Rational drug design using genetic algorithm: case of malaria disease
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...
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| Format: | Article |
| Language: | English |
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CIS Journal
2012
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| Online Access: | http://irep.iium.edu.my/25623/1/cis-journal.pdf |
| _version_ | 1825646772178911232 |
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| author | Al-Safi, Hassen Mohammed Alshaikhli, Imad Fakhri Taha |
| author_facet | Al-Safi, Hassen Mohammed Alshaikhli, Imad Fakhri Taha |
| author_sort | Al-Safi, Hassen Mohammed |
| collection | IIUM |
| description | 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. |
| first_indexed | 2024-03-05T23:07:34Z |
| format | Article |
| id | oai:generic.eprints.org:25623 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-13T18:57:35Z |
| publishDate | 2012 |
| publisher | CIS Journal |
| record_format | dspace |
| spelling | oai:generic.eprints.org:256232012-09-07T01:21:32Z http://irep.iium.edu.my/25623/ Rational drug design using genetic algorithm: case of malaria disease Al-Safi, Hassen Mohammed Alshaikhli, Imad Fakhri Taha QA75 Electronic computers. Computer science 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. CIS Journal 2012-07 Article PeerReviewed application/pdf en http://irep.iium.edu.my/25623/1/cis-journal.pdf Al-Safi, Hassen Mohammed and Alshaikhli, Imad Fakhri Taha (2012) Rational drug design using genetic algorithm: case of malaria disease. Journal of Emerging Trends in Computing and Information Sciences, 3 (7). pp. 1093-1102. ISSN 2218-6301 (O), 2079-8407 (P) http://www.cisjournal.org |
| spellingShingle | QA75 Electronic computers. Computer science Al-Safi, Hassen Mohammed Alshaikhli, Imad Fakhri Taha Rational drug design using genetic algorithm: case of malaria disease |
| title | Rational drug design using genetic algorithm: case of malaria disease |
| title_full | Rational drug design using genetic algorithm: case of malaria disease |
| title_fullStr | Rational drug design using genetic algorithm: case of malaria disease |
| title_full_unstemmed | Rational drug design using genetic algorithm: case of malaria disease |
| title_short | Rational drug design using genetic algorithm: case of malaria disease |
| title_sort | rational drug design using genetic algorithm case of malaria disease |
| topic | QA75 Electronic computers. Computer science |
| url | http://irep.iium.edu.my/25623/1/cis-journal.pdf |
| work_keys_str_mv | AT alsafihassenmohammed rationaldrugdesignusinggeneticalgorithmcaseofmalariadisease AT alshaikhliimadfakhritaha rationaldrugdesignusinggeneticalgorithmcaseofmalariadisease |