken from literature and used together with the experimental P − x data to simultaneously fit temperature dependent interaction parameters for UNIQUAC and NRTL. The parameters were used to predict the azeotropic composition over a large temperature range. The results were compared with those of a simple analytical thermodynamic equation using only the pure component vapor pressure data, heats of mixing in the heterogeneous region and the azeotropic composition at one temperature.

Heats of mixing were measured at 140°C with the help of a flow calorimeter in order to determine the slope of H^E vs. x₁ in the heterogeneous region. The H^E data were used to check the reliability of the G^E model parameters and the equation to calculate the temperature dependence of the heteroazeotropic composition.     

Fully automated flexible docking of ligands into flexible synthetic receptors using forward and inverse docking strategies

The prediction of the structure of host-guest complexes is one of the most challenging problems in supramolecular chemistry. Usual procedures for docking of ligands into receptors do not take full conformational freedom of the host molecule into account. We describe and apply a new docking approach which performs a conformational sampling of the host and then sequentially docks the ligand into all receptor conformers using the incremental construction technique of the FlexX software platform. The applicability of this approach is validated on a set of host-guest complexes with known crystal structure. Moreover, we demonstrate that due to the interchangeability of the roles of host and guest, the docking process can be inverted. In this inverse docking mode, the receptor molecule is docked around its ligand. For all investigated test cases, the predicted structures are in good agreement with the experiment for both normal (forward) and inverse docking. Since the ligand is often smaller than the receptor and, thus, its conformational space is more restricted, the inverse docking approach leads in most cases to considerable speed-up. By having the choice between two alternative docking directions, the application range of the method is significantly extended. Finally, an important result of this study is the suitability of the simple energy function used here for structure prediction of complexes in organic media.