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One of the main issues faced currently by the pharmaceutical industry is the rational design of the appropriate lead compound and its analogues for a given target protein and ensuring that these compounds are highly specific for the studied target. This is not an easy task in the laboratory usually requires a great deal of effort and it has some limitations to be performed routinely. Similar information can be handled more easily using molecular modeling techniques such as molecular docking, 2D or 3D quantitative structure-activity relationships (QSAR) studies, pharmacophore models, molecular dynamics (MD) simulations and virtual screening techniques, which have become feasible during the last decade. In this study, recent advances in computational drug design approaches are discussed using the extensive in silico applications on bioactive cannabinoid and fullerene derivatives.

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Dr. Durdagi has been applying computational chemistry methods to biological systems for several years. His expertise lays in the field of protein-drug interactions and optimization protocols for rational drug design. His PhD degree was awarded from Free Univ. of Berlin. He has published 16 articles in top peer reviewed journals.

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