QSAR of phytochemicals for the design of better drugs.
BACKGROUND
Phytochemicals have been the single most prolific source of leads for the development of new drug entities from the dawn of the drug discovery. They cover a wide range of therapeutic indications with a great diversity of chemical structures. The research fraternity still believes in exploring the phytochemicals for new drug discovery. Application of molecular biological techniques has increased the availability of novel compounds that can be conveniently isolated from natural sources. Combinatorial chemistry approaches are being applied based on phytochemical scaffolds to create screening libraries that closely resemble drug-like compounds. In silico techniques like quantitative structure-activity relationships (QSAR), pharmacophore and virtual screening are playing crucial and rate accelerating steps for the better drug design in modern era.


METHODS
QSAR models of different classes of phytochemicals covering different therapeutic areas are thoroughly discussed in the review. Further, the authors have enlisted all the available phytochemical databases for the convenience of researchers working in the area.


CONCLUSIONS
This review justifies the need to develop more QSAR models for the design of better drugs from phytochemicals. Technical drawbacks associated with phytochemical research have been lessened, and there are better opportunities to explore the biological activity of previously inaccessible sources of phytochemicals although there is still the need to reduce the time and cost involvement in such exercise. The future possibilities for the integration of ethnopharmacology with QSAR, place us at an exciting stage that will allow us to explore plant sources worldwide and design better drugs.
Jadavpur University, Department of Pharmaceutical Technology, Drug Theoretics and Cheminformatics Laboratory, Kolkata, India. kunalroy_in@yahoo.com
Supratik
S
Kar
Kunal
K
Roy
D000818:Animals; D016208:Databases, Factual; D015195:Drug Design; D006801:Humans; D008517:Phytotherapy; D010946:Plants, Medicinal; D021281:Quantitative Structure-Activity Relationship