Current Computer - Aided Drug Design - Volume 20, Issue 5, 2024

Background: Based on the anti-inflammatory and analgesic activity of hydrazone and phthalimide, a new series of hybrid hydrazone and phthalimide pharmacophores was prepared and evaluated as analgesic agents. Methods: The designed ligands were synthesized by reaction of the appropriate aldehydes and 2- aminophthalimide. Analgesic, cyclooxygenase inhibitory, and cytostatic activity of prepared compounds were measured. Results: All the tested ligands demonstrated significant analgesic activity. Moreover, compounds 3i and 3h were the most potent ligands in the formalin and writhing tests, respectively. Compounds 3g, 3j, and 3l were the most COX-2 selective ligands and ligand 3e was the most potent COX inhibitor with a 0.79 of COX-2 selectivity ratio. The presence of electron-withdrawing moieties with hydrogen bonding ability at the meta position was found to affect the selectivity efficiently, in which compounds 3g, 3l, and 3k showed high COX-2 selectivity, and compound 3k was the most potent one. The cytostatic activity of selected ligands demonstrated that compounds 3e, 3f, 3h, 3k, and 3m showed good analgesic and COX inhibitory activity and were less toxic than the reference drug. Conclusion: High therapeutic index of these ligands is one of the valuable advantages of these compounds.

Computer-aided molecular modeling is a rapidly emerging technology that is being used to accelerate the discovery and design of new drug therapies. It involves the use of computer algorithms and 3D structures of molecules to predict interactions between molecules and their behavior in the body. This has drastically improved the speed and accuracy of drug discovery and design. Additionally, computer-aided molecular modeling has the potential to reduce costs, increase the quality of data, and identify promising targets for drug development. Through the use of sophisticated methods, such as virtual screening, molecular docking, pharmacophore modeling, and quantitative structure-activity relationships, scientists can achieve higher levels of efficacy and safety for new drugs. Moreover, it can be used to understand the activity of known drugs and simplify the process of formulating, optimizing, and predicting the pharmacokinetics of new and existing drugs. In conclusion, computer-aided molecular modeling is an effective tool to rapidly progress drug discovery and design by predicting the interactions between molecules and anticipating the behavior of new drugs in the body.

Background: Ginseng (Panax ginseng) is a herb of medicinal and nutritional importance. Ginseng has been used since ancient times for the treatment of numerous ailments as it has many therapeutic properties. Several phytoconstituents are present in Panax ginseng that possess a variety of beneficial pharmacological properties. Objective: To explore the potential of phytoconstituents of Panax ginseng in the treatment of depression, a molecular modeling technique was utilized targeting monoamine oxidase-A (MAO-A). Methods: A total of sixty-one phytoconstituents of ginseng were drawn with the help of ChemBioDraw Ultra 12.0 software and PDBs for MAO-A enzyme were retrieved from the RCSB PDB database. The prepared ligands were screened for MAO-A properties using the software Molegro Virtual Docker (MVD 2010.4.1.0). All the prepared ligands were evaluated for drug-likeliness properties using Swiss ADME. Results: Among the docking studies of 60 Ginseng phytochemicals including one standard, 15 phytoconstituents with the highest dock score and better binding interactions were selected further for absorption, distribution, metabolism and excretion (ADME) studies. Stachyose (-227.287, 17 interactions), Raffinose (-222.157, 14 interactions), and Ginsenoside Rg1 (-216.593, 10 interactions) were found to possess better interactions as compared to Clorgyline taken as a standard drug. Conclusion: Stachyose was found to be the most potent inhibitor of MAO-A enzyme under investigation and can be a potential lead molecule for the development of newer phytochemical-based treatment of depression.