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Charles H Reynolds

Publications and source records attributed to Charles H Reynolds.

11 recordsLinked to original sources
PubMed2005

Linear interaction energy models for beta-secretase (BACE) inhibitors: Role of van der Waals, electrostatic, and continuum-solvation terms.

Computing the binding affinity of a protein-ligand complex is one of the most fundamental and difficult tasks in computer-aided drug design. Many approaches for computing binding affinities can be classified as linear interaction energy (LIE) models as they rely on some type of linear fit of computed interaction energies between ligand and protein. We have examined the computed interaction energies of a series of beta-secretase (BACE) inhibitors in terms of van der Waals, coulombic, and continuum-solvation contributions to ligand binding. We have also systematically examined the effect of different protonation states of the protein and ligands. We find that the binding affinities are relatively insensitive to the protonation state of the protein when neutral ligands are considered. Inclusion of charged ligands leads to large deviations in the coulomb, solvation, and even van der Waals terms. The latter is due to increased repulsive van der Waals interactions in the complex due to the strong coulomb attraction found between oppositely charged functional groups in the protein and ligand. In general, we find that the best models are obtained when the protein is judiciously charged (e.g. Asp32-, Arg235+) and the potentially charged ligands are treated as neutral.

Amyloid Precursor Protein Secretases↗
PubMed2005

A two-state homology model of the hERG K+ channel: application to ligand binding.

Homology models based on available K+ channel structures have been used to construct a multiple state representation of the hERG cardiac K+ channel. These states are used to capture the flexibility of the channel. We show that this flexibility is essential in order to correctly model the binding affinity of a set of diverse ligands. Using this multiple state approach, a binding affinity model was constructed for set of known hERG channel binders. The predicted pIC50s are in good agreement with experiment (RMSD: 0.56 kcal/mol). In addition, these calculations provide structures for the bound ligands that are consistent with published mutation studies. These computed ligand bound complex structures can be used to guide synthesis of analogs with reduced hERG liability.

ERG1 Potassium Channel↗
PubMed2004

Modeling the protonation states of the catalytic aspartates in beta-secretase.

Beta-secretase (BACE) is a critical enzyme in the production of beta-amyloid, a protein that has been implicated as a potential cause of Alzheimer's disease (AD). There are two aspartic acid residues (Asp 32 and Asp 228) present in the catalytic region of BACE that can adopt multiple protonation states. The protonation state and precise location of the protons for these two residues, particularly in the presence of an inhibitor, are subjects of great interest since they have a direct bearing on the mechanism of aspartyl proteases and efforts to model beta-secretase. We have carried out full liner-scaling quantum mechanical (QM) calculations that include Poisson-Boltzmann solvation in order to identify the preferred protonation state and proton location in the presence and absence of an inhibitor. These calculations favor the monoprotonated state in the presence of ligand, and di-deprotonated state in the absence of ligand. Further the proton in the monoprotonated state is located on the inner oxygen of Asp 228. These results have implications for the catalytic mechanism of BACE and related aspartyl proteases. They also provide a reference state for the protein in structure-based modeling studies of this therapeutically important target.

Amyloid Precursor Protein Secretases↗
PubMed2004

Modeling the binding affinities of beta-secretase inhibitors: application to subsite specificity.

A new linear binding affinity model has been developed for hydroxyethylene based inhibitors of beta-secretase (BACE). This model is an improvement over a previously published model, and has been applied to a series of analogs not included in the training set. The linear model has been used to study subsite specificity for the P(2) through P(2)' positions, and to evaluate a small number of C-terminal analogs. The predicted rankings are in good agreement with experiment and support using this model for structure-based design of BACE inhibitors.

Amyloid Precursor Protein Secretases↗
PubMed2004

Potent nonpeptide vasopressin receptor antagonists based on oxazino- and thiazinobenzodiazepine templates.

Vasopressin receptor antagonists can elicit ion-sparing diuretic effects (i.e., aquaresis) in vivo by blunting the action of the circulating hypophyseal hormone arginine vasopressin. We have identified two new series of basic tricyclic benzodiazepines, represented by general structure 1, which contain compounds that bind with high affinity to human V2 receptors. For example, (S)-(+)-8 and 5 are potent and selective V2 receptor antagonists with pronounced aquaretic activity in rats on oral administration.

Administration, Oral↗
PubMed2004

A Web-based chemoinformatics system for drug discovery.

One of the key questions that must be addressed when implementing a chemoinformatics system is whether the tools will be designed for use by the expert user or by the "bench scientist." This decision can impact not only the style of tools that are rolled out, but is also a factor in terms of how these tools are delivered to the end users. The system that we outline here was designed for use by the non-expert user. As such, the tools that we discuss are in many cases simplified versions of some common algorithms used in chemoinformatics. In addition, the focus is on how to distribute these tools using a web-services interface, which greatly simplifies delivering new protocols to the end user.

Combinatorial Chemistry Techniques↗
PubMed2003

Calculation of the binding affinity of beta-secretase inhibitors using the linear interaction energy method.

It has been shown that the rate-limiting step in the production of beta-amyloid peptide (Abeta) is the proteolytric cleavage of the membrane-bound beta-amyloid precursor protein (APP) by beta-secretase (BACE). Since the accumulation of Abeta has been implicated as one of the key events in the progression of Alzheimer's disease, BACE has become an important therapeutic target. Recently, two crystal structures of BACE cocrystallized with the inhibitors OM99-2 and OM00-3 were published by Tang and co-workers. In addition, the Ghosh group has published binding data on a series of inhibitors based on their initial lead, OM99-2. Using this set as a basis, we have developed a model for the binding affinity of these ligands to BACE using the linear interaction energy method. The best binding affinity model for the full set of ligands had a RMSD of 1.10 kcal/mol. The best model excluding the two charged ligands had a RMSD of 0.87 kcal/mol.

Amyloid Precursor Protein Secretases↗
PubMedDate not supplied

Chemical information based scaling of molecular descriptors: a universal chemical scale for library design and analysis.

Scaling is a difficult issue for any analysis of chemical properties or molecular topology when disparate descriptors are involved. To compare properties across different data sets, a common scale must be defined. Using several publicly available databases (ACD, CMC, MDDR, and NCI) as a basis, we propose to define chemically meaningful scales for a number of molecular properties and topology descriptors. These chemically derived scaling functions have several advantages. First, it is possible to define chemically relevant scales, greatly simplifying similarity and diversity analyses across data sets. Second, this approach provides a convenient method for setting descriptor boundaries that define chemically reasonable topology spaces. For example, descriptors can be scaled so that compounds with little potential for biological activity, bioavailability, or other drug-like characteristics are easily identified as outliers. We have compiled scaling values for 314 molecular descriptors. In addition the 10th and 90th percentile values for each descriptor have been calculated for use in outlier filtering.

Combinatorial Chemistry Techniques↗
PubMedDate not supplied

Performance of similarity measures in 2D fragment-based similarity searching: comparison of structural descriptors and similarity coefficients.

2D fragment-based similarity searching is one of the most popular techniques for searching a large database of chemical structures and has been widely applied in drug discovery. However, its performance, especially its effectiveness in retrieving active structural analogues, has not been adequately studied. We report a series of computational experiments, where we systematically studied the influence of structural descriptors and similarity coefficients on the effectiveness of similarity searching. The study was conducted using two public large data sets, NCI anti-AIDS and MDDR. Four sets of 2D linear fragment descriptors, based on the original definitions of atom pairs and atom sequences, were compared. The effect of using the Tanimoto coefficient and the Euclidean distance was studied as a function of descriptor set. The results clearly indicate that the Tanimoto coefficient is superior to the Euclidean distance in 2D-fragment based similarity searching, in terms of hit rate, while atom sequences demonstrate the best overall performance among the structural descriptors we studied.

Anti-HIV Agents↗
PubMedDate not supplied

Defining privileged reagents using subsimilarity comparison.

We have developed a new method for assigning a drug-like score to reagents. This algorithm uses topological torsion (TT) 2D descriptors to compute the subsimilarity of any given reagent to a substructural element of any compound in the CMC. The utility of this approach is demonstrated by scoring a test set of reagents derived from the "Comprehensive Survey of Combinatorial Library Synthesis: 2000" (J. Comb. Chem.). R-groups were extracted from the most-active compounds found in each of the reviewed libraries, and the distribution of the subsimilarity scores for these monomers were compared to the ACD. This comparison showed a dramatic shift in the distribution of the JCC R-group subset toward higher subsimilarity scores in comparison to the entire ACD database. The ACD was also used to examine the relationship between molecular weight and various subsimilarity scoring algorithms. This analysis was used to derive a subsimilarity score that is less biased by molecular weight.

Journal Article↗