Dataset Information

In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition.

ABSTRACT: The COVID-19 pandemic emerged in 2019, bringing with it the need for greater stores of effective antiviral drugs. This paper deals with the conformation-independent, QSAR model, developed by employing the Monte Carlo optimization method, as well as molecular graphs and the SMILES notation-based descriptors for the purpose of modeling the SARS-CoV-3CLpro enzyme inhibition. The main purpose was developing a reproducible model involving easy interpretation, utilized for a quick prediction of the inhibitory activity of SAR-CoV-3CLpro. The following statistical parameters were present in the best-developed QSAR model: (training set) R ² = 0.9314, Q ² = 0.9271; (test set) R ² = 0.9243, Q ² = 0.8986. Molecular fragments, defined as SMILES notation descriptors, that have a positive and negative impact on 3CLpro inhibition were identified on the basis of the results obtained for structural indicators, and were applied to the computer-aided design of five new compounds with (4-methoxyphenyl)[2-(methylsulfanyl)-6,7-dihydro-1H-[1,4]dioxino[2,3-f]benzimidazol-1-yl]methanone as a template molecule. Molecular docking studies were used to examine the potential inhibition effect of designed molecules on SARS-CoV-3CLpro enzyme inhibition and obtained results have high correlation with the QSAR modeling results. In addition, the interactions between the designed molecules and amino acids from the 3CLpro active site were determined, and the energies they yield were calculated.

Supplementary information

The online version contains supplementary material available at 10.1007/s11696-022-02170-8.

SUBMITTER: Nickcovic VP

PROVIDER: S-EPMC8977062 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition.

Ničkčović Vanja P VP Nikolić Gordana R GR Nedeljković Biserka M BM Mitić Nebojša N Danić Snežana Filipović SF Mitić Jadranka J Marčetić Zoran Z Sokolović Dušan D Veselinović Aleksandar M AM

Chemicke zvesti 20220403 7

The COVID-19 pandemic emerged in 2019, bringing with it the need for greater stores of effective antiviral drugs. This paper deals with the conformation-independent, QSAR model, developed by employing the Monte Carlo optimization method, as well as molecular graphs and the SMILES notation-based descriptors for the purpose of modeling the SARS-CoV-3CLpro enzyme inhibition. The main purpose was developing a reproducible model involving easy interpretation, utilized for a quick prediction of the in ...[more]

PMID: 35400796

Similar Datasets

Project description:Over 10 years have passed since the deadly human coronavirus that causes severe acute respiratory syndrome (SARS-CoV) emerged from the Guangdong Province of China. Despite the fact that the SARS-CoV pandemic infected over 8500 individuals, claimed over 800 lives and cost billions of dollars in economic loss worldwide, there still are no clinically approved antiviral drugs, vaccines or monoclonal antibody therapies to treat SARS-CoV infections. The recent emergence of the deadly human coronavirus that causes Middle East respiratory syndrome (MERS-CoV) is a sobering reminder that new and deadly coronaviruses can emerge at any time with the potential to become pandemics. Therefore, the continued development of therapeutic and prophylactic countermeasures to potentially deadly coronaviruses is warranted. The coronaviral proteases, papain-like protease (PLpro) and 3C-like protease (3CLpro), are attractive antiviral drug targets because they are essential for coronaviral replication. Although the primary function of PLpro and 3CLpro are to process the viral polyprotein in a coordinated manner, PLpro has the additional function of stripping ubiquitin and ISG15 from host-cell proteins to aid coronaviruses in their evasion of the host innate immune responses. Therefore, targeting PLpro with antiviral drugs may have an advantage in not only inhibiting viral replication but also inhibiting the dysregulation of signaling cascades in infected cells that may lead to cell death in surrounding, uninfected cells. This review provides an up-to-date discussion on the SARS-CoV papain-like protease including a brief overview of the SARS-CoV genome and replication followed by a more in-depth discussion on the structure and catalytic mechanism of SARS-CoV PLpro, the multiple cellular functions of SARS-CoV PLpro, the inhibition of SARS-CoV PLpro by small molecule inhibitors, and the prospect of inhibiting papain-like protease from other coronaviruses. This paper forms part of a series of invited articles in Antiviral Research on "From SARS to MERS: 10years of research on highly pathogenic human coronaviruses."

Project description:The biggest challenge in medical management and control of the COVID-19 pandemic is the nonavailability of the treatment molecules. While vaccines and other biotherapeutic products for managing COVID-19 have reached the market, a small-molecule cure is yet to be developed. This is relevant because the cost of production, storage, and ease of distribution of a small-molecule drug are significantly more favorable than those of biologics. In this paper, we present a multicompound approach, where two drug molecules are administered concurrently to offer an effective therapy for COVID-19. The co-action of the two compounds, each derived from natural origins, has been demonstrated against the 3CL protease, already recognized as a potential drug target for inhibiting SARS-CoV-2. The pair of compounds pursued in this study are flavonoid and naphthalene scaffold. Individually, they offer ∼30 to 35% inhibition at 10 μM. Comprehensive docking and molecular dynamics simulations elucidate that these compounds exhibit excellent binding in the process, which however quickly deteriorates, and the ligand is separated from the binding site. This suggests that while the ligands initially bind with the protease, they are unable to maintain it for an extended period. However, the simulation showed that a simultaneous docked complex of both the compounds together with the protein boosts the stronger binding for a sufficient time. The enzyme assay exhibited 97 and 85% inhibition activity when both compounds were used together at 100 and 50 μM, respectively. Later, a multiconcentration assay was used to determine the coinhibitory activity, and it was observed that the compounds have ∼20 to 30% inhibition activity even at lower concentrations of 0.5 and 1 μM. Surface plasmon resonance was used to measure the binding of the compounds, and when used together, the compounds had a 10-fold greater binding affinity. Thus, the results demonstrate a synergistic mechanism between the two compounds that enhances the inhibition activity against SARS-CoV-2 3CL protease.

Dataset Information

In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition.

Supplementary information

Publications

In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets