| Literature DB >> 35431537 |
Precious Ayorinde Akinnusi1, Samuel Olawale Olubode1, Wasiu Adeboye Salaudeen1.
Abstract
Background: The search for ideal drugs with absolute antiviral activity against SARS-CoV-2 is still in place, and attention has been recently drawn to natural products. Several molecular targets have been identified as points of therapeutic intervention. The targets used in this study include SARS-CoV-2 helicase, spike protein, RNA-dependent RNA polymerase, main protease, and human ACE-2. An integrative computer-aided approach, which includes molecular docking, pharmacophore modeling, and pharmacokinetic profiling, was employed to identify anthocyanins with robust multiple antiviral activities against these SARS-CoV-2 targets. Result: Four anthocyanins (Delphinidin 3-O-glucosyl-glucoside, Cyanidin 3-O-glucosyl-rutinoside, Cyanidin 3-(p-coumaroyl)-diglucoside-5-glucoside), and Nasunin) with robust multiple inhibitory interactions were identified from a library of 118 anthocyanins using computer-aided techniques. These compounds exhibited very good binding affinity to the protein targets and moderate pharmacokinetic profiles. However, Cyanidin 3-O-glucosyl-rutinoside is reported to be the most suitable drug candidate with multiple antiviral effects against SARS-CoV-2 due to its good binding affinity to all five protein targets engaged in the study. Conclusions: The anthocyanins reported in this study exhibit robust binding affinities and strong inhibitory molecular interactions with the target proteins and could be well exploited as potential drug candidates with potent multiple antiviral effects against COVID-19.Entities:
Keywords: 3CL protease; ACE-2; ADME/Tox; Anthocyanins; Helicase; Molecular docking; Pharmacophore modeling; RNA-dependent RNA polymerase; SARS-CoV-2
Year: 2022 PMID: 35431537 PMCID: PMC9006501 DOI: 10.1186/s42269-022-00786-0
Source DB: PubMed Journal: Bull Natl Res Cent ISSN: 1110-0591
Docking scores of top-scoring anthocyanins against SARS-CoV-2 targets
| Compounds | SARS-CoV-2 3Cl pro | SARS-CoV-2 | SARS-CoV-2 | SARS-CoV-2 | HUMAN |
|---|---|---|---|---|---|
| C1 | − 12.77 | − 10.75 | − 10.85 | − 6.76 | − 12.18 |
| C2 | − 10.67 | − 10.93 | − 10.10 | − 10.07 | − 13.26 |
| C3 | − 10.54 | − 11.58 | − 13.82 | − 6.10 | − 13.67 |
| C4 | − 7.51 | − 11.72 | − 10.22 | − 7.32 | − 11.42 |
| C5 | − 10.00 | − 7.67 | − 12.73 | − 4.19 | − 12.07 |
| C6 | − 7.69 | − 6.17 | − 8.91 | − 7.61 | − 13.56 |
| C7 | − 8.22 | − 7.59 | − 9.12 | − 7.45 | − 12.25 |
| C8 | − 11.30 | − 9.53 | − 10.88 | − 6.97 | − 13.90 |
| Hydroxychloroquine | − 6.19 | − 4.57 | − 1.47 | − 1.82 | − 6.31 |
| Remdesivir | − 5.88 | − 4.88 | − 6.67 | − 2.16 | − 5.70 |
C1 = Delphinidin 3-O-glucosyl-glucoside, C2 = Cyanidin 3-O-glucosyl-rutinoside, C3 = Cyanidin 3-(p-coumaroyl)-diglucoside-5-glucoside, C4 = Cyanidin 3-O-xylosyl-rutinoside, C5 = Cyanidin 3-(sinapoyl)-diglucoside-5-glucoside, C6 = Petunidin 3-O-rutinoside, C7 = Malvidin 3-O-(6''-caffeoyl-glucoside), C8 = Nasunin
SWISSADME-predicted lipophilicity (Log P) and water solubility (Log Sw)
| Compounds | Consensus Log P | Silicos-IT LogSw | Silicos-IT class |
|---|---|---|---|
| C1 | − 3.18 | 1.46 | Soluble |
| C2 | − 3.68 | 2.12 | Soluble |
| C3 | − 2.85 | 0.65 | Soluble |
| C4 | − 3.53 | 1.68 | Soluble |
| C5 | − 2.81 | 0.5 | Soluble |
| C6 | − 3.23 | 0.28 | Soluble |
| C7 | 0.42 | − 3.23 | Soluble |
| C8 | − 2.59 | 1.05 | Soluble |
C1 = Delphinidin 3-O-glucosyl-glucoside, C2 = Cyanidin 3-O-glucosyl-rutinoside, C3 = Cyanidin 3-(p-coumaroyl)-diglucoside-5-glucoside), C4 = Cyanidin 3-O-xylosyl-rutinoside, C5 = Cyanidin 3-(sinapoyl)-diglucoside-5-glucoside, C6 = Petunidin 3-O-rutinoside, C7 = Malvidin 3-O-(6''-caffeoyl-glucoside), C8 = Nasunin
2D Amino acid interaction of the top-scoring compounds
Drug-likeness and bioavailability
| Compounds | Lipinski #violations | Veber #violations | Bioavailability score |
|---|---|---|---|
| C1 | 3 | 1 | 0.17 |
| C2 | 3 | 1 | 0.17 |
| C3 | 3 | 1 | 0.17 |
| C4 | 3 | 1 | 0.17 |
| C5 | 3 | 2 | 0.17 |
| C6 | 3 | 1 | 0.17 |
| C7 | 3 | 1 | 0.17 |
| C8 | 3 | 2 | 0.17 |
Predicted pharmacokinetic properties of test compounds
| Compounds | BBB permeant | Pgp substrate | CYP1A2 inhibitor | CYP2C19 inhibitor | CYP2C9 inhibitor | CYP2D6 inhibitor | CYP3A4 inhibitor | Log Kp (cm/s) |
|---|---|---|---|---|---|---|---|---|
| C1 | No | No | No | No | No | No | No | − 11.8 |
| C2 | No | Yes | No | No | No | No | No | − 13.12 |
| C3 | No | Yes | No | No | No | No | No | − 12.98 |
| C4 | No | Yes | No | No | No | No | No | − 13.73 |
| C5 | No | Yes | No | No | No | No | No | − 13.39 |
| C6 | No | No | No | No | No | No | No | − 11.84 |
| C7 | No | No | No | No | No | No | No | − 9 |
| C8 | No | No | No | No | No | No | No | − 13.12 |
ProTox-II toxicity prediction
| Compounds | LD50 (mg/kg) | Toxicity class | Hepatotoxicity | Carcinogenicity |
|---|---|---|---|---|
| C1 | 5000 | 5 | – | – |
| C2 | 5000 | 5 | – | – |
| C3 | 5000 | 5 | – | – |
| C4 | 5000 | 5 | – | – |
| C5 | 5000 | 5 | – | – |
| C6 | 5000 | 5 | – | – |
| C7 | 5000 | 5 | – | – |
| C8 | 5000 | 5 | – | – |
C1 = Delphinidin 3-O-glucosyl-glucoside, C2 = Cyanidin 3-O-glucosyl-rutinoside, C3 = Cyanidin 3-(p-coumaroyl)-diglucoside-5-glucoside), C4 = Cyanidin 3-O-xylosyl-rutinoside, C5 = Cyanidin 3-(sinapoyl)-diglucoside-5-glucoside, C6 = Petunidin 3-O-rutinoside, C7 = Malvidin 3-O-(6''-caffeoyl-glucoside), C8 = Nasunin
Fig. 1Structures of reported anthocyanins
Fig. 2Pharmacophore model of top-scoring compounds. A = C1-3Cl protease complex, B = C4-Helicase complex, C = C3-RNA-dependent RNA polymerase complex, D = C2-Spike protein RBD complex, E = C8-Ace 2 complex
Fig. 3Heat map of the docking scores of the top-scoring compounds