title: Prospective Prediction of Antitarget Activity by Matched Molecular Pairs Analysis.
abstract: Matched molecular pairs analysis (MMPA)1,2 is an inverse quantitative structure activity relationship (QSAR) technique that is rapidly gaining popularity in the retrospective analysis of large experimental datasets.3,4 While much of the recent focus has been on the differences in properties between structurally related groups of existing compounds, attempts to extend this methodology to the de-novo design of novel structures have been limited. To our knowledge the aggregate effect of multiple transformations, all suggesting the same molecular structure, has only ever being considered within a very limited dataset.5 We therefore sought to test this exciting new approach to the design (and absolute property prediction - effectively QSAR-by-MMPA) of novel chemical entities based on a larger, more diverse dataset, and couple these designs to MMPA-based predictions of antitarget activity.
authors.affiliation: Department of Medicinal Chemistry, AstraZeneca R&D Montreal, Montreal, Quebec, H4S 1Z9, Canada. dan.warner@astrazeneca.com.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Warner
authors.affiliation: Department of Safety Pharmacology, Safety Assessment UK, AstraZeneca Pharmaceuticals, Alderley Park, Macclesfield, SK10 4TG, UK.
authors.forename: Matthew H
authors.initials: MH
authors.lastname: Bridgland-Taylor
authors.affiliation: Department of Safety Pharmacology, Safety Assessment UK, AstraZeneca Pharmaceuticals, Alderley Park, Macclesfield, SK10 4TG, UK.
authors.forename: Clare E
authors.initials: CE
authors.lastname: Sefton
authors.affiliation: Discovery Sciences, AstraZeneca Pharmaceuticals, Alderley Park, Macclesfield, SK10 4TG, UK.
authors.forename: David J
authors.initials: DJ
authors.lastname: Wood
keywords: De-novo design; Ionworks; Matched molecular pairs analysis; QSAR; hKCNQ1-hKCNE1