Background: The development of multitarget drugs capable of simultaneously inhibiting SARS-CoV-2 proteases—3CL^pro and PL^pro—may enhance therapeutic efficacy against COVID-19. Given the historical use of Traditional Chinese Medicine (TCM) in the management of respiratory diseases, phenylethanoid glycosides (PGs) represent an attractive and chemically diverse natural product scaffold for the discovery of antiviral agents. Objectives: This study aimed to identify promising candidates within this class capable of simultaneously inhibiting both target proteases. Methods: The PG structures described in the literature between 1950 and 2020 were gathered and curated to construct a dedicated database, which was subsequently subjected to virtual screening. In silico ADMETox predictions and 2D ligand–protein interaction analyses were then employed to evaluate the identified hit PGs. Ligand stability within the binding sites of the proteases was further assessed using free energy landscape (FEL) and MM/GBSA calculations, while enzymatic inhibition of the commercial PG was evaluated via FRET assays. Results: Virtual screening identified 22 PGs with multitarget potential, predominantly sourced from Asia, followed by the Americas and Europe. The hit compound magnoloside I is found in Magnolia officinalis, a species widely used in TCM for respiratory conditions and officially prescribed during the COVID-19 pandemic. A second hit, calceolarioside B, inhibited more than 90% of the enzymatic activity of both proteases in the FRET assay. Conclusions: Together, these findings highlight phenylethanoid glycosides as promising scaffolds for dual protease inhibition.

Coronavirus disease (COVID-19) pandemic has infected 630 million people and led to 6.59 million deaths worldwide since its outbreak. To control COVID-19 advance, finding new molecules with potential to inhibit viral spread is pivotal. Papain-like protease (PLpro) is one of the most interesting targets of pharmacological inhibition since it is implicated not only in viral replication but also in modulation of host immune response. Natural products are of great interest to the pharmaceutical industry due to their diverse structure and biological activities. The NuBBEDB (Nuclei of Bioassays, Biosynthesis and Ecophysiology of Natural Products Database) is an excellent source of natural products (NPs) from the Brazilian flora. In this study, we performed virtual screening, molecular dynamics, and binding energy analyses of the NuBBEDB library to target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) papain-like protease (PLpro), the virus’s protease essential for replication. Among the top-ranked molecules, the indole alkaloids raputindoles A, C, and D emerged as potential SARS-CoV-2 inhibitors, showing significant interactions with the pivotal Beta-Loop-2 (BL2) region, including the catalytic Y268 residue. Notably, raputindole D displayed enhanced stabilization of the BL2 region, while raputindole C exhibited superior overall stability. These in silico findings suggest that raputindoles, especially D, might offer therapeutic value against COVID-19, laying the groundwork for further experimental evaluations.

O desenvolvimento de fármacos demanda tempo e recursos financeiros devido às muitas fases experimentais envolvidas no processo. Com a evolução tecnológica, a utilização de ferramentas de bioinformática possibilitou a otimização de etapas como a triagem de um grande número de compostos e avaliação de propriedades farmacocinéticas e toxicológicas. Atualmente, a predição dos parâmetros de Absorção, Distribuição, Metabolismo, Excreção e Toxicidade (ADMETox) pode ser realizada através de programas computacionais e servidores web. No presente trabalho, serão esclarecidos alguns conceitos relacionados à farmacocinética, além da exemplificação de preditores disponíveis e algumas de suas funcionalidades.

As etapas de preparação do docking molecular são de extrema importância para obtenção de resultados fidedignos. Esta metodologia pode ser empregada de diversas maneiras, sendo uma delas a triagem virtual de substâncias que tem como finalidade filtrar grandes bibliotecas de compostos. Assim, o ajuste correto de parâmetros, como o provável estado de protonação dos grupamentos funcionais das moléculas, têm impacto na fidelidade do resultado das simulações de {docking. Neste artigo, serão apresentados os parâmetros de docking para a preparação do sistema. E também a comparação entre um sistema que obedece aos parâmetros de preparação e outro sem ajustes, com a finalidade de esclarecer a influência de cada etapa.

A técnica de virtual screening (VS) tornou-se uma ferramenta importante para identificação de potenciais fármacos ou novos usos de fármacos já aprovados. Dentre as vantagens, a diminuição dos custos no processo de desenvolvimento de fármacos torna a ferramenta extremamente atrativa, uma vez que, são realizadas simulações computacionais da interação entre moléculas. Neste tutorial, será apresentado uma metodologia para VS com o banco de dados Food and Drug Administration (FDA) e o programa gratuito de docking molecular Autodock Vina.