4D-QSAR analysis of a series of antifungal p450 inhibitors and 3D-pharmacophore comparisons as a function of alignment

A training set of 55 antifungal p450 analogue inhibitors was used to construct receptor-independent four-dimensional quantitative structure-activity relationship (RI 4D-QSAR) models. Ten different alignments were used to build the models, and one alignment yields a significantly better model than the other alignments. Two different methodologies were used to measure the similarity of the best 4D-QSAR models of each alignment. One method compares the residual of fit between pairs of models using the cross-correlation coefficient of their residuals of fit as a similarity measure. The other method compares the spatial distributions of the IPE types (3D-pharmacophores) of pairs of 4D-QSAR models from different alignments. Optimum models from several different alignments have nearly the same correlation coefficients, r(2), and cross-validation correlation coefficients, xv-r(2), yet the 3D-pharmacophores of these models are very different from one another. The highest 3D-pharmacophore similarity correlation coefficient between any pair of 4D-QSAR models from the 10 alignments considered is only 0.216. However, the best 4D-QSAR models of each alignment do contain some proximate common pharmacorphore sites. A test set of 10 compounds was used to validate the predictivity of the best 4D-QSAR models of each alignment. The "best" model from the 10 alignments has the highest predictivity. The inferred active sites mapped out by the 4D-QSAR models suggest that hydrogen bond interactions are not prevalent when this class of P450 analogue inhibitors binds to the receptor active site. This feature of the 4D-QSAR models is in agreement with the crystal structure results that indicate no ligand-receptor hydrogen bonds are formed.     

Construction of 4D-QSAR Models for Use in the Design of Novel p38-MAPK Inhibitors

The p38-mitogen-activated protein kinase (p38-MAPK) plays a key role in lipopolysaccharide-induced tumor necrosis factor-alpha (TNF-alpha) and interleukin-1 (IL-1) release during the inflammatory process, emerging as an attractive target for new anti-inflammatory agents. Four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis [Hopfinger et al., J. Am. Chem. Soc., 119 (1997) 10509] was applied to a series of 33 (a training set of 28 and a test set of 5) pyridinyl-imidazole and pyrimidinyl-imidazole inhibitors of p38-MAPK, with IC50 ranging from 0.11 to 2100 nM [Liverton et al., J. Med. Chem., 42 (1999) 2180]. Five thousand conformations of each analogue were sampled from a molecular dynamics simulation (MDS) during 50 ps at a constant temperature of 303 K. Each conformation was placed in a 2 angstroms grid cell lattice for each of three trial alignments. 4D-QSAR models were constructed by genetic algorithm (GA) optimization and partial least squares (PLS) fitting, and evaluated by leave-one-out cross-validation technique. In the best models, with three to six terms, the adjusted cross-validated squared correlation coefficients, Q2adj, ranged from 0.67 to 0.85. Model D (Q2adj = 0.84) was identified as the most robust model from alignment 1, and it is representative of the other best models. This model encompasses new molecular regions as containing pharmacophore sites, such as the amino-benzyl moiety of pyrimidine analogs and the N1-substituent in the imidazole ring. These regions of the ligands should be further explored to identify better anti-inflammatory inhibitors of p38-MAPK.     

Receptor-independent 4D-QSAR analysis of a set of norstatine derived inhibitors of HIV-1 protease

A training set of 27 norstatine derived inhibitors of HIV-1 protease, based on the 3(S)-amino-2(S)-hydroxyl-4-phenylbutanoic acid core (AHPBA), for which the -log IC(50) values were measured, was used to construct 4D-QSAR models. Five unique RI-4D-QSAR models, from two different alignments, were identified (q(2) = 0.86-0.95). These five models were used to map the atom type morphology of the lining of the inhibitor binding site at the HIV protease receptor site as well as predict the inhibition potencies of seven test set compounds for model validation. The five models, overall, predict the -log IC(50) activity values for the test set compounds in a manner consistent with their q(2) values. The models also correctly identify the hydrophobic nature of the HIV protease receptor site, and inferences are made as to further structural modifications to improve the potency of the AHPBA inhibitors of HIV protease. The finding of five unique, and nearly statistically equivalent, RI-4D-QSAR models for the training set demonstrates that there can be more than one way to fit structure-activity data even within a given QSAR methodology. This set of unique, equally good individual models is referred to as the manifold model.     

Calculation of dye-dye and dye-AgX surface interaction energies

The computation of the interaction energy between an adsorbed dye molecule and the silver halide surface has been accomplished through the use of a new code which is based upon CHEMLAB. The surface interaction energies have been computed for 1,1′-ethylene-2,2′-cyanine, a dye molecule, in both monomeric and aggregated configurations on the (100) surfaces of AgBr and AgCl. The model predicts reasonable configurations for the adsorbed dye monomer and its H- and B-aggregates. At high dye levels, the adsorption of aggregated forms is found to be favored over an adsorbed monolayer of monomeric dye molecules. Using the current interaction potentials, however, it was found that the adsorption of the dye on the AgCl (100) surface was slightly favored over that on the AgBr (100) surface. This finding, although at variance with experimental data, may be attributed to the use of an unrelaxed silver halide surface in these computations.     

Conformational analysis in the prediction of transition phenomena

A formalism is described whereby the Helmholtz energy of a polymer crystal or melt is found by solution of a set of selfconsistent equations involving functionals of the distribution of torsional angles along a side chain. The interchain interactions are treated in a generalized meanfield framework which starts from a detailed computation of the molecular energetics of a pair of parallel and adjacent chain segments. Intrachain potentials for the cases of polymethylene and polytetrafluorethylene were obtained from molecular orbital calculations, while interchain potentials were found in addition by using semiclassical techniques. Results are presented to describe the melt transition in these materials.     

Molecular modeling of polymers, 14 quantitative structure-property relationship analyses of multicomponent systems containing polymers

One general class of polymer modeling applications involves materials which are large, in terms of molecular degrees of freedom, and poorly defined in terms of composition and morphology. Such materials are often multicomponent with respect to number of distinct polymers, fillers, additives, etc. Two obstacles limit the modeling of these materials. First, one normally does not have any idea about the key physicochemical molecular properties governing the system. Second, the functional dependence of the target properties of the material upon the key physicochemical molecular properties is usually totally unknown. Torsion angle unit (TAU) theory, a molecular decomposition technique, permits an arbitrarily large number of physicochemical properties to be computed in an open-ended fashion, and thus addresses the first problem. Genetic function approximation (GFA) analysis tackles the second problem by efficiently exploring any desired number of functional relationships between target properties and physicochemical molecular properties. Case studies of (TAU theory)-(GFA analysis) applications to estimate glass, Tg, and crystal-melt, Tm, transition temperatures will be described.