Repurposing potential of Ayurvedic medicinal plants derived active principles against SARS-CoV-2 associated target proteins revealed by molecular docking, molecular dynamics and MM-PBSA studies

Abstract

All the plants and their secondary metabolites used in the present study were obtained from Ayurveda, with historical roots in the Indian subcontinent. The selected secondary metabolites have been experimentally validated and reported as potent antiviral agents against genetically-close human viruses. The plants have also been used as a folk medicine to treat cold, cough, asthma, bronchitis, and severe acute respiratory syndrome in India and across the globe since time immemorial. The present study aimed to assess the repurposing possibility of potent antiviral compounds with SARS-CoV-2 target proteins and also with host-specific receptor and activator protease that facilitates the viral entry into the host body. Molecular docking (MDc) was performed to study molecular affinities of antiviral compounds with aforesaid target proteins. The top-scoring conformations identified through docking analysis were further validated by 100 ns molecular dynamic (MD) simulation run. The stability of the conformation was studied in detail by investigating the binding free energy using MM-PBSA method. Finally, the binding affinities of all the compounds were also compared with a reference ligand, remdesivir, against the target protein RdRp. Additionally, pharmacophore features, 3D structure alignment of potent compounds and Bayesian machine learning model were also used to support the MDc and MD simulation. Overall, the study emphasized that curcumin possesses a strong binding ability with host-specific receptors, furin and ACE2. In contrast, gingerol has shown strong interactions with spike protein, and RdRp and quercetin with main protease (M^pro) of SARS-CoV-2. In fact, all these target proteins play an essential role in mediating viral replication, and therefore, compounds targeting aforesaid target proteins are expected to block the viral replication and transcription. Overall, gingerol, curcumin and quercetin own multitarget binding ability that can be used alone or in combination to enhance therapeutic efficacy against COVID-19. The obtained results encourage further in vitro and in vivo investigations and also support the traditional use of antiviral plants preventively.

Keywords: ACE-2; COVID-19; Coronavirus; Furin; Main protease; RdRp, spike protein RBD.

Fig. 1

Chemical structures of potent antiviral compounds identified from Ayurvedic plant sources.

Fig. 2

Analysis of molecular dynamics simulation results. A) Root mean square deviation (RMSD) of backbone atoms of ACE2 in complex with curcumin, gingerol and rosmarinic acid, B) RMSD of backbone atoms of furin in complex with curcumin and quercetin, C) RMSD of backbone atoms of spike protein RBD-ACE2 in complex with gingerol, D) RMSD of backbone atoms of M^pro in complex with quercetin and curcumin.

Fig. 3

Binding free energy analysis from MM-PBSA method over the last 50 ns trajectories. A) The ACE2 complexes with curcumin (orange), gingerol (purple), and rosmarinic acid (green) are represented in different color schemes, B) Furin protein complexes with curcumin (orange) and quercetin (red) are represented in different color schemes, C) Spike RBD-ACE2 in complex with gingerol represented here in purple color, D) The M^pro complexes with quercetin (red) and curcumin (orange) are represented in different color schemes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 4

Analysis of molecular dynamics simulation results. A) Root mean square deviation (RMSD) of backbone atoms of RdRp in complex with remdesivir, gingerol, curcumin, and quercetin B) Binding free energy analysis from MM-PBSA method over the last 50 ns trajectories of RdRp. The complexes are represented in different color schemes with remdesivir (olive), gingerol (purple), curcumin (orange), and quercetin (red). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 5

Binding mode analysis for human ACE2 and furin proteins. A) ACE2 (cyan color) shown in solid ribbon representation in complex with curcumin (orange color), B) The close depiction of active site of ACE2 with curcumin, here active site residues are shown in cyan sticks C) Furin protein (light pink) shown in solid ribbon representation in complex with curcumin (orange color), D) The close depiction of furin bound curcumin complex, background is shown with protein in line ribbon (pink color). Active site interacting residues are shown in pink sticks. Hydrogen bonds are indicated with green dashed lines. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 6

Binding mode analysis for SARS-CoV-2 spike and M^pro protein. A) ACE2 protein is shown in cyan and RBD domain of SARS-CoV-2 is shown in green color solid ribbon representation. B) The close depiction of protein complex displays gingerol (purple color) in stick representation inside the spike protein RBD active site. Protein in the background is shown as ribbon. Active site interacting residues of ACE2 protein are shown in cyan sticks whereas, RBD domain active site residues are shown in green sticks. C) M^pro (light purple color) shown in solid ribbon representation bound with quercetin, D) The close depiction of protein displays quercetin (red color) in stick representation inside the M^pro active site. Protein in the background is shown as ribbon (light purple color). Active site interacting residues are shown in purple sticks. Hydrogen bonds are indicated with green dashed lines. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 7

Binding mode analysis for SARS-CoV-2 RdRp protein. A) RdRp protein is shown in peach color solid ribbon representation. B) The close depiction of protein complex displays remdesivir (olive color) in stick representation inside the RdRp active site C) RdRp protein is shown in peach color solid ribbon representation. D) The close depiction of protein complex displays gingerol (purple color) in stick representation inside the RdRp active site. Protein in the background is shown as ribbon. Active site interacting residues of RdRp protein are shown in peach sticks whereas. Hydrogen bonds are indicated with green dashed lines. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 8

Pharmacophore features (2D and 3D) of top-ranked compounds (based on MD simulation) predicted using Ligandscout software. The pharmacophore color code is yellow for hydrophobic regions, red for hydrogen acceptors and green for hydrogen donors. 2D Pharmacophore features represent HBA: hydrogen bond acceptor, HBD: hydrogen bond donor, AR: aryl, NI: negative ionizable and H: hydrophobic center. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 9

PharmaGist based ligands superimposition and determination of pivot molecule (key structure). Curcumin, gingerol and quercetin showed structural similarity with high align score and hence may be able to bind SARS-CoV-2 associated target proteins more efficiently than others.

Fig. 10

A Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with ACE-2 target protein. B Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with SARS-CoV-2 spike protein. C Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with SARS-CoV-2 main protease.

Fig. 10

A Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with ACE-2 target protein. B Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with SARS-CoV-2 spike protein. C Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with SARS-CoV-2 main protease.

Fig. 10

A Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with ACE-2 target protein. B Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with SARS-CoV-2 spike protein. C Assay Central Visualization. A) Machine learning model performance summary of a Bayesian (left) and Random Forest (right) algorithms. Bayesian machine learning models using ECFP6 fingerprint was used for scoring and selecting compounds having potent binding affinity with SARS-CoV-2 main protease.