Dataset Information

In silico identification of deep-sea fungal alkaloids as potential inhibitors of SARS-CoV-2, Delta and Omicron spikes.

ABSTRACT: Aim: Virtual screening of deep-sea fungal metabolites against SARS-CoV-2 Delta and Omicron spikes as potential antivirals. Materials & methods: Deep-sea fungal alkaloids (n ≥ 150) were evaluated against SARS-CoV-2, Delta and Omicron spikes, using various in silico approaches, including Admet scores, physiochemical properties, molecular docking (MD) and MD simulation (150 ns). Results: The test alkaloids complied with Admet scores and physiochemical properties within acceptable ranges, and followed Lipinski's rule of five. Of these, Cladosporium sphaerospermum-derived cladosin K (tetramate alkaloid) for SARS-CoV-2, Cystobasidium laryngis-derived saphenol (phenazine alkaloid) for Delta and Chaetomium globosum-derived chaetoglobosin E (quinoline alkaloid) for Omicron were identified as potential spike-inhibitors. Conclusion: Our data therefore, strongly warrants further experimental validations of cladosin K, saphenol and chaetoglobosin E, especially against the Omicron and Delta spikes.

SUBMITTER: Alanzi AR

PROVIDER: S-EPMC10615363 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

In silico identification of deep-sea fungal alkaloids as potential inhibitors of SARS-CoV-2, Delta and Omicron spikes.

Alanzi Abdullah R AR Parvez Mohammad K MK Al-Dosari Mohammed S MS

Future virology 20231026

Aim: Virtual screening of deep-sea fungal metabolites against SARS-CoV-2 Delta and Omicron spikes as potential antivirals. Materials & methods: Deep-sea fungal alkaloids (n ≥ 150) were evaluated against SARS-CoV-2, Delta and Omicron spikes, using various in silico approaches, including Admet scores, physiochemical properties, molecular docking (MD) and MD simulation (150 ns). Results: The test alkaloids complied with Admet scores and physiochemical properties within a ...[more]

PMID: 37908844

Similar Datasets

Project description:BACKGROUNDIncreased SARS-CoV-2 reinfection rates have been reported recently, with some locations basing reinfection on a second positive PCR test at least 90 days after initial infection. In this study, we used Johns Hopkins SARS-CoV-2 genomic surveillance data to evaluate the frequency of sequencing-validated, confirmed, and inferred reinfections between March 2020 and July 2022.METHODSPatients who had 2 or more positive SARS-CoV-2 tests in our system, with samples sequenced as a part of our surveillance efforts, were identified as the cohort for our study. SARS-CoV-2 genomes of patients' initial and later samples were compared.RESULTSA total of 755 patients (920 samples) had a positive test at least 90 days after the initial test, with a median time between tests of 377 days. Sequencing was attempted on 231 samples and was successful in 127. Rates of successful sequencing spiked during the Omicron surge; there was a higher median number of days from initial infection in these cases compared with those with failed sequences. A total of 122 (98%) patients showed evidence of reinfection; 45 of these patients had sequence-validated reinfection and 77 had inferred reinfections (later sequencing showed a clade that was not circulating when the patient was initially infected). Of the 45 patients with sequence-validated reinfections, 43 (96%) had reinfections that were caused by the Omicron variant, 41 (91%) were symptomatic, 32 (71%) were vaccinated prior to the second infection, 6 (13%) were immunosuppressed, and only 2 (4%) were hospitalized.CONCLUSIONSequence-validated reinfections increased with the Omicron surge but were generally associated with mild infections.FUNDINGFunding was provided by the Johns Hopkins Center of Excellence in Influenza Research and Surveillance (HHSN272201400007C), CDC (75D30121C11061), Johns Hopkins University President's Fund Research Response, Johns Hopkins Department of Pathology, and the Maryland Department of Health.

Dataset Information

In silico identification of deep-sea fungal alkaloids as potential inhibitors of SARS-CoV-2, Delta and Omicron spikes.

Publications

<i>In silico</i> identification of deep-sea fungal alkaloids as potential inhibitors of SARS-CoV-2, Delta and Omicron spikes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets