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Chirality Descriptors in QSAR

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Chirality is an important concept in medicinal chemistry, since many biochemical reactions and processes are stereospecific, including the recognition of some drugs by their receptors. Quantitative structure-activity relations (QSAR) are mathematical models that relate chemical structure and/or molecular properties to biological activity, and incorporating stereospecificity into QSAR can be essential for some studies. Starting with the mathematical concept of oriented volume and with the notational viewpoint of the Cahn-Ingold-Prelog rules, qualitative chirality descriptors can be built into covalent connectivity graph invariants several ways, some of which emphasize properties other than atomic number and may involve multiple chiral centers. Alternatively, there are several ways to define chirality quantitatively. One approach is to measure the van der Waals volume overlap when optimally superimposing a molecule and its mirror image. Another way is to measure the degree of distortion required to convert the molecule or subsets of its atoms into a structure having a desired symmetry, such as mirror symmetry. The third quantitative approach involves translating and rotating the molecule to a standard position associated with symmetry axes based on various atomic properties. The advantages and disadvantages of all these methods are discussed, and key equations are presented.

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Keywords: CIP rules; Chirality; QSAR; enantiomers; graph invariants; quantitative chirality; symmetry

Document Type: Research Article

Publication date: December 1, 2008

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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