Morpheus: a conformation-activity relationships and receptor modeling package

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued efforts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature.

OVID and SUPER: two overlap programs for drug design

Two programs, OVID and SUPER, for exploring the similarity of molecules with respect to their action at a receptor are described. OVID accepts two molecules as input and optimizes the three-dimensional overlap of specified atoms in one molecule with specified atoms in the second molecule. The result is expressed as a percent of the theoretical maximum. OVID gives a quantitative measure of the extent of a guessed correspondence between two molecules based on volume overlap of selected atoms. The Achilles' heel of OVID is that the correspondence between the two molecules has to be guessed. We realized that it would be better to systematically examine all possible correspondences of two structures to minimize the chance of overlooking a superior correspondence. We created SUPER to satisfy this need. SUPER accepts two molecules as input and finds the top twenty correspondences of their surfaces and charge distributions, giving a quantitative measure of the extent of each correspondence. An instructive example of the application of OVID and SUPER to the design of leukotriene D4 receptor antagonists is described. SUPER appears to be a practical brain-storming tool for the medicinal chemist trying to understand how molecules whose structures may not resemble one another in an obvious way can bind to the same site.

A one-variable topographical descriptor for the beta-turns of peptides and proteins

The beta-turn is a common secondary structure in biologically active peptides and globular proteins, where it is widely thought to serve as a molecular recognition site for many biological processes. Although the primary beta-turn recognition requirements are thought to be straightforward, relating mainly to the relative positions of the peptide sidechains, current classifications of beta-turns are complex and are based solely upon the very variable geometry of the peptide backbone. We demonstrate here that beta-turns can be described in terms of a single dihedral angle, which we have called beta, which provides a complete description of the spatial relationship between the entry and exit peptide bonds as well as the relative orientations of the intervening sidechains for any beta-turn. This description should prove particularly useful in the development and application of novel peptide mimetic drugs, compounds for which a classification based on a peptide backbone geometry may be entirely irrelevant.