Abstract

INSILICO STRUCTURE BASED DRUG DESIGNING OF LEAD COMPOUNDS FOR LUNG CANCER

Amutha Muthusamy*, Lalitha Pottail and Jannathul Firdhouse

ABSTRACT

One of the dreadful cancers which contribute to the highest death rate is Lung cancer. Unforeseen surge in the rate of cancer incidence, rise in death toll and detrimental side effects elicited by the medicines already in use, validate the need for new drugs. Cheminformatics tools serve in designing new drugs. This paper focuses on arriving at new drug leads for lung cancer. Gamma-enolase, an auxiliary marker in lung cancer is docked with nine ligands which have structural similarity to the chemical constitutents in Kedrostis foetidissima Jacq.Cogn. and compared with the standard drugs commercially used in the treatment of lung cancer such as Gemcitabine and Crizotinib. All the nine ligands shows better GLIDE score and GLIDE energy. Ligand AM1 (2-[(4-{[(2,4-diaminopteridin-6-yl)mthyl] aminophenyl} formamido] pentanedioic acid) shows excellent docking (GLIDE score: -6.926 Kcal mol-1; GLIDE energy: -63.592 Kcal mol-1 ) with 1TE6 protein than the standard drugs Gemcitabine (GLIDE score: -4.922 Kcal mol-1; GLIDE energy: -37.548 Kcal mol-1) and Crizotinib (GLIDE score: -6.212 Kcal mol-1; GLIDE energy: -52.790 Kcal mol-1). In Silico studies of nine selected ligands discloses AM-1 was efficient than the standard drugs Crizotinib and Gemcitabine; the standard drugs used in the treatment of Human Lung cancer. This paper also focuses on the use of insilico methods in arriving at new drug leads.

Keywords: 1TE6 protein, Lung cancer, GLIDE scores.