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Computer-aided drug design.

G R Marshall

    Annual Review of Pharmacology and Toxicology
    |January 1, 1987
    PubMed
    Summary
    This summary is machine-generated.

    Computational tools are advancing for molecular interactions, aiding drug design. Further theoretical chemistry progress will enhance molecular design for medicinal chemists and protein engineers.

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    Area of Science:

    • Computational chemistry and molecular modeling.
    • Biotechnology and genetic engineering.
    • Medicinal chemistry and drug discovery.

    Background:

    • Increased demand for computational tools in molecular interaction studies due to genetic engineering progress.
    • Advances in computational hardware have removed previous limitations.
    • Current computer-aided drug design (CADD) relies on experienced medicinal chemists' insights.

    Purpose of the Study:

    • To highlight the advancements and future needs in computational tools for molecular interactions.
    • To discuss the role of theoretical chemistry in developing robust molecular design.
    • To project the future impact of enhanced molecular design on drug discovery and protein engineering.

    Main Methods:

    • Review of current progress in computational techniques for molecular interactions.

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  • Analysis of the interplay between theoretical chemistry and computational hardware.
  • Evaluation of the current state and limitations of computer-aided drug design.

    • Main Results:

    • Significant advancements in computational techniques and their applications have been demonstrated.
    • Further development necessitates progress in theoretical chemistry and practical experience.
    • Computer-aided drug design currently supplements, rather than replaces, expert knowledge.

    Conclusions:

    • Molecular design is poised to become a realistic and valuable tool for medicinal chemists and protein engineers.
    • Continued progress in theoretical foundations will solidify the role of computational methods in molecular design.
    • The integration of computational tools and expert insight will accelerate innovation in drug discovery and biotechnology.