Bioactive pharmacophore

Parallel synthesis and screening of bioactive pharmacophore libraries... 

Tel. 415-903-3900, fax 415-961-0584, e-mail support biocad.com Molecule building with stick, ball-and-stick, and space-filling graphics. Systematic conformational searching and statistical fitting of 3D structural features to bioactivities. Pharmacophoric hypotheses can be used to search for matches in databases of 3D structures created by user. Silicon Graphics and networked Macintosh and PC. 

It is well known that the identification of the pharmacophoric moiety (i.e. the essential atoms and molecular fragments of the bioactive compound, which selectively recognize the receptor eliciting the observed specific pharmacological effect) constitutes an important aspect of drug design procedures and SAR studies [84—86]. 

The requirement for diverse compound libraries by means of solid-phase synthesis led to the development of hnkers for most functional groups found in organic synthesis. The number of hnkers developed for a specific group also reflects the distribution of pharmacophoric groups present in natural products and other bioactive compounds. Tab. 3.16 gives an overview of examples of hnkers for different functional groups. 

The standard screening approach when several active molecules have been identified is pharmacophore mapping followed by 3D database searching. This approach assumes that the active molecules have a common mode of action and that features that are common to all of the molecules describe the pharmacophoric pattern responsible for the observed bioactivity. This is a powerful technique but one that may not be applicable to the structurally heterogeneous hits that characterize typical HTS experiments or sets of competitor compounds drawn from the public literature. In such cases, it is appropriate to consider approaches based on 2D similarity searching and we present here a comparison of approaches for combining the structural information that can be gleaned from a small set of reference structures. 

A diversity of biological effects are possessed by benzofused six-membered heterocycles. These range from antimicrobial activity to cardiovascular, CNS, and inflammation-influencing agents. It can be inferred that the ring system itself is primarily a molecular scaffold upon which to assemble the characteristic pharmacophore for the various receptors involved. It is interesting also to note that the range of bioactivities involved differ substantially from those seen with the benzofused five-membered heterocycles described in Chapter 10. 

The results of the 4D-QSAR case study are interesting and provide large amounts of data about the system of interest, and, unlike static 3D-QSAR methods (CoMFA and SOMFA), 4D-QSAR is able to provide the exact locations of statistically important interaction pharmacophore elements. The ability of this method to overcome the question of What conformation to use and predict the bioactive conformation is impressive and a major reason to use the software. Yet it is the ability to construct manifold models and examine several models for the same alignment that is the true benefit of this method. Add to the list the ability to determine the best alignment scheme (based on statistical and experimental results) and this method will provide more information than one could imagine. This abundance of information is key when troubleshooting results that are not in agreement with current beliefs. 

If the bioactive conformation of a ligand for a particular receptor is known, then a single three- or four-point 3D pharmacophore that is crucial for the... 

Depending on which face it puts forward, a single dmg molecule may interact with more than one receptor and thus may have more than one pharmacophoric pattern. For example, one bioactive face of acetylcholine permits interaction with a muscarinic receptor, while another bioactive face of acetylcholine permits interaction with a nicotinic receptor (section 4.2). Similarly, the excitatory neurotransmitter glutamate may bind to a range of different receptors, such as the NMDA and AMPA receptors (section 4.7), depending upon the pharmacophoric pattern displayed by the glutamate molecule toward the receptor with which it is interacting. 

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