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Functional group contributions to drug-receptor interactions.

P R Andrews, D J Craik, J L Martin

    Journal of Medicinal Chemistry
    |December 1, 1984
    PubMed
    Summary

    This study quantifies average binding energies for common functional groups in drugs and enzyme inhibitors. Charged groups exhibit the strongest binding, followed by polar and nonpolar groups, aiding in predicting drug-receptor interactions.

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    Area of Science:

    • Medicinal Chemistry
    • Computational Drug Design
    • Biophysics

    Background:

    • Understanding drug-receptor interactions is crucial for drug discovery.
    • Accurate prediction of binding affinity requires quantitative assessment of molecular interactions.
    • Previous methods for estimating binding energy were limited in scope.

    Purpose of the Study:

    • To calculate and tabulate intrinsic binding energies for common functional groups.
    • To develop a method for predicting drug-receptor binding based on functional group contributions.
    • To assess the goodness of fit for various drug molecules to their targets.

    Main Methods:

    • Utilized binding constants and structural data from 200 drugs and enzyme inhibitors.
    • Calculated average intrinsic binding energies for charged, polar, and nonpolar functional groups.
    • Developed a model incorporating intrinsic binding energies and entropic terms to predict overall binding energy.

    Main Results:

    • Established intrinsic binding energies (kcal/mol): charged groups (8.2–11.5), polar groups (1.1–3.4), and nonpolar groups (0.7–0.8).
    • Demonstrated that drug-receptor fit can be assessed by comparing experimental binding energy to calculated values.
    • Identified drugs like diazepam and biotin as having exceptionally good receptor fits, while methotrexate and buprenorphine showed poorer fits than average.

    Conclusions:

    • The derived intrinsic binding energies provide a quantitative basis for predicting drug-receptor interactions.
    • The method allows for the assessment of drug efficacy based on structural components and binding thermodynamics.
    • This approach can guide the design of new drugs with optimized binding affinities and therapeutic potential.

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