In Silico Discovery of 1,3,4‐Thiadiazole Derivatives as VEGFR‐2 Inhibitors for Breast Cancer Liver Metastasis via QSAR modeling, Molecular Docking, ADMET, and DFT Studies

ABSTRACT Breast cancer liver metastasis (BCLM) represents a highly aggressive stage of breast cancer progression, largely driven by abnormal angiogenesis mediated by vascular endothelial growth factor receptor‐2 (VEGFR‐2). Consequently, inhibition of VEGFR‐2 has emerged as an important therapeutic strategy for suppressing tumor angiogenesis and metastatic progression. In the present study, an integrated ligand‐ and structure‐based drug design approach was employed to identify potential VEGFR‐2 inhibitors based on the 1,3,4‐thiadiazole (1,3,4‐TDA) scaffold. Experimentally reported IC 50 data for 1,3,4‐TDA derivatives against MCF‐7 and HepG2 cancer cell lines were used to develop statistically robust GA‐MLR QSAR models exhibiting strong predictive performance (MCF‐7: R 2 = 0.884–0.919, Q 2 LOO = 0.853–0.891; HepG2: R 2 = 0.808–0.815, Q 2 LOO = 0.767–0.771). Mechanistic interpretation of molecular descriptors revealed key structural features influencing VEGFR‐2 inhibitory activity. Subsequent QSAR‐guided virtual screening of a large PubChem library, combined with drug‐likeness filtering, identified several promising candidates with predicted sub‐micromolar potency. Molecular docking studies against VEGFR‐2 (PDB ID: 4ASD) revealed that PubChem CIDs 24647757 and 59818234 were the best binders, exhibiting high LibDock scores (163.017 and 149.055 kcal/mol), strong binding affinities (−11.7 and −12.4 kcal/mol), and forming stable interactions with key residues (ASP1046, CYS1045, and LYS868) in the ATP‐binding pocket. ADMET and toxicity analyses suggested favorable pharmacokinetic properties and improved safety profiles relative to sorafenib. In addition, density functional theory (DFT) calculations supported the favorable electronic properties of the identified hits. Overall, these findings highlight 1,3,4‐TDA derivatives as promising scaffolds for the development of next‐generation VEGFR‐2 inhibitors targeting breast cancer liver metastasis.

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Journal
Journal of Chemometrics
Published
2026-04-20
DOI
https://doi.org/10.1002/cem.70126
Primary Topic
Computational Drug Discovery Methods
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article
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article

In Silico Discovery of 1,3,4‐Thiadiazole Derivatives as VEGFR‐2 Inhibitors for Breast Cancer Liver Metastasis via QSAR modeling, Molecular Docking, ADMET, and DFT Studies

Jagadish Singh, Balaji Wamanrao Matore, Anjali Murmu, Pragya Gawande et al.
Journal of Chemometrics
Computational Drug Discovery Methods
article

In Silico Discovery of 1,3,4‐Thiadiazole Derivatives as VEGFR‐2 Inhibitors for Breast Cancer Liver Metastasis via QSAR modeling, Molecular Docking, ADMET, and DFT Studies

Jagadish Singh, Balaji Wamanrao Matore, Anjali Murmu, Pragya Gawande, Partha Pratim Roy
article en

Abstract

ABSTRACT Breast cancer liver metastasis (BCLM) represents a highly aggressive stage of breast cancer progression, largely driven by abnormal angiogenesis mediated by vascular endothelial growth factor receptor‐2 (VEGFR‐2). Consequently, inhibition of VEGFR‐2 has emerged as an important therapeutic strategy for suppressing tumor angiogenesis and metastatic progression. In the present study, an integrated ligand‐ and structure‐based drug design approach was employed to identify potential VEGFR‐2 inhibitors based on the 1,3,4‐thiadiazole (1,3,4‐TDA) scaffold. Experimentally reported IC 50 data for 1,3,4‐TDA derivatives against MCF‐7 and HepG2 cancer cell lines were used to develop statistically robust GA‐MLR QSAR models exhibiting strong predictive performance (MCF‐7: R 2 = 0.884–0.919, Q 2 LOO = 0.853–0.891; HepG2: R 2 = 0.808–0.815, Q 2 LOO = 0.767–0.771). Mechanistic interpretation of molecular descriptors revealed key structural features influencing VEGFR‐2 inhibitory activity. Subsequent QSAR‐guided virtual screening of a large PubChem library, combined with drug‐likeness filtering, identified several promising candidates with predicted sub‐micromolar potency. Molecular docking studies against VEGFR‐2 (PDB ID: 4ASD) revealed that PubChem CIDs 24647757 and 59818234 were the best binders, exhibiting high LibDock scores (163.017 and 149.055 kcal/mol), strong binding affinities (−11.7 and −12.4 kcal/mol), and forming stable interactions with key residues (ASP1046, CYS1045, and LYS868) in the ATP‐binding pocket. ADMET and toxicity analyses suggested favorable pharmacokinetic properties and improved safety profiles relative to sorafenib. In addition, density functional theory (DFT) calculations supported the favorable electronic properties of the identified hits. Overall, these findings highlight 1,3,4‐TDA derivatives as promising scaffolds for the development of next‐generation VEGFR‐2 inhibitors targeting breast cancer liver metastasis.

Journal of ChemometricsVol. 40(5)
Guru Ghasidas Vishwavidyalaya (IN)
Good health and well-being
Openalex Percentile: Top 11%
Computational Drug Discovery Methods
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