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Metabologenomics approach to the discovery of novel compounds from Streptomyces sp. GMR22 as anti-SARS-CoV-2 drugs.

ABSTRACT: COVID-19 is spreading rapidly yet there is no clinically proven drug available now. Soil-derived Streptomyces sp. GMR22 has a large genome size (11.4 Mbp) and a huge BGCs (Biosynthetic Gene Clusters) encoding secondary metabolites. This bacterium is a potential source for producing a wide variety of compounds which are able to block SARS-CoV-2, the causative agent of COVID-19. This study aimed to predict the secondary metabolites of Streptomyces sp. GMR22 and to evaluate the ability as SARS-CoV-2 inhibitor. The AntiSMASH 5.0 was used for genome mining analysis and targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) was used for metabolite analysis. In silico molecular docking was performed on important target proteins of SARS-CoV-2 i.e., spike protein (PDB ID: 6LXT), Receptor Binding Domain (RBD)-ACE2 (Angiotensin-Converting Enzyme 2) (PDB ID: 6VW1), 3CLpro (3-chymotrypsin-like protease) (PDB ID: 6M2N), and RdRp (RNA-dependent RNA polymerase) (PDB ID: 6M71). Two compounds from GMR22 extract, echoside A and echoside B were confirmed by targeted LC-HRMS and potential as SARS-CoV-2 inhibitor. Echoside A and echoside B showed higher docking score than remdesivir as COVID-19 drug on four target proteins, i.e., spike protein (-7.9 kcal/mol and -7.8 kcal/mol), RBD-ACE2 (-7.5 kcal/mol and -8.2 kcal/mol), 3CLpro (-8.4 kcal/mol and -9.4 kcal/mol) and RdRp (-7.3 kcal/mol and -8.0 kcal/mol). A combination of genome mining and metabolomic approaches can be used as integrated strategy to elucidate the potential of GMR22 as a resource in the discovery of anti-COVID -19 compound.

SUBMITTER: Melinda YN

PROVIDER: S-EPMC8560767 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, or 2019-nCoV), there is an urgent need to identify therapeutics that are effective against COVID-19 before vaccines are available. Since the current rate of SARS-CoV-2 knowledge acquisition via traditional research methods is not sufficient to match the rapid spread of the virus, novel strategies of drug discovery for SARS-CoV-2 infection are required. Structure-based virtual screening for example relies primarily on docking scores and does not take the importance of key residues into consideration, which may lead to a significantly higher incidence rate of false-positive results. Our novel in silico approach, which overcomes these limitations, can be utilized to quickly evaluate FDA-approved drugs for repurposing and combination, as well as designing new chemical agents with therapeutic potential for COVID-19. As a result, anti-HIV or antiviral drugs (lopinavir, tenofovir disoproxil, fosamprenavir and ganciclovir), antiflu drugs (peramivir and zanamivir) and an anti-HCV drug (sofosbuvir) are predicted to bind to 3CLPro in SARS-CoV-2 with therapeutic potential for COVID-19 infection by our new protocol. In addition, we also propose three antidiabetic drugs (acarbose, glyburide and tolazamide) for the potential treatment of COVID-19. Finally, we apply our new virus chemogenomics knowledgebase platform with the integrated machine-learning computing algorithms to identify the potential drug combinations (e.g. remdesivir+chloroquine), which are congruent with ongoing clinical trials. In addition, another 10 compounds from CAS COVID-19 antiviral candidate compounds dataset are also suggested by Molecular Complex Characterizing System with potential treatment for COVID-19. Our work provides a novel strategy for the repurposing and combinations of drugs in the market and for prediction of chemical candidates with anti-COVID-19 potential.

Project description:The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome virus 2 (SARS-CoV-2) has impacted negatively on public health and socioeconomic status, globally. Although, there are currently no specific drugs approved, several existing drugs are being repurposed, but their successful outcomes are not guaranteed. Therefore, the search for novel therapeutics remains a priority. We screened for inhibitors of the SARS-CoV-2 main protease and the receptor-binding domain of the spike protein from an integrated library of African natural products, compounds generated from machine learning studies and antiviral drugs using AutoDock Vina. The binding mechanisms between the compounds and the proteins were characterized using LigPlot+ and molecular dynamics simulations techniques. The biological activities of the hit compounds were also predicted using a Bayesian-based approach. Six potential bioactive molecules NANPDB2245, NANPDB2403, fusidic acid, ZINC000095486008, ZINC0000556656943 and ZINC001645993538 were identified, all of which had plausible binding mechanisms with both viral receptors. Molecular dynamics simulations, including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations revealed stable protein-ligand complexes with all the compounds having acceptable free binding energies <-15 kJ/mol with each receptor. NANPDB2245, NANPDB2403 and ZINC000095486008 were predicted as antivirals; ZINC000095486008 as a membrane permeability inhibitor; NANPDB2403 as a cell adhesion inhibitor and RNA-directed RNA polymerase inhibitor; and NANPDB2245 as a membrane integrity antagonist. Therefore, they have the potential to inhibit viral entry and replication. These drug-like molecules were predicted to possess attractive pharmacological profiles with negligible toxicity. Novel critical residues identified for both targets could aid in a better understanding of the binding mechanisms and design of fragment-based de novo inhibitors. The compounds are proposed as worthy of further in vitro assaying and as scaffolds for the development of novel SARS-CoV-2 therapeutic molecules.

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Metabologenomics approach to the discovery of novel compounds from Streptomyces sp. GMR22 as anti-SARS-CoV-2 drugs.

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