An In silico Approach to Identify High Affinity Small Molecule Targeting m-TOR Inhibitors for the Clinical Treatment of Breast Cancer

Document Type: Research Articles


1 In silico Research Laboratory, Eminent Biosciences, Indore, Madhya Pradesh, India.

2 Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi,Tamil Nadu, India.

3 Department of Biotechnology, Lovely Faculty of Technology and Sciences, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, India.

4 Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd., Indore, India.


Breast cancer is the most frequent malignancy among women. It is a heterogeneous disease with different subtypes
defined by its hormone receptor. A hormone receptor is mainly concerned with the progression of the PI3K/AKT/
mTOR pathway which is often dysregulated in breast cancer. This is a major signaling pathway that controls the
activities such as cell growth, cell division, and cell proliferation. The present study aims to suppress mTOR protein
by its various inhibitors and to select one with the highest binding affinity to the receptor protein. Out of 40 inhibitors
of mTOR against breast cancer, SF1126 was identified to have the best docking score of -8.705, using Schrodinger
Suite which was further subjected for high throughput screening to obtain best similar compound using Lipinski’s
filters. The compound obtained after virtual screening, ID: ZINC85569445 is seen to have the highest affinity with
the target protein mTOR. The same result based on the binding free energy analysis using MM-GBSA showed that
the compound ZINC85569445 to have the the highest binding free energy. The next study of interaction between the
ligand and receptor protein with the pharmacophore mapping showed the best conjugates, and the ZINC85569445 can
be further studied for future benefits of treatment of breast cancer.


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