RESUMEN

Background: A coronavirus identified in 2019, SARS- CoV- 2, has caused a pandemic of respiratory illness, called COVID- 19. Most people with COVID-19 experience mild to moderate symptoms and recover without the need for special treatments. The SARS­CoV­2 RNA­dependent RNA polymerase (RdRp) plays a crucial role in the viral life cycle. The active site of the RdRp is a very accessible region, so targeting this region to study the inhibition of viral replication may be an effective therapeutic approach. For this reason, this study has selected and analysed a series of ligands used as SARS-CoV-2 virus inhibitors, namely: the Zidovudine, Tromantadine, Pyramidine, Oseltamivir, Hydroxychoroquine, Cobicistat, Doravirine (Pifeltro), Dolutegravir, Boceprevir, Indinavir, Truvada, Trizivir, Trifluridine, Sofosbuvir and Zalcitabine. Methods: These ligands were analyzed using molecular docking, Receptor-Based Pharmacophore Modelling. On the other hand, these outcomes were supported with chemical reactivity indices defined within a conceptual density functional theory framework. Results: The results show the conformations with the highest root-mean-square deviation (RMSD), have π-π stacking interaction with residue LEU141, GLN189, GLU166 and GLY143, HIE41, among others. Also was development an electrostatic potential comparison using the global and local reactivity indices. Conclusions: These studies allow the identification of the main stabilizing interactions using the crystal structure of SARS­CoV­2 RNA­dependent RNA polymerase. In this order of ideas, this study provides new insights into these ligands that can be used in the design of new COVID-19 treatments. The studies allowed us to find an explanation supported in the Density Functional Theory about the chemical reactivity and the stabilization in the active site of the ligands.

Asunto(s)

Antivirales , Simulación del Acoplamiento Molecular , SARS-CoV-2 , SARS-CoV-2/efectos de los fármacos , Ligandos , Antivirales/farmacología , Antivirales/química , Humanos , COVID-19/virología , Tratamiento Farmacológico de COVID-19 , ARN Polimerasa Dependiente del ARN/química , ARN Polimerasa Dependiente del ARN/antagonistas & inhibidores , ARN Polimerasa Dependiente del ARN/metabolismo , Pandemias , Betacoronavirus/efectos de los fármacos , Farmacóforo

RESUMEN

Though QSAR was originally developed in the context of physical organic chemistry, it has been applied very extensively to chemicals (drugs) which act on biological systems, in this idea one of the most important QSAR methods is the 3D QSAR model. However, due to the complexity of understanding the results it is necessary to postulate new methodologies to highlight their physical-chemical meaning. In this sense, this work postulates new insights to understand the CoMFA results using molecular quantum similarity and chemical reactivity descriptors within the framework of density functional theory. To obtain these insights a simple theoretical scheme involving quantum similarity (overlap, coulomb operators, their euclidean distances) and chemical reactivity descriptors such as chemical potential (µ), hardness (ɳ), softness (S), electrophilicity (ω), and the Fukui functions, was used to understand the substitution effect. In this sense, this methodology can be applied to analyze the biological activity and the stabilization process in the non-covalent interactions on a particular molecular set taking a reference compound.