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From empirical structure modifications to QSAR.

A C Glasser

    Methods and Findings in Experimental and Clinical Pharmacology
    |October 1, 1984
    PubMed
    Summary

    This review traces the historical evolution of drug discovery, from ancient practices to modern computational methods like Quantitative Structure-Activity Relationships (QSAR). It highlights key techniques and their development over time.

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    Area of Science:

    • Medicinal Chemistry
    • Drug Discovery
    • Computational Chemistry

    Background:

    • Humanity's drug search spans from prehistoric times to advanced computational techniques.
    • The evolution reflects a growing understanding of chemical structures and biological activity.

    Purpose of the Study:

    • To provide a historical overview of drug discovery methodologies.
    • To detail the development and application of Quantitative Structure-Activity Relationships (QSAR).

    Main Methods:

    • Historical review of drug discovery approaches.
    • Detailed explanation of the Hansch concept, including multiple regression analysis and partition coefficient.
    • Introduction to de novo methods like Free-Wilson and non-computerized techniques (Topliss, Darvas).
    • Mention of interactive computer graphics in modern drug design.

    Main Results:

    • The Hansch equation and related methods have significantly advanced drug design.
    • Various computational and non-computational methods offer diverse approaches to drug discovery.
    • The field has progressed from empirical observations to sophisticated predictive modeling.

    Conclusions:

    • The historical trajectory shows a continuous innovation in drug discovery tools.
    • QSAR and related computational methods represent a major leap in understanding structure-activity relationships.
    • A diverse toolkit, from simple to complex, aids the ongoing search for new therapeutics.

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