The investigation of 1,2,4-triazole-chalcone has sparked immense interest due to their promising biological activities. These compounds, labeled 10C-10S, were synthesized and characterized by Jinjing et al., specifically focusing on their potential applications in biological settings, particularly their antiproliferative properties. Strategic exploration by computational chemistry techniques such as DFT calculations, molecular docking, and molecular dynamics with empirical findings proved pivotal in unraveling the multifaceted properties of these organic molecules. Additionally, molecular docking studies were conducted to elucidate the antiproliferative effects and analyze the potential binding modes of the compounds with specific amino acid residues in proteins. Rigorous comparisons between theoretical and experimental results yielded comprehensive insights into the properties of these compounds. We chose two molecules, C (the most active) and E (the least active), which have affinities of -7.689 and -7.526 kcal/mol, respectively, to test how stable they are with the EGFR receptor (PDB entry code: 6Z4B). Molecular dynamics simulations over 100 ns revealed more stable energies, with ΔG_Bind = -25.135 Kcal/mol and ΔG_Bind_vdW = -30.644 Kcal/mol.

While the number of AIDS-related deaths continues to rise, efforts have been made to transform the disease into a manageable chronic condition. HIV protease inhibitors have become central to combination therapy. As a result, these inhibitors have become a major focus of anti-HIV drug development. This research takes a data-driven approach to drug development through the use of quantitative structure-activity relationship (QSAR) analysis. A dataset of 450 anti-HIV drugs was used to construct and validate models. Using extensive validation methods and various machine learning algorithms, the results clearly showed that the "ET" regression outperformed the other models (“XGB”, “LGBM”, “DT”, “RF”, “GB”, “Bag”, and “HGB”) in terms of goodness of fit, predictivity, generalizability, and model robustness. Promising compounds were subjected to molecular docking and molecular dynamics simulation, resulting in drugs with favourable pharmacokinetic and pharmacodynamic properties that consistently interact with the therapeutic target.

In the current study, the compound 4,4-dimethoxychalcone (DMC) was structurally studied and analyzed by in silico approach against M^pro to investigate its inhibitory potential. The molecular structure of the compound was confirmed by the single crystal X-ray diffraction studies. The crystal structure packing is characterized by various hydrogen bonds, C-H…π and π…π stacking. Intermolecular interactions are quantified by Hirshfeld surface analysis and the electronic structure was optimized by DFT calculations; results are in agreement with the experimental studies. Further, DMC was virtually screened against SARS-CoV-2 main protease (PDB-ID: 6LU7) using molecular docking, and molecular dynamics (MD) simulations to identify its inhibitory potential. A significant binding affinity exists between DMC and M^pro with a -6.00 kcal/mol binding energy. A MD simulation of 30ns was carried out; the results predict DMC possessing strong binding affinity and hydrogen-bonding interactions within the active site during the simulation period. Therefore, based on the results of the current investigation, it can be inferred that a DMC molecule may be able to inhibit M^pro of COVID-19.