Literature DB >> 28967750

Turbocharging Matched Molecular Pair Analysis: Optimizing the Identification and Analysis of Pairs.

Iva Lukac1, Joanna Zarnecka1, Edward J Griffen2, Alexander G Dossetter2, Stephen A St-Gallay3, Steven J Enoch1, Judith C Madden1, Andrew G Leach1,2.   

Abstract

We have applied the two most commonly used methods for automatic matched pair identification, obtained the optimum settings, and discovered that the two methods are synergistic. A turbocharging approach to matched pair analysis is advocated in which a first round (a conservative categorical approach that uses an analogy with coin flips, heads corresponding to an increase in a measured property, tails to a decrease, and a biased coin to a structural change that reliably causes a change in that property) provides the settings for a second round (which uses the magnitude of the change in properties). Increased chemical specificity allows reliable knowledge to be extracted from smaller sets of pairs, and an assay-specific upper limit can be placed on the number of pairs required before adequate sampling of variability has been achieved.

Mesh:

Year:  2017        PMID: 28967750     DOI: 10.1021/acs.jcim.7b00335

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  1 in total

1.  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

  1 in total

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