Predicting ADMET Properties for Commercially Available Anticancer Drugs
Shanmuga SundariIlangovan1, Subash R2, Janani N3, Ishwarya P4
1Shanmuga SundariIlangovan, Department of Biotechnology, Bannari Amman Institute of Technology, Sathya Mangalam, Tamil Nadu, India.
2Subash R, Department of Biotechnology, Bannari Amman Institute of Technology, Sathya Mangalam, Tamil Nadu, India.
3Janani N, Department of Biotechnology, Bannari Amman Institute of Technology, Sathya Mangalam, Tamil Nadu, India.
4Ishwarya P, Department of Biotechnology, Bannari Amman Institute of Technology, Sathya Mangalam, Tamil Nadu, India.
Manuscript received on 01 December 2018 | Revised Manuscript received on 06 December 2018 | Manuscript Published on 26 December 2018 | PP: 130-141 | Volume-8 Issue- 2S2 December 2018 | Retrieval Number: BS2028128218/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Drug discovery and development is a tedious process which involves high man power, costly chemicals and resources. Failure of drugs at late stage clinical trials is the common problem that occurs at current scenario. Though tremendous input has been given to discover new drugs, overcoming the drug failures and occurrence of adverse side effects need to be rectified. Predicting Absorption, Distribution, Metabolism and Excretion (ADME) properties at early stage with in silico tools would be much promising. In this paper, commercially available anticancer drugs were taken and their ADME properties were predicted with SWISS ADME. The results shows that most of the drugs possess lower solubility, low GL absorption and lower penetration to blood brain barrier. The obtained results could be a model to develop new drugs and to design anticancer drugs that eventually prevent late stage clinical trials.
Keywords: ADME, Anticancer, Drugs, SWISS ADME, Clinical Trials.
Scope of the Article: Bio-Technology