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Advances in Computational Medicinal Chemistry: Matched Molecular Pair Analysis

Authors

  • Anne Mai Wassermann,

    1. Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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    • These authors contributed equally to this work.
  • Dilyana Dimova,

    1. Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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    • These authors contributed equally to this work.
  • Preeti Iyer,

    1. Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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  • Jürgen Bajorath

    Corresponding author
    • Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
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Correspondence to: Jürgen Bajorath, Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Dahlmannstr. 2, D-53113 Bonn, Germany.

E-mail: bajorath@bit.uni-bonn.de

Abstract

Preclinical Research

Herein we discuss the concept of matched molecular pairs (MMPs) and relevant medicinal chemistry applications. In recent years, this concept has become popular in medicinal chemistry as it provides a formal and general basis to establish structural relationships between compounds, identify chemical changes that transform structurally related compounds into each other, and facilitate a large-scale analysis of structure–activity relationships. Algorithms have been developed for the systematic computational identification of qualifying pairs in large compound databases. In addition to a number of other areas such as graphical analysis and visualization of structure–activity relationships, systematic MMP analysis has significantly advanced the field of computational medicinal chemistry, providing a basis for many practical applications. Characteristic features of this concept include that it eliminates subjective criteria from structural comparisons, alleviates the need to employ predefined molecular hierarchies in studying structural relationships, and elucidates distinguishing structural features between active compounds in a highly intuitive manner. Hence, the results of computational MMP analysis are readily accessible to medicinal chemists, which makes this type of analysis highly attractive for a variety of applications.

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