RESUMEN
Based on the core unit of chloroquine, new types of N-heterocyclic compounds that are fused together have been made. The compounds were put into two groups. In series A, the five-member hetero-rings were directly connected to the core unit, while in series B, the CH2 group was used to make the five-member ring more flexible (series B). Using the Gaussian 09 programme, the DFT method with hybrid correlation functional (B3LYP) and 6-311 (d, p) basis sets were used to figure out how to optimize and measure the quantum chemical properties of molecules. The molecular overeating environment (MOE) programme is used to study molecular docking. The binding of flexible compounds shows that AC8, AC10, AC3, and AC5 have the strongest binding affinities compared to the other candidates, while the rigid molecules ARC10 and ARC6 have the lowest binding affinities. In general, the results of the binding affinity showed that the drugs and receptors being studied might have anti-Covid-19 properties. Likewise, the flexible compounds AC8, AC10, AC3, and AC5 had the lowest Ki values of those made and could be used as a treatment. Our virtual physicochemical evaluation of all compounds in series A and B showed that all of them met the limits for molecular weight, lipophilicity (MLogP 4.15, the octanol-water partition coefficient), and water solubility. In addition to MR, the number of H-bond acceptors and the PSA were both within the acceptable range. It seems that the number of rotatable bonds is the only physicochemical property that separates the compounds in series B. The scores of compounds AC3, AC4, AC7, AC8, AC11, and AC12 are outside the acceptable range when compared to the results of chloroquine as the parent compound. © 2023 by SPC (Sami Publishing Company).
RESUMEN
Due to the urgent need of drugs to control the COVID-19 pandemic, repo-sitioning of already marketed drugs could be a fast and convenient option to identify agents to aid in controlling and treating COVID-19. This work presented a computational work regarding homology modeling and molecular docking of repurposing drugs related to the SARS-CoV-2. We have cre-ated a homology model of the cell surface transmembrane protease serine 2 protein (TMPRSS2) in order to investigate and analyze the interac-tions of already known small-molecules. This study indicates the most active inhibitors, poceprevir, simeprevir and neoandrgrapholide, that can be used further to search for better TMPRSS2 inhibitors. Moreover, we analyzed the most important atomistic connections between these compounds and the modeled protein pockets. This study will focus on TMPRSS2-targeted drugs by comparing the binding mode of approved and experimentally used TMRSS2 inhibitors with other agents with TMPRSS2 inhibitory activity and could potentially inhibit SARS-CoV-2 and therefore could lead to the identification of new agents for further clinical evaluation of SARS-CoV-2 and potential treatment of COVID-19.