3D QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIP DESIGNING AND MOLECULAR DOCKING STUDY OF NOVEL THIADIAZOLE DERIVATIVES AS A POTENTIAL ANTI-CANCER AGENT

Abstract

Objective: Melanoma, which arises from uncontrolled melanocyte growth, can be treated with surgery in the early stages but poses challenges in advanced cases. This study used 3D quantitative structure–activity relationship (3D QSAR) and docking methods to evaluate 51 molecules and to identify compounds with significant binding affinity to BRAF protein. The objective of this study is to design and evaluate novel thiadiazole derivatives as potential anti-cancer agents using a combination of 3D-QSAR modeling and molecular docking studies.

Methods: The study employs a 3D QSAR approach to analyze the inhibitory activity of 51 selected molecules against BRAF, a key target in cancer research. The methodology is structured as follows. A total of 51 molecules were retrieved from the literature based on their documented inhibitory activity against BRAF. These molecules were curated and preprocessed to ensure consistency and accuracy for further computational analysis. Molecular descriptors, which quantitatively represent molecular properties, were generated to facilitate the QSAR modeling process. These descriptors were essential for establishing a correlation between molecular features and biological activity. The Schrödinger software suite was employed to conduct the 3D QSAR analysis. The model was built using ligand-based and structure-based approaches, incorporating spatial and electronic properties to predict activity. To further validate the binding potential of these molecules, PyRx software was utilized for molecular docking studies. Docking simulations helped assess the binding interactions between the molecules and the BRAF protein, offering insights into potential drug-receptor affinity. This methodology allows for the identification of key structural features contributing to BRAF inhibition, providing a foundation for the design of more potent inhibitors in future research.

Results: The Gaussian-based QSAR was produced by correlating with the five fields of steric, electrostatic, hydrophobic, hydrogen bond donor (HBD), and hydrogen bond acceptor (HBA) with the aid of PLS with five variables. With a standard error estimate of 0.2 and an F ratio of 80.3, r2cv values of 0.47 and r2 0.93 were obtained. The steric, HBA, hydrophobic, HBD, electrostatic, and field contributions were, in order, 0.29, 0.08, 0.24, 0.18, and 0.188. Based on the structure of this best descriptor, novel 25 thiadiazole derivatives were designed. For these 25 novel molecules, a docking study was performed using PyRx software.

Conclusion: The results of this study indicate that the thiadiazole ring’s (HBD) and (HBA) substituents are crucial to the drug’s BRAF antagonistic action. Good r2 = 0.93 was displayed by the Gaussian models that were developed based on the five field intensities. The docking studies revealed that the derivative IA25 (−9.7 k/cal) showed a similar binding affinity of standard molecule Dabrafenib toward the targeted protein and these molecules showed 2 conventional hydrogen bonds with Asn221 and Phe209 amino acid residues. The remaining compounds showed the docking score range from 8 k/cal to 9.6 k/cal. Based on the docking score 10 molecules are selected for further studies.