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Structure-Activity Relationship Studies Based on 3D-QSAR CoMFA/CoMSIA for Thieno-Pyrimidine Derivatives as Triple
1Yonsei Institute of Pharmaceutical Sciences, College of Pharmacy, Yonsei University, Incheon 21983, Republic of Korea.
Abstract:
Triple-negative breast cancer (TNBC) is defined as a kind of breast cancer that lacks estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptors (HER2). This cancer accounts for 10-15% of all breast cancers and has the features of high invasiveness and metastatic potential. The treatment regimens are still lacking and need to develop novel inhibitors for therapeutic strategies. Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses, based on a series of forty-seven thieno-pyrimidine derivatives, were performed to identify the key structural features for the inhibitory biological activities. The established comparative molecular field analysis (CoMFA) presented a leave-one-out cross-validated correlation coefficient q2 of 0.818 and a determination coefficient r2 of 0.917. In comparative molecular similarity indices analysis (CoMSIA), a q2 of 0.801 and an r2 of 0.897 were exhibited. The predictive capability of these models was confirmed by using external validation and was further validated by the progressive scrambling stability test. From these results of validation, the models were determined to be statistically reliable and robust. This study could provide valuable information for further optimization and design of novel inhibitors against metastatic breast cancer.
Insights
Researchers developed 3D-QSAR models to identify key structural features for novel triple-negative breast cancer (TNBC) inhibitors. These validated models offer insights for designing effective treatments against this aggressive cancer.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Oncology
Background:
- Triple-negative breast cancer (TNBC) is an aggressive subtype lacking ER, PR, and HER2 receptors, accounting for 10-15% of breast cancers.
- TNBC exhibits high invasiveness and metastatic potential, necessitating the development of novel therapeutic strategies and inhibitors.
- Current treatment options for TNBC are limited, highlighting the urgent need for innovative drug discovery approaches.
Purpose of the Study:
- To establish reliable 3D-QSAR models for predicting the inhibitory activity of thieno-pyrimidine derivatives against TNBC.
- To identify critical structural features responsible for the biological activity of these compounds.
- To provide a foundation for the rational design and optimization of novel TNBC inhibitors.
Main Methods:
- Utilized three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses on a series of 47 thieno-pyrimidine derivatives.
- Employed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to build predictive models.
- Validated the models using leave-one-out cross-validation, external validation, and progressive scrambling stability tests.
Main Results:
- The CoMFA model achieved a q² of 0.818 and an r² of 0.917, while the CoMSIA model yielded a q² of 0.801 and an r² of 0.897.
- Both models demonstrated statistical reliability, robustness, and strong predictive capabilities, confirmed through rigorous validation procedures.
- Key structural determinants for inhibitory activity against TNBC were identified, guiding future molecular design.
Conclusions:
- The developed 3D-QSAR models are statistically sound and robust for predicting the inhibitory potential of thieno-pyrimidine derivatives.
- This study provides valuable insights into structure-activity relationships crucial for designing novel and effective inhibitors against metastatic breast cancer.
- The findings can accelerate the development of targeted therapies for triple-negative breast cancer, addressing a significant unmet clinical need.
