A chemically advanced template search (CATS) based on topological pharmacophore models has been developed as a technique for virtual screening. This technique has successfully identified novel potent Ca(2+) antagonists (such as 2) that have a similar activity to 1 (a known T-channel blocking agent) in a library of several hundred thousand compounds on the basis of a correlation vector representation.

A computer-based method was developed for rapid and automatic identification of potential "frequent hitters". These compounds show up as hits in many different biological assays covering a wide range of targets. A scoring scheme was elaborated from substructure analysis, multivariate linear and nonlinear statistical methods applied to several sets of one and two-dimensional molecular descriptors. The final model is based on a three-layered neural network, yielding a predictive Matthews correlation coefficient of 0.81. This system was able to correctly classify 90% of the test set molecules in a 10-times cross-validation study. The method was applied to database filtering, yielding between 8% (compilation of trade drugs) and 35% (Available Chemicals Directory) potential frequent hitters. This filter will be a valuable tool for the prioritization of compounds from large databases, for compound purchase and biological testing, and for building new virtual libraries.

Since its discovery, endothelin-1 has attracted considerable scientific interest because of its extremely potent and long-lasting vasoconstrictor effect and its binding to G-protein-coupled receptors. Plasma concentrations of endothelin-1 are low and its release by endothelial cells is polarized towards the basolateral side, suggesting that it is a paracrine factor and not a hormone. Consequently, the effect of injected endothelin-1 may not reflect the effect of endogenous endothelin-1. In contrast, blockade of the action of endogenous endothelin-1 using receptor antagonists should be a valuable means of investigating its physiological and pathological effects. We report here evidence for the pathophysiological role of endothelin-1 as brought by the first synthetic orally active nonpeptide antagonist of endothelin receptors, Ro 46-2005.

We present a series of small molecule drug discovery case studies where computational methods were prospectively employed to impact Roche research projects, with the aim of highlighting those methods that provide real added value. Our brief accounts encompass a broad range of methods and techniques applied to a variety of enzymes and receptors. Most of these are based on judicious application of knowledge about molecular conformations and interactions: filling of lipophilic pockets to gain affinity or selectivity, addition of polar substituents, scaffold hopping, transfer of SAR, conformation analysis, and molecular overlays. A case study of sequence-driven focused screening is presented to illustrate how appropriate preprocessing of information enables effective exploitation of prior knowledge. We conclude that qualitative statements enabling chemists to focus on promising regions of chemical space are often more impactful than quantitative prediction.

A chemically advanced template search (CATS) based on topological pharmacophore models has been developed as a technique for virtual screening. This technique has successfully identified novel potent Ca(2+) antagonists (such as 2) that have a similar activity to 1 (a known T-channel blocking agent) in a library of several hundred thousand compounds on the basis of a correlation vector representation.