Rational drug design using genetic algorithm: case of malaria disease

• Main Authors: Al-Safi, Hassen Mohammed, Alshaikhli, Imad Fakhri Taha
• Format: Article
• Language: English
• Published: CIS Journal 2012
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://irep.iium.edu.my/25623/1/cis-journal.pdf; http://irep.iium.edu.my/25623/; http://www.cisjournal.org

With the rapid development in the amount of molecular biological structures, computational molecular docking (CMD) approaches become one of the crucial tools in rational drug design (RDD). Currently, number of researchers are working in this filed to overcome the recent issues of docking by using genetic algorithm approach. Moreover, Genetic Algorithm facilities the researchers and scientists in molecular docking experiments. Since conducting the experiment in the laboratory considered as time consuming and costly, the scientists determined to use the computational techniques to simulate their experiments. In this paper, auto dock 4.2, well known docking simulation has been used to perform the experiment in specific disease called malaria. The genetic algorithm (GA) approach in the autodock4.2 has been used to search for the potential candidate drug in the twenty drugs. It shows the great impacts in the results obtained from the CMD simulation. In the experiment, we used falcipain-2 as our target protein (2GHU.pdb) obtained from the protein data bank and docked with twenty different available anti malaria drugs in order to find the effective and efficient drugs. Drug Diocopeltine A was found as the best lowest binding energy with the value of -8.64 Kcal/mol. Thus, it can be selected as the anti malaria drug candidate.