%0 Journal Article %1 Devi2015EvoDrugDesign %A Devi, R. Vasundhara %A Sathya, S. Siva %A Coumar, Mohane Selvaraj %D 2015 %J Applied Soft Computing %K drug-design evolutionary-algorithms evolutionary-drug-design molecular-dynamics %P 543 - 552 %R http://dx.doi.org/10.1016/j.asoc.2014.09.042 %T Evolutionary algorithms for de novo drug design – A survey %U http://www.sciencedirect.com/science/article/pii/S1568494614004955 %V 27 %X Abstract The process of drug design and discovery demands several man years and huge investment. Computer-aided drug design (CADD) technique is an aid to speed up the drug discovery process. De novo drug design, a \CADD\ technique to identify drug-like novel chemical structures from a huge chemical search space, helps to find new drugs by the optimization of multiple pharmaceutically relevant parameters required for a successful drug. As the search space is very large in the case of de novo drug design, evolutionary algorithm (EA), a soft computing technique can be used to find an optimal solution, which in this case is a novel drug. In this paper, various \EA\ techniques used in de novo drug design tools are surveyed and analyzed in detail, with particular emphasis on the computational aspects.

@article{Devi2015EvoDrugDesign, abstract = {Abstract The process of drug design and discovery demands several man years and huge investment. Computer-aided drug design (CADD) technique is an aid to speed up the drug discovery process. De novo drug design, a \{CADD\} technique to identify drug-like novel chemical structures from a huge chemical search space, helps to find new drugs by the optimization of multiple pharmaceutically relevant parameters required for a successful drug. As the search space is very large in the case of de novo drug design, evolutionary algorithm (EA), a soft computing technique can be used to find an optimal solution, which in this case is a novel drug. In this paper, various \{EA\} techniques used in de novo drug design tools are surveyed and analyzed in detail, with particular emphasis on the computational aspects. }, added-at = {2016-03-15T20:05:30.000+0100}, author = {Devi, R. Vasundhara and Sathya, S. Siva and Coumar, Mohane Selvaraj}, biburl = {https://www.bibsonomy.org/bibtex/2f32a3d44337bcb795e68e9b157ab3fdb/salotz}, description = {Evolutionary algorithms for de novo drug design – A survey}, doi = {http://dx.doi.org/10.1016/j.asoc.2014.09.042}, interhash = {b41bce5d1633441928573cb38afa6233}, intrahash = {f32a3d44337bcb795e68e9b157ab3fdb}, issn = {1568-4946}, journal = {Applied Soft Computing }, keywords = {drug-design evolutionary-algorithms evolutionary-drug-design molecular-dynamics}, pages = {543 - 552}, timestamp = {2016-03-15T20:05:30.000+0100}, title = {Evolutionary algorithms for de novo drug design – A survey }, url = {http://www.sciencedirect.com/science/article/pii/S1568494614004955}, volume = 27, year = 2015 }