Pharmacophore development for identification of anti-lung cancer drugs
Pharmacophore development for identification of anti-lung cancer drugs Pharmacophore development for identification of anti-lung cancer drugs Sadia Abbasi a,*, Shanila Emmanuel a, Muhammad Haseeba, Aftab Khalil a,
Saima Kulsoom b, Hamid Rashid a, Raisa Bano a a b
Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad, Pakistan
Department of Chemistry, Quiad-e-Azam University, Pakistan
Lung cancer is one particular type of cancer that is more deadly and common than any other. Lung cancer is treated with chemotherapy, radiation therapy and surgery depending on the type of lung cancer and the stage of the disease. Focusing on the drugs used for chemotherapy and their associated side effects, there is a need to design and develop new anti-lung cancer drugs with lesser side effects and improved efficacy.
Pharmacophore model proves to be a very helpful tool serving in the designing and development of new lead compounds. In this paper, pharmacophore of 10 novel anti-lung cancer compounds has been identified and validated for the first time. Using LigandScout the pharmacophore features were predicted and 3D pharmacophore have been extracted via VMD software. A training set data was collected from literature and the proposed model was applied to the training set whereby validating and verifying their similar activity as that of the most active compounds. Therefore they could be recommended for further studies. Key words: Pharmacophore, anti-lung cancer drugs, Computer aided drug designing, LigandScout, VMD
INTRODUCTION
Lung cancer is known to have a high fatality rate among males and females and takes more lives each year as compared to colon, prostate, ovarian and breast cancers (1).Lung cancer is classified into two main types namely Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC) of which
NSCLC accounts for about 80% cases and SCLC accounts for 10-15% among all other types of lung cancers (2).
Saima Kulsoom b, Hamid Rashid a, Raisa Bano a a b
Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad, Pakistan
Department of Chemistry, Quiad-e-Azam University, Pakistan
Lung cancer is one particular type of cancer that is more deadly and common than any other. Lung cancer is treated with chemotherapy, radiation therapy and surgery depending on the type of lung cancer and the stage of the disease. Focusing on the drugs used for chemotherapy and their associated side effects, there is a need to design and develop new anti-lung cancer drugs with lesser side effects and improved efficacy.
Pharmacophore model proves to be a very helpful tool serving in the designing and development of new lead compounds. In this paper, pharmacophore of 10 novel anti-lung cancer compounds has been identified and validated for the first time. Using LigandScout the pharmacophore features were predicted and 3D pharmacophore have been extracted via VMD software. A training set data was collected from literature and the proposed model was applied to the training set whereby validating and verifying their similar activity as that of the most active compounds. Therefore they could be recommended for further studies. Key words: Pharmacophore, anti-lung cancer drugs, Computer aided drug designing, LigandScout, VMD
INTRODUCTION
Lung cancer is known to have a high fatality rate among males and females and takes more lives each year as compared to colon, prostate, ovarian and breast cancers (1).Lung cancer is classified into two main types namely Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC) of which
NSCLC accounts for about 80% cases and SCLC accounts for 10-15% among all other types of lung cancers (2).
References: Sridhar Ramaswamy, M.D. Rational Design of Cancer-Drug Combinations, 2007. Drc :A Review of LigandScout, 2008 Wolber, G.; Langer, T.; LigandScout: 3-D Pharmacophores Derived from Protein-Bound Ligands and III trial. Joint Lung Cancer Study Group. Helsing M, Bergman B, Thaning L, Hero U Eur J Cancer. 1998 Jun; 34(7):1036-44. Kapetanoic,I.M., 2008. Computer aided Drug discovery and development: insilico-chemico-biological approach