Dataset Information

In Silico Screening of Natural Flavonoids against 3-Chymotrypsin-like Protease of SARS-CoV-2 Using Machine Learning and Molecular Modeling.

ABSTRACT: The "Long-COVID syndrome" has posed significant challenges due to a lack of validated therapeutic options. We developed a novel multi-step virtual screening strategy to reliably identify inhibitors against 3-chymotrypsin-like protease of SARS-CoV-2 from abundant flavonoids, which represents a promising source of antiviral and immune-boosting nutrients. We identified 57 interacting residues as contributors to the protein-ligand binding pocket. Their energy interaction profiles constituted the input features for Machine Learning (ML) models. The consensus of 25 classifiers trained using various ML algorithms attained 93.9% accuracy and a 6.4% false-positive-rate. The consensus of 10 regression models for binding energy prediction also achieved a low root-mean-square error of 1.18 kcal/mol. We screened out 120 flavonoid hits first and retained 50 drug-like hits after predefined ADMET filtering to ensure bioavailability and safety profiles. Furthermore, molecular dynamics simulations prioritized nine bioactive flavonoids as promising anti-SARS-CoV-2 agents exhibiting both high structural stability (root-mean-square deviation < 5 Å for 218 ns) and low MM/PBSA binding free energy (<-6 kcal/mol). Among them, KB-2 (PubChem-CID, 14630497) and 9-O-Methylglyceofuran (PubChem-CID, 44257401) displayed excellent binding affinity and desirable pharmacokinetic capabilities. These compounds have great potential to serve as oral nutraceuticals with therapeutic and prophylactic properties as care strategies for patients with long-COVID syndrome.

SUBMITTER: Cai L

PROVIDER: S-EPMC10745665 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

In Silico Screening of Natural Flavonoids against 3-Chymotrypsin-like Protease of SARS-CoV-2 Using Machine Learning and Molecular Modeling.

Cai Lianjin L Han Fengyang F Ji Beihong B He Xibing X Wang Luxuan L Niu Taoyu T Zhai Jingchen J Wang Junmei J

Molecules (Basel, Switzerland) 20231210 24

The "Long-COVID syndrome" has posed significant challenges due to a lack of validated therapeutic options. We developed a novel multi-step virtual screening strategy to reliably identify inhibitors against 3-chymotrypsin-like protease of SARS-CoV-2 from abundant flavonoids, which represents a promising source of antiviral and immune-boosting nutrients. We identified 57 interacting residues as contributors to the protein-ligand binding pocket. Their energy interaction profiles constituted the inp ...[more]

PMID: 38138524

Similar Datasets

Project description:Background Inhibition of papain-like protease (PLpro) and 3-chymotrypsin-like protease (3CLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is projected to terminate its replication. Hence, these proteases represent viable therapeutic targets. Methods Sixty-one flavonoids with reported activities against other RNA viruses were selected and docked in PLpro and 3CLpro. Flavonoids with better binding energies compared to reference inhibitors (lopinavir and ritonavir) in their interaction with PLpro and 3CLpro were selected for drug-likeness and ADMET analysis. The best representative flavonoid for each protease from the ADMET filtering analysis was subjected to molecular dynamics simulations (MDS) and clustering analysis of the trajectory files. Results Licorice, ugonin M, procyanidin, silymarin, and gallocatechin gallate had better binding energies (-11.8, -10.1, -9.8, -9.7 and -9.6 kcal/mol respectively) with PLpro compared to lopinavir and ritonavir (-9.1 and -8.5 kcal/mol respectively). Also, isonymphaeol B, baicalin, abyssinone II, tomentin A, and apigetrin had better binding energies (-8.7, -8.3, -8.2, -8.1, and -8.1 kcal/mol respectively) with 3CLpro compared to lopinavir and ritonavir (-7.3 and -7.1 kcal/mol respectively). These flavonoids interacted with the proteases via hydrogen and non-hydrogen bonding. Of these flavonoids, silymarin and isonymphaeol B demonstrated most favourable combination of attributes in terms of binding energies, compliance with Lipinski rule for drug-likeness and favourable pharmacokinetics in silico. These two flavonoids exhibited appreciable degree of structural stability, maintaining strong interaction with residues in the different representative clusters selected during the MDS run. Conclusion Silymarin and isonymphaeol B are proposed for further studies as compounds with potential activities against SARS-CoV-2. Supplementary Information The online version contains supplementary material available at 10.1186/s40816-022-00347-y. Highlights • Flavonoids displayed varying affinities for PLpro and 3CLpro of SARS-CoV-2 • They interacted via hydrogen and non-hydrogen bonds; nine and twenty-seven flavonoids had better binding affinities for PLpro and 3CLpro respectively than lopinavir and ritonavir • Silymarin and isonymphaeol B demonstrated most favourable combination of attributes in terms of binding energies, compliance with Lipinski rule for drug-likeness and favourable pharmacokinetics. • Silymarin and isonymphaeol B exhibited appreciable degree of structural stability, maintaining strong interaction with residues in the different representative clusters selected during the MDS run. Supplementary Information The online version contains supplementary material available at 10.1186/s40816-022-00347-y.

Dataset Information

In Silico Screening of Natural Flavonoids against 3-Chymotrypsin-like Protease of SARS-CoV-2 Using Machine Learning and Molecular Modeling.

Publications

In Silico Screening of Natural Flavonoids against 3-Chymotrypsin-like Protease of SARS-CoV-2 Using Machine Learning and Molecular Modeling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets