Literature DB >> 27477265

Prospective Prediction of Antitarget Activity by Matched Molecular Pairs Analysis.

Daniel J Warner1, Matthew H Bridgland-Taylor2, Clare E Sefton2, David J Wood3.   

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.
Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  De-novo design; Ionworks; Matched molecular pairs analysis; QSAR; hKCNQ1-hKCNE1

Year:  2012        PMID: 27477265     DOI: 10.1002/minf.201200020

Source DB:  PubMed          Journal:  Mol Inform        ISSN: 1868-1743            Impact factor:   3.353


  2 in total

1.  Predicting liver cytosol stability of small molecules.

Authors:  Pranav Shah; Vishal B Siramshetty; Alexey V Zakharov; Noel T Southall; Xin Xu; Dac-Trung Nguyen
Journal:  J Cheminform       Date:  2020-04-07       Impact factor: 5.514

2.  Data-Driven Derivation of Molecular Substructures That Enhance Drug Activity in Gram-Negative Bacteria.

Authors:  Dominik Gurvic; Andrew G Leach; Ulrich Zachariae
Journal:  J Med Chem       Date:  2022-04-15       Impact factor: 8.039

  2 in total

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