Natural Compounds as Non-Nucleoside Inhibitors of Zika Virus Polymerase through Integration of In Silico and In Vitro Approaches

Ramos, Paulo Ricardo Pimenta da Silva; Mottin, Melina; Lima, Caroline Sprengel; Assis, Letícia Ribeiro de; Oliveira, Ketllyn Zagato de; Mesquita, Nathalya Cristina de Moraes Roso; Cassani, Natasha Marques; Santos, Igor Andrade; Borba, Joyce Villa Verde Bastos; Costa, Vinícius Alexandre Fiaia; Neves, Bruno J.; Güido, Rafael Victório Carvalho; Oliva, Glaucius; Jardim, Ana Carolina Gomes; Regasini, Luis Octávio; Andrade, Carolina Horta

doi:10.3390/ph15121493

Cited by 8 publications

(3 citation statements)

References 89 publications

(168 reference statements)

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“…These scores were negatively correlated with the reference native ligand. Previous studies with similar in silico approaches on ZIKV-RdRp showed inhibitor compounds with docking scores ranging from −6.13 kcal/mol to −9.20 kcal/mol, which was higher than the top twelve selected compounds in this study [37][38][39]. The docking score of the native ligand was lower than the selected ligand, which suggested a higher strength of binding, but the docking program is a rigid protocol, and, thus, it has limitations in finding the optimum minimum energy state.…”

Section: Virtual Screening and Mm/gbsa (∆G Binding Free Energy)contrasting

confidence: 53%

Investigating the Mechanism of Action of Anti-Dengue Compounds as Potential Binders of Zika Virus RNA-Dependent RNA Polymerase

Alandijany

El-Daly

Tolah

et al. 2023

Viruses

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The World Health Organization (WHO) has designated the Zika virus (ZIKV) as a significant risk to the general public’s health. Currently, there are no vaccinations or medications available to treat or prevent infection with the Zika virus. Thus, it is urgently required to develop a highly efficient therapeutic molecule. In the presented study, a computationally intensive search was carried out to identify potent compounds that have the potential to bind and block the activity of ZIKV NS5 RNA-dependent RNA polymerase (RdRp). The anti-dengue chemical library was subjected to high-throughput virtual screening and MM/GBSA analysis in order to rate the potential candidates. The top three compounds were then chosen. According to the MM/GBSA analysis, compound 127042987 from the database had the highest binding affinity to the protein with a minimum binding free energy of −77.16 kcal/mole. Compound 127042987 had the most stable RMSD trend and the greatest number of hydrogen bond interactions when these chemical complexes were evaluated further under a 100 ns molecular dynamics simulation. Compound 127042987 displayed the best binding free energy (GBind) of −96.50 kcal/mol, surpassing the native ligand binding energy (−66.17 kcal/mole). Thereafter, an MM/GBSA binding free energy study was conducted to validate the stability of selected chemical complexes. Overall, this study illustrated that compound 127042987 showed preferred binding free energies, suggesting a possible inhibitory mechanism against ZIKV-RdRp. As per this study, it was proposed that compound 127042987 could be used as a therapeutic option to prevent Zika virus infection. These compounds need to be tested in experiments for further validation.

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Section: Virtual Screening and Mm/gbsa (∆G Binding Free Energy)contrasting

confidence: 53%

Investigating the Mechanism of Action of Anti-Dengue Compounds as Potential Binders of Zika Virus RNA-Dependent RNA Polymerase

Alandijany

El-Daly

Tolah

et al. 2023

Viruses

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“…Likewise, Singh et al 264 used DockThor to study and evaluate molecules obtained from experimental GC–MS‐screening of crude plant extracts with virtual screening and characterize potential targets. Silva Ramos et al 265 used the DockThor approach to identify potent candidate molecules as inhibitors for the Zika virus NS5 RNA‐dependent RNA‐polymerase.…”

Section: Applicationsmentioning

confidence: 99%

Modern machine‐learning for binding affinity estimation of protein–ligand complexes: Progress, opportunities, and challenges

Harren,

Gutermuth,

Grebner

et al. 2024

WIREs Comput Mol Sci

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Structure‐based drug design is a widely applied approach in the discovery of new lead compounds for known therapeutic targets. In most structure‐based drug design applications, the docking procedure is considered the crucial step. Here, a potential ligand is fitted into the binding site, and a scoring function assesses its binding capability. With the rise of modern machine‐learning in drug discovery, novel scoring functions using machine‐learning techniques achieved significant performance gains in virtual screening and ligand optimization tasks on retrospective data. However, real‐world applications of these methods are still limited. Missing success stories in prospective applications are one reason for this. Additionally, the fast‐evolving nature of the field makes it challenging to assess the advantages of each individual method. This review will highlight recent strides toward improved real world applicability of machine‐learning based scoring, enabling a better understanding of the potential benefits and pitfalls of these functions on a project. Furthermore, a systematic way of classifying machine‐learning based scoring that facilitates comparisons will be presented.This article is categorized under: Data Science > Chemoinformatics Data Science > Artificial Intelligence/Machine Learning Software > Molecular Modeling

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“…Recently, many mechanisms of the antiviral action of QUER were described against several RNA and DNA viruses, including severe acute respiratory syndrome coronavirus 2 [ 5 , 8 , 13 , 19 , 20 ], and other ones were proposed through the integration of in silico approaches [ 13 , 21 ]. Therefore, in this study, we evaluated the antiviral activity of QUER on JUNV multiplication in different cell culture systems at different stages of the viral replication cycle, as well as the direct virucidal activity.…”

Section: Introductionmentioning

confidence: 99%

Effects of the Natural Flavonoid Quercetin on Arenavirus Junín Infection

Lauro

Pelaez

Márquez

et al. 2023

Viruses

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There is no specific chemotherapy approved for the treatment of pathogenic arenaviruses that cause severe hemorrhagic fever (HF) in the population of endemic regions in America and Africa. The present study reports the effects of the natural flavonoid quercetin (QUER) on the infection of A549 and Vero cells with Junín virus (JUNV), agent of the Argentine HF. By infectivity assays, a very effective dose-dependent reduction of JUNV multiplication was shown by cell pretreatment at 2–6 h prior to the infection at non-cytotoxic concentrations, with 50% effective concentration values in the range of 6.1–7.5 µg/mL. QUER was also active by post-infection treatment but with minor efficacy. Mechanistic studies indicated that QUER mainly affected the early steps of virus adsorption and internalization in the multiplication cycle of JUNV. Treatment with QUER blocked the phosphorylation of Akt without changes in the total protein expression, detected by Western blot, and the consequent perturbation of the PI3K/Akt pathway was also associated with the fluorescence redistribution from membrane to cytoplasm of TfR1, the cell receptor recognized by JUNV. Then, it appears that the cellular antiviral state, induced by QUER treatment, leads to the prevention of JUNV entry into the cell.

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Natural Compounds as Non-Nucleoside Inhibitors of Zika Virus Polymerase through Integration of In Silico and In Vitro Approaches

Cited by 8 publications

References 89 publications

Investigating the Mechanism of Action of Anti-Dengue Compounds as Potential Binders of Zika Virus RNA-Dependent RNA Polymerase

Investigating the Mechanism of Action of Anti-Dengue Compounds as Potential Binders of Zika Virus RNA-Dependent RNA Polymerase

Modern machine‐learning for binding affinity estimation of protein–ligand complexes: Progress, opportunities, and challenges

Effects of the Natural Flavonoid Quercetin on Arenavirus Junín Infection

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