The Internet of Medical Things (IoMT)

1In Silico Molecular Modeling and Docking Analysis in Lung Cancer Cell Proteins

Manisha Sritharan¹ and Asita Elengoe^2*

¹Department of Science and Biotechnology, Faculty of Engineering and Life Sciences, University of Selangor, Bestari Jaya, Selangor, Malaysia

²Department of Biotechnology, Faculty of Science, Lincoln University College, Petaling Jaya, Selangor, Malaysia

Abstract

In this study, the three-dimensional (3D) models of lung cancer cell line proteins [epidermal growth factor (EGFR), K-ras oncogene protein, and tumor suppressor (TP53)] were generated and their binding affinities with curcumin, ellagic acid, and quercetin through local docking were assessed. Firstly, Swiss model was used to build lung cancer cell line proteins and then visualized by the PyMol software. Next, ExPASy ProtParam Proteomics server was used to evaluate the physical and chemical parameters of the protein structures. Furthermore, the protein models were validated using PROCHECK, ProQ, ERRAT, and Verify3D programs. Lastly, the protein models were docked with curcumin, ellagic acid, and quercetin by using BSP-Slim server. All three protein models were adequate and in exceptional standard. The curcumin showed binding energy with EGFR, K-ras oncogene protein, and TP53 at 5.320, 2.730, and 1.633, kcal/mol, respectively. Besides that, the ellagic acid showed binding energy of EGFR, K-ras oncogene protein, and TP53 at –2.892, 0.921, and 0.054 kcal/mol, respectively. Moreover, the quercetin showed ...