Robert B. Nachbar

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Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this(More)
This article describes the parameterization and performance of MMFF94 for conformational energies, rotational barriers, and equilibrium torsion angles. It describes the derivation of the torsion parameters from high-quality computational data and characterizes MMFF94's ability to reproduce both computational and experimental data, the latter particularly in(More)
Three-dimensional molecular modeling can provide an unlimited number m of structural properties. Comparative Molecular Field Analysis (CoMFA), for example, may calculate thousands of field values for each model structure. When m is large, partial least squares (PLS) is the statistical method of choice for fitting and predicting biological responses. Yet PLS(More)
A simple hierarchical data structure (tree) and associated set of algorithms (written in Mathematica) have been developed that permit the direct manipulation of the topology of a molecule while simultaneously maintaining valid chemical valence. Coupled with a genetic algorithm optimization engine, these computational tools can be used to optimize chemical(More)
Aggregation of the small peptide amyloid beta (Aβ) into oligomers and fibrils in the brain is believed to be a precursor to Alzheimer's disease. Aβ is produced via multiple proteolytic cleavages of amyloid precursor protein (APP), mediated by the enzymes β- and γ-secretase. In this study, we examine the temporal dynamics of soluble (unaggregated) Aβ in the(More)
Trend vector analysis [Carhart, R.E. et al., J. Chem. Inf. Comput. Sci., 25 (1985) 64], in combination with topological descriptors such as atom pairs, has proved useful in drug discovery for ranking large collections of chemical compounds in order of predicted biological activity. The compounds with the highest predicted activities, upon being tested,(More)
The affinities of a diverse set of 500 drug-like molecules to cytochrome P450 isoforms 2C9 and 2D6 were measured using recombinant expressed enzyme. The dose-response curve of each compound was fitted with a series of equations representing typical or various types of atypical kinetics. Atypical kinetics was identified where the Akaike Information(More)
A novel method for computing chemical similarity from chemical substructure descriptors is described. This new method, called LaSSI, uses the singular value decomposition (SVD) of a chemical descriptor-molecule matrix to create a low-dimensional representation of the original descriptor space. Ranking molecules by similarity to a probe molecule in the(More)
A knowledge-based approach for generating conformations of molecules has been developed. The method described here provides a good sampling of the molecule's conformational space by restricting the generated conformations to those consistent with the reference database. The present approach, internally named et for enumerate torsions, differs from previous(More)