Virtual screening of natural compounds as inhibitors of EGFR 696-1022 T790M associated with non-small cell lung cancer
| Autor: | Veena Pande, Subhash Chandra, Madhulata Kumari, Mahesha Nand, Ragini Pant, Priyanka Maiti |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
EGFR In silico 03 medical and health sciences T790M natural compounds medicine Cytotoxic T cell Epidermal growth factor receptor Lung cancer Virtual screening biology Chemistry Active site Cancer molecular docking prediction General Medicine Hypothesis medicine.disease respiratory tract diseases lung cancer machine learning 030104 developmental biology Cancer research biology.protein |
| Zdroj: | Bioinformation |
| ISSN: | 0973-2063 0973-8894 |
| Popis: | Non-small cell lung cancer (NSCLC) is the most dominating and lethal type of lung cancer triggering more than 1.3 million deaths per year. The most effective line of treatment against NSCLC is to target epidermal growth factor receptor (EGFR) activating mutation. The present study aims to identify the novel anti-lung cancer compounds form nature against EGFR 696-1022 T790M by using in silico approaches. A library of 419 compounds from several natural resources was subjected to pre-screen through machine learning model using Random Forest classifier resulting 63 screened molecules with active potential. These molecules were further screened by molecular docking against the active site of EGFR 696-1022 T790M protein using AutoDock Vina followed by rescoring using X-Score. As a result 4 compounds were finally screened namely Granulatimide, Danorubicin, Penicinoline and Austocystin D with lowest binding energy which were -6.5 kcal/mol, -6.1 kcal/mol, -6.3 kcal/mol and -7.1 kcal/mol respectively. The drug likeness of the screened compounds was evaluated using FaF-Drug3 server. Finally toxicity of the hit compounds was predicted in cell line using the CLC-Pred server where their cytotoxic ability against various lung cancer cell lines was confirmed. We have shown 4 potential compounds, which could be further exploited as efficient drug candidates against lung cancer. |
| Databáze: | OpenAIRE |
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