Title:Synthesis, Molecular Docking, and 2D-QSAR Modeling of Quinoxaline
Derivatives as Potent Anticancer Agents against Triple-negative Breast
Cancer
Volume: 22
Issue: 10
Author(s): Tanu Kaushal, Sana Khan, Kaneez Fatima, Suaib Luqman, Feroz Khan*Arvind Singh Negi*
Affiliation:
- Computational Biology Unit, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIRCIMAP),
Lucknow, 226015, (U.P.), India
- Academy of Scientific and Innovative Research
(AcSIR), Ghaziabad, 201002, (U.P.), India
- Medicinal Chemistry Department, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP), Lucknow,
226015, (U.P.), India
- Academy of Scientific and Innovative Research
(AcSIR), Ghaziabad, 201002, (U.P.), India
Keywords:
Breast cancer, Molecular Docking, QSAR, Multiple Linear Regression Modeling, Anti-cancer agents, Triplenegative breast cancer.
Abstract:
Background: Breast carcinomas aka triple-negative breast cancers (TNBC) are one of
the most complex and aggressive forms of cancers in females. Recently, studies have shown that
these carcinomas are resistant to hormone-targeted therapies, which makes it a priority to search for
effective and potential anticancer drugs. The present study aimed to synthesize and develop the 2Dquantitative
structural activity relationship model (QSAR) of quinoxaline derivatives as a potential
anticancer agent.
Methods: Quinoxaline derivatives were designed and synthesized (8a-8i and 9a-9d) and the 2DQSAR
model against TNBC was developed using VLife MDS v4.4. The anticancer activity was investigated
against the TNBC MDA-MB-231 cell line using an MTT cytotoxicity assay. Molecular
docking studies along with the estimation of ADMET parameters were done using Discovery Studio.
The most potent compound was docked against the β-tubulin protein target (PDB: 4O2B), using
the Autodock Vina v0.8 program.
Results: Eleven derivatives of quinoxaline were designed and synthesized (8a-8i and 9a-9d) and a
2D-QSAR model was developed against the TNBC MDA-MB231 cell line. The regression coefficient
values for the training set were (r2) 0.78 and (q2) 0.71. Further, external test set regression
(pred_r2) was 0.68. Five molecular descriptors viz., energy dispersive (Epsilon3), protein-coding
gene (T_T_C_6), molecular force field (MMFF_6), most hydrophobic hydrophilic distance (XA),
and Zcomp Dipole were identified. After ADMET, the best analog 8a showed the best activity against
the TNBC cell line. The best-predicted hit '8a' was found to bind within the active site of the β-
tubulin protein target.
Conclusion: The newly synthesized quinoxaline compounds could serve as potent leads for the development
of novel anti-cancer agents against TNBC.