Structure-assisted discovery of an aminothiazole derivative as a lead molecule for inhibition of bacterial fatty-acid synthesis

β-Ketoacyl-ACP synthase is a key target for the treatment of infectious diseases. A structure-based biophysical screening approach identified for the first time a synthetic small molecule, 2-phenylamino-4-methyl-5-acetylthiazole, that binds to the active site of the enzyme. Implications for the use of this information in drug discovery are discussed

Challenges and Rewards in Medicinal Chemistry Targeting Cardiovascular and Metabolic Diseases

Medicinal chemistry has been transformed by major technological and conceptual innovations over the last three decades: structural biology and bioinformatics, structure and property based molecular design, the concepts of multidimensional optimization (MDO), in silico and experimental high-throughput molecular property analysis. The novel technologies advanced gradually and in synergy with biology and Roche has been at the forefront. Applications in drug discovery programs towards new medicines in cardiovascular and metabolic diseases are highlighted to show impact and advancement: the early discovery of endothelin antagonists for endothelial dysfunction (Bosentan), 11-beta hydroxysteroid dehydrogenase (11?-HSD1) inhibitors for dysregulated cellular glucocorticoid tonus (type 2 diabetes and metabolic syndrome) and non-covalent hormone sensitive lipase (HSL) inhibitors to study the scope of direct inhibition of lipolysis in the conceptual frame of lipotoxicity and type 2 diabetes

Ensemble Methods for Classification in Cheminformatics

We describe the application of ensemble methods to binary classification problems on two pharmaceutical compound data sets. Several variants of single and ensembles models of k-nearest neighbors classifiers, support vector machines (SVMs), and single ridge regression models are compared. All methods exhibit robust classification even when more features are given than observations. On two data sets dealing with specific properties of drug-like substances (cytochrome P450 inhibition and “Frequent Hitters”, i.e., unspecific protein inhibition), we achieve classification rates above 90%. We are able to reduce the cross-validated misclassification rate for the Frequent Hitters problem by a factor of 2 compared to previous results obtained for the same data set with different modeling techniques. 1

Torsion Angle Preferences in Druglike Chemical Space: A Comprehensive Guide

Crystal structure databases offer ample opportunities to derive small molecule conformation preferences, but the derived knowledge is not systematically applied in drug discovery research. We address this gap by a comprehensive and extendable expert system enabling quick assessment of the probability of a given conformation to occur. It is based on a hierarchical system of torsion patterns that cover a large part of druglike chemical space. Each torsion pattern has associated frequency histograms generated from CSD and PDB data and, derived from the histograms, traffic-light rules for frequently observed, rare, and highly unlikely torsion ranges. Structures imported into the corresponding software are annotated according to these rules. We present the concept behind the tree of torsion patterns, the design of an intuitive user interface for the management and usage of the torsion library, and we illustrate how the system helps analyze and understand conformation properties of substructures widely used in medicinal chemistry

Torsion Angle Preferences in Druglike Chemical Space: A Comprehensive Guide

Crystal structure databases offer ample opportunities to derive small molecule conformation preferences, but the derived knowledge is not systematically applied in drug discovery research. We address this gap by a comprehensive and extendable expert system enabling quick assessment of the probability of a given conformation to occur. It is based on a hierarchical system of torsion patterns that cover a large part of druglike chemical space. Each torsion pattern has associated frequency histograms generated from CSD and PDB data and, derived from the histograms, traffic-light rules for frequently observed, rare, and highly unlikely torsion ranges. Structures imported into the corresponding software are annotated according to these rules. We present the concept behind the tree of torsion patterns, the design of an intuitive user interface for the management and usage of the torsion library, and we illustrate how the system helps analyze and understand conformation properties of substructures widely used in medicinal chemistry

Oxidosqualene Cyclase (OSC) Inhibitors for the Treatment of Dyslipidemia

Novel inhibitors of oxidosqualene cyclase (OSC) for the treatment of dyslipidemia are reported. Starting point for the chemistry program was a set of compounds derived from a fungicide project which, in addition to high affinity for OSC from Candida albicans, also showed high affinity for the human enzyme (hOSC). Here the evaluation process of different scaffolds is outlined for two representative series, the phenyl substituted benzo[d]isothiazoles and the aminocyclohexanes. The most promising compounds derived from the latter series were further profiled in vivo and showed promising properties with respect to modulation of lipid parameters

3‑Amido-3-aryl-piperidines: A Novel Class of Potent, Selective, and Orally Active GlyT1 Inhibitors

3-Amido-3-aryl-piperidines were discovered as a novel structural class of GlyT1 inhibitors. The structure–activity relationship, which was developed, led to the identification of highly potent compounds exhibiting excellent selectivity against the GlyT2 isoform, drug-like properties, and in vivo activity after oral administration