Computational Study on Benzofuran Derivatives as Potent Lysine-Specific Demethylase 1 Inhibitors using 3D QSAR, ADMET Prediction, and Molecular Docking

Abstract

Cancer is one of the most serious diseases affecting human health. It has been considered by the World Health Organization (WHO) as one of the main causes of death in the world. For this reason, a set of benzofuran derivatives are studied in silico using the 3D-QSAR, drug-likeness, ADMET properties, and molecular docking The 3D-QSAR study was performed using CoMFA and CoMSIA techniques to generate two reliable 3D-QSAR models and effectively predict the biological activity of new molecules in an efficient manner. The reliability and efficacy of the developed models were validated by the Y-randomisation test internal and external validation. Based on the interesting information obtained from the CoMFA and CoMSIA contour maps, we designed five new moleculesT1-T5. The lysine-specific demethylase 1 (LSD1) inhibitory activities of the newly designed molecules were predicted in silico, and their obtained results show that these molecules have a higher inhibitory activity of LSD1 than the most active synthesized molecule N4. The five designed LSD1 inhibitors were subjected to the drug-likeness and ADMET properties test. The results of this test show that two molecules T4 and T5 are non-toxic and have good pharmacokinetic properties compared to the synthesized molecule N4. The two molecules T4 and T5 chosen for their ADMET properties were analyzed by molecular docking simulation. The obtained results show the two molecules T4 and T5 are more localized and stable in the LSD1 pocket than the molecules N4 The newly designed molecules T4 and T5 were proposed as the best candidates to obtain a better inhibition of LSD1 compared to the synthesized molecule N4. Finally, we have proposed synthetic pathways for the designed molecules.