Evaluation of 1,3,4-Thiadiazole and 1,3-Thiazolidine-4-One Binary Molecules against the SARS-CoV-2 Receptor: DFT Study, PASS Prediction, ADMET Analysis, Molecular Docking, and ADMET Optimization

This study investigates the stability, reactivity, and antiviral potential of novel 1,3,4-thiadiazole and 1,3-thiazolidine-4-one derivatives using a combination of Density Functional Theory (DFT) calculations and molecular docking. DFT analyses, including molecular electrostatic potential (MEP) mapping, reactivity indices (electronegativity, electrophilic index, softness, and hardness), and frontier molecular orbitals (HOMO-LUMO), were conducted to understand the chemical properties of the main compound. PASS predictions indicated strong activity of these compounds as Mcl-1 antagonists and antivirals. The docking studies, performed using AutoDock Vina v1.1.2 in PyRx 8, evaluated the binding affinities of 21 compounds against SARS-CoV-2 and rhinovirus, comparing them with standard drugs (Lopinavir, Nafamostat, and Remdesivir). The compounds exhibited binding affinities ranging from -6.9 to -8.5 kcal/mol, suggesting notable antiviral activity. Additionally, ADMET analysis (absorption, distribution, metabolism, excretion, and toxicity) was carried out using ADMET-AI and admetSAR 2.0, confirming their drug-like properties and suitability for further medicinal chemistry development.