QSAR-Based Hansch Modelling and Molecular Docking Studies of Thiophene Derivatives Against Microbial Targets

Thiophene, a sulfur-containing five-membered heterocyclic compound (C₄H₄S), has emerged as a versatile scaffold in medicinal chemistry owing to its chemical stability, electronic properties, and structural adaptability. Numerous thiophene derivatives have demonstrated diverse pharmacological activities, including antimicrobial, antifungal, antiviral, anticancer, and anti-inflammatory effects, making thiophene an attractive framework for rational drug design. In the present investigation, eighteen thiophene derivatives were subjected to 2D-QSAR analysis and molecular docking studies to evaluate their antimicrobial potential and establish correlations between structural features and biological activity. A range of molecular descriptors—lipophilicity, electronic, steric, and topological parameters—were calculated and incorporated into Hansch-based QSAR models. Statistically validated equations were generated for Salmonella typhi, Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Aspergillus niger, and Candida albicans. The models revealed that lipophilicity (LogP) and solubility (LogS) were critical determinants of antimicrobial activity, with balanced hydrophilic–lipophilic properties enhancing microbial cell penetration. Electronic and steric factors further influenced ligand–target interactions, underscoring the importance of substituent effects. Docking studies were performed against transferase (PDB ID: 1IYL) and oxidoreductase (PDB ID: 3FYV) to assess binding affinities. Compounds C15 and C16 exhibited superior docking scores (-9.761 and -7.145 kcal/mol, respectively), outperforming reference drugs cefadoxil and fluconazole. Additional compounds, such as C3 and C12, also demonstrated strong binding against transferase, while C9 and C15 showed enhanced activity against oxidoreductase. These findings highlight the potential of thiophene derivatives as lead candidates for antimicrobial drug development. The combined application of QSAR and molecular docking provides a reliable computational framework for predicting biological activity, optimizing lead compounds, and reducing experimental costs in drug discovery. This integrative approach underscores the relevance of thiophene scaffolds in addressing the global challenge of antimicrobial resistance and offers promising avenues for the design of next-generation therapeutic agents.