Literature DB >> 24765112

Structure-activity relationship analysis on the basis of matched molecular pairs.

Anne Mai Wassermann1.   

Abstract

Entities:  

Year:  2014        PMID: 24765112      PMCID: PMC3980054          DOI: 10.1186/1758-2946-6-S1-O14

Source DB:  PubMed          Journal:  J Cheminform        ISSN: 1758-2946            Impact factor:   5.514


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Matched molecular pairs (MMPs), i.e., pairs of compounds that are related to each other by a specific molecular transformation, have become an integral tool of drug discovery [1,2]. Generally spoken, matched molecular pair analysis (MMPA) aims at the extraction of all MMPs from a set of compounds and their association with calculated or measured property changes. Using public bioactivity data, we have used MMPs as a consistent reference framework to identify sets of chemical replacements that either have the propensity to induce large-magnitude potency changes or tend to retain compound potency across diverse targets [3,4]. Furthermore, we have extended the concept of MMPs to matched molecular series, i.e., analog series with different molecular core structures but corresponding substitution patterns [5,6]. The identification of series with alternative core structures but similar SAR trends is highly relevant for lead optimization where SAR information from one series that has been explored historically is ideally used to guide compound design efforts for a new chemotype [6].
  6 in total

1.  Matched molecular pairs as a medicinal chemistry tool.

Authors:  Ed Griffen; Andrew G Leach; Graeme R Robb; Daniel J Warner
Journal:  J Med Chem       Date:  2011-09-22       Impact factor: 7.446

2.  Chemical substitutions that introduce activity cliffs across different compound classes and biological targets.

Authors:  Anne Mai Wassermann; Jürgen Bajorath
Journal:  J Chem Inf Model       Date:  2010-07-26       Impact factor: 4.956

3.  Local structural changes, global data views: graphical substructure-activity relationship trailing.

Authors:  Mathias Wawer; Jürgen Bajorath
Journal:  J Med Chem       Date:  2011-03-28       Impact factor: 7.446

4.  Large-scale exploration of bioisosteric replacements on the basis of matched molecular pairs.

Authors:  Anne Mai Wassermann; Jürgen Bajorath
Journal:  Future Med Chem       Date:  2011-03       Impact factor: 3.808

5.  A data mining method to facilitate SAR transfer.

Authors:  Anne Mai Wassermann; Jürgen Bajorath
Journal:  J Chem Inf Model       Date:  2011-08-08       Impact factor: 4.956

Review 6.  Matched molecular pair analysis in drug discovery.

Authors:  Alexander G Dossetter; Edward J Griffen; Andrew G Leach
Journal:  Drug Discov Today       Date:  2013-04-02       Impact factor: 7.851

  6 in total

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