Virtual screening (VS) methods have emerged as an adaptive response to the massive throughput synthesis and screening technologies. Based on the structure-permeability paradigm, the Lipinski rule of five has become a standard property filtering protocol for VS. Three possible VS scenarios with respect to optimising binding affinity and pharmacokinetic properties are discussed. The parsimony principle for selecting candidate leads for further optimisation

The active conformation is part of a conformational mixt. with exptl. activity Yexp, and is used in QSAR studies to ext. more information regarding the ligand-receptor interaction. To reflect the relative amt. (a) of the active conformation, we adjust Yexp: Yadj = Yexp - log a. We establish a quant. structure-activity relationship (QSAR) between Yadj and 3D conformational characteristics for the acetylcholinesterase (AChE) hydrolysis rates of 25

Cytochrome P 450 enzymes are monooxygenases that contain a functional heme b group linked to a conserved cysteine with a thiolate bond. In the native state, the central iron atom is hexacoordinated with a covalently bound water mol. The exclusion of solvent mols. from the active site is essential for efficient enzymic function. Upon substrate binding, water has to be displaced from the active site to prevent electron uncoupling that results in hydrogen

A review with 26 refs. The authors proposed that the properties required of library compds. intended to provide leads suitable for further optimization may be rather different. The selection of leadlike compds. for further optimization eases the pressure on subsequent and more labor-intensive parts of drug discovery process.

The process of compd. selection and prioritization is crucial for both combinatorial chem. (CBC) and high throughput screening (HTS). Compd. libraries have to be screened for unwanted chem. structures, as well as for unwanted chem. properties. Property extrema can be eliminated by using property filters, in accordance with their actual distribution. Property distribution was examd. in the following compd. databases: MACCS-II Drug Data Report (MDDR),

Poor intestinal permeability of drugs constitutes a major bottleneck in the successful development of candidate drugs. Fast computational tools to help in designing compds. with increased probability of oral absorption are required, since both medicinal and combinatorial chemists are under pressure to consider increasing nos. of virtual and existing compds. The QSAR paradigm for drug absorption is expressed as a function of mol. size, hydrogen-bonding

Structure-property relationships, central to many of today's drug discovery strategies, are not straightforward to deal with when trying to predict drug efficacy, i.e., the combined outcome of target affinity, pharmacodynamic behavior, pharmacokinetic properties, and metabolic fate. In this article, we discuss the handling of chem. property information in reagents-for-synthesis selection, enumeration, and virtual library construction. We describe

Combinatorial chem. needs focused mol. diversity applied to the drug-like chem. space (drugspace). A drugspace map can be obtained by systematically applying the same conventions when examg. the chem. space, in a manner similar to the Mercator convention in geog.: Rules are equiv. to dimensions (e.g., longitude and latitude), while structures are equiv. to objects (e.g., cities and countries). Selected rules include size, lipophilicity, polarizability,

A review with 68 refs. Cheminformatics is a tool that aims at facilitating the decision-making process across various preclin. stages of drug discovery. Access to biol. and chem. data, but not the data themselves, is an integral part of cheminformatics. Emerging tools that allow storage of, and access to, chem., structural-chem. and biol. information are only now beginning to reach maturity. Recent advances in cheminformatics include virtual library

To be considered for further development, lead structures should display the following properties: (1) simple chem. features, amenable for chem. optimization; (2) membership to an established SAR series; (3) favorable patent situation; and (4) good absorption, distribution, metab., and excretion (ADME) properties. There are two distinct categories of leads: those that lack any therapeutic use (i.e., "pure" leads), and those that are marketed drugs