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Updated: Aug 17, 2026
Utilization of the Soft Agar Colony Formation Assay to Identify Inhibitors of Tumorigenicity in Breast Cancer Cells
Published on: May 20, 2015
Ligand and structure based virtual screening of chemical databases to explore potent small molecule inhibitors
Shivangi Agarwal1, Anshuman Dixit2, Sushil K Kashaw1
1Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar, MP, India.
Abstract:
Breast carcinoma is the most common invasive cancer to affect the women in the North America and the world. Cancer of breast is the number one cancer overall with estimated 1.5 lakh new cases during 2016. The success of the current endocrine therapies is often limited due to the development of resistance. Therefore, there is a need to develop new lead compounds for breast cancer treatment. As 70% of breast carcinoma is ER+, and it is well known previously that estrogen receptor alpha (ERα) is overexpressed in ER + cases, so in the current work we attempt to develop some novel potent analogues against ERα. To achieve this, we have adopted an integrative computational approach that involves multiple sequence alignment, virtual screening (ligand and structure based), molecular docking, fingerprint based clustering and molecular dynamics simulation. The approach envisaged vital information about the binding site residues, conserved sequence among different species, ligand and protein conformations, binding energy of compound to bind into the active site of the receptor. Molecular docking analysis revealed that some analogues exhibited significant binding towards ERα. The top docked complexes showing good docking scores, hydrogen bond and hydrophobic interactions were selected for molecular dynamics simulation studies. RMSD revealed that the systems were quite stable with RMSD value below 3 Å. The RMSF analysis calculated residue wise fluctuations and revealed that the residues are flexible enough to interact with the ligand. The residue at C-terminal showed more flexibility as compared to other residues. To confirm binding of these analogues, MMGBSA analysis was performed which revealed binding energy of the ligands. Further, per-residue decomposition energy analysis revealed that Glu353, Leu346, Leu387 and Arg394 contributed towards ligand binding. The results visibly indicated that MMGBSA can act as filter in virtual screening experiments and play a major role in facilitating drug discovery.
Insights
Researchers developed novel potent analogues against estrogen receptor alpha (ERα) to combat breast cancer resistance to endocrine therapies. Computational methods identified promising compounds with significant binding affinity for potential new treatments.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Breast carcinoma is a leading cancer in women globally, with resistance to endocrine therapies limiting treatment success.
- Estrogen receptor alpha (ERα) is overexpressed in ER-positive breast cancers, making it a key therapeutic target.
Purpose of the Study:
- To develop novel potent analogues targeting estrogen receptor alpha (ERα) for breast cancer treatment.
- To identify new lead compounds that can overcome resistance to current endocrine therapies.
Main Methods:
- An integrative computational approach combining multiple sequence alignment, virtual screening, molecular docking, and molecular dynamics simulation.
- Analysis of binding site residues, conserved sequences, ligand-protein interactions, and binding energy using molecular docking and MMGBSA.
Main Results:
- Molecular docking identified analogues with significant binding affinity to ERα.
- Molecular dynamics simulations confirmed system stability and residue flexibility for ligand interaction.
- MMGBSA analysis revealed favorable binding energies and identified key contributing residues (Glu353, Leu346, Leu387, Arg394).
Conclusions:
- The study successfully identified novel ERα analogues with potential for breast cancer treatment.
- MMGBSA serves as an effective filter in virtual screening, aiding drug discovery for resistant breast cancers.
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