Natural inhibitors of SARS-CoV-2 main protease: structure based pharmacophore modeling, molecular docking and molecular dynamic simulation studies

Halimi, Mohammad; Bararpour, Parvindokht

doi:10.1007/s00894-022-05286-6

Cited by 9 publications

(5 citation statements)

References 45 publications

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“…Furthermore, the pose score required for molecular dynamics simulation is close to one, indicating a similarity in action to the natural ligand. This alignment in pose score supports the findings from the docking process and suggests that Gar-A exhibits a molecular interaction with HER2 protein akin to its natural ligand [39].…”

Section: Discussionsupporting

confidence: 80%

Unravelling the Interaction Between Garcinisidone-a and Her2 Protein in Breast Cancer: A Computational Study

FURQAN,

DACHRIYANUS,

SUSANTI

et al. 2024

Int J App Pharm

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Objective: One substance found in the leaves of Garcinia cowa Roxb that has anticancer properties is garcinisidone-A. The study aims to simulate the docking of garcinisidone-A (Gar-A), molecular dynamics, and predict the ADME by predicting the binding of the HER2 protein in breast cancer cells and developing new drug candidate options for cancer treatment, often starting with computational analysis. Methods: The research method involves computational utilization of pkCSM applications, Gar-A docking simulation with the HER2 protein using Gnina software version 1.0.2, and molecular dynamics conducted with GROMACS 2022.2 and CHARMMGUI applications. Results: Gar-A has a molecular weight of less than 500, a Log P value of greater than 5, a limited amount of water solubility, a low level of skin permeability, good intestinal permeability, and a Convolutional Neural Network (CNN) pose score on the HER2 protein of 0.6178. It also does not readily cross the blood-brain barrier, and total clearance values indicate rapid elimination via other excretory routes or enzyme metabolism. Gar-A is thought to have interactions with HER2. There are hydrogen bond interactions with amino acids Lys753 and Asp863, carbon-hydrogen bonds with amino acids Leu785, Ser783, Thr862, and alkyl bonds with amino acids Leu726, Leu852, and Ile767. The stability of the Gar-A-substrate interaction could have been more evident during 100 ns molecular dynamics simulation. Conclusion: The physicochemical properties of Gar-A align with Lipinski's rule for drug candidates. ADME predictions indicate good intestinal permeability for Gar-A; however, it suggests it cannot penetrate the blood-brain barrier. The docking results reveal that Gar-A has a value close to one which indicates similar action to its natural ligand and molecular dynamics simulations that Gar-A is less stable. The results illustrate that Gar-A has the potential as a breast anticancer.

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Section: Discussionsupporting

confidence: 80%

Unravelling the Interaction Between Garcinisidone-a and Her2 Protein in Breast Cancer: A Computational Study

FURQAN,

DACHRIYANUS,

SUSANTI

et al. 2024

Int J App Pharm

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“…The structural behaviour of protein‐ligand complexes was evaluated using the GROMACS program (version 2023 with GPU acceleration) on the Linux operating system 27,28 . Input files for MD simulations in GROMACS were generated using the SwissParam server based on the docking results and built with the CHARMM27 force field 29,30 . The initial structure of the Plasmodium falciparum apicoplast DNA polymerase enzyme (7SXL.PDB) with ligands 03, 05, and standard was solved with SPC waters in periodic and cubic boxes.…”

Section: Methodsmentioning

confidence: 99%

“… 27 , 28 Input files for MD simulations in GROMACS were generated using the SwissParam server based on the docking results and built with the CHARMM27 force field. 29 , 30 The initial structure of the Plasmodium falciparum apicoplast DNA polymerase enzyme (7SXL.PDB) with ligands 03, 05, and standard was solved with SPC waters in periodic and cubic boxes. The solvent systems were then subjected to the steepest descent energy minimization process.…”

Section: Methodsmentioning

confidence: 99%

Antimalarial drug discovery against malaria parasites through haplopine modification: An advanced computational approach

Akash,

Abdelkrim,

Bayil

et al. 2023

J Cellular Molecular Medi

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The widespread emergence of antimalarial drug resistance has created a major threat to public health. Malaria is a life‐threatening infectious disease caused by Plasmodium spp., which includes Apicoplast DNA polymerase and Plasmodium falciparum cysteine protease falcipain‐2. These components play a critical role in their life cycle and metabolic pathway, and are involved in the breakdown of erythrocyte hemoglobin in the host, making them promising targets for anti‐malarial drug design. Our current study has been designed to explore the potential inhibitors from haplopine derivatives against these two targets using an in silico approach. A total of nine haplopine derivatives were used to perform molecular docking, and the results revealed that Ligands 03 and 05 showed strong binding affinity compared to the control compound atovaquone. Furthermore, these ligand‐protein complexes underwent molecular dynamics simulations, and the results demonstrated that the complexes maintained strong stability in terms of RMSD (root mean square deviation), RMSF (root mean square fluctuation), and Rg (radius of gyration) over a 100 ns simulation period. Additionally, PCA (principal component analysis) analysis and the dynamic cross‐correlation matrix showed positive outcomes for the protein‐ligand complexes. Moreover, the compounds exhibited no violations of the Lipinski rule, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) predictions yielded positive results without indicating any toxicity. Finally, density functional theory (DFT) and molecular electrostatic potential calculations were conducted, revealing that the mentioned derivatives exhibited better stability and outstanding performance. Overall, this computational approach suggests that these haplopine derivatives could serve as a potential source for developing new, effective antimalarial drugs to combat malaria. However, further in vitro or in vivo studies might be conducted to determine their actual effectiveness.

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“…The chemical features used to construct the hypotheses were the hydrogen bond acceptor (A), hydrogen bond donor (D), and general hydrophobic features (H). 18…”

Section: Methodsmentioning

confidence: 99%

“…15 The pharmacophore models of SARS-CoV-2 M pro inhibitors based on the structure of ligand-receptor complexes have been extracted. [16][17][18][19] However, to the best of our knowledge, to date, there is little information available regarding a highly predictive pharmacophore for SARS-CoV-2 M pro inhibitors. Therefore, we aimed to generate chemical feature-based pharmacophores for SARS-CoV-2 M pro inhibitors to guide the discovery of structurally novel inhibitors with improved efficacy.…”

Section: Introductionmentioning

confidence: 99%

Pharmacophore-Based Virtual Screening of Potential SARS-CoV-2 Main Protease Inhibitors from Library of Natural Products

Wang

Jiang

et al. 2022

Natural Product Communications

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Background: The SARS-CoV-2 main protease (Mpro) is an attractive target for drug discovery. Methods: A pharmacophore model was built using the three-dimensional (3D) pharmacophore generation algorithm HypoGen in Discovery Studio 2019. The best pharmacophore model was selected for validation using a test set of 24 compounds and was used as a 3D query for further screening of an in-house database of natural compounds. Lipinski's rule of five was used to assess the drug-like properties of the hit compounds. The filtered compounds were then subjected to bioactivity evaluations. The active compounds were docked into the active site of the SARS-CoV-2 Mpro crystal structure (PDB ID: 7D1M). Results: A suitable 3D pharmacophore model, Hypo1, was found to be the best model, consisting of four features (one hydrophobic feature, one hydrogen bond donor, and two hydrogen bond acceptors). Pharmacophore-based virtual screening with Hypo1 as the query to search an in-house database of 34 439 natural compounds resulted in 1502 hits. Among these, 255 compounds satisfied Lipinski's rule of five. The highest ranking 10 compounds were selected for further experimental testing, and one hit (W-7) illustrated inhibitory activity against SARS-CoV-2 Mpro with an IC50 value of 75 μM. Docking studies revealed that this hit compound retained the necessary interactions within the active site of SARS-CoV-2 Mpro. Conclusion The identified lead natural compound could provide a scaffold for the further development of SARS-CoV-2 Mpro inhibitors.

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Natural inhibitors of SARS-CoV-2 main protease: structure based pharmacophore modeling, molecular docking and molecular dynamic simulation studies

Cited by 9 publications

References 45 publications

Unravelling the Interaction Between Garcinisidone-a and Her2 Protein in Breast Cancer: A Computational Study

Unravelling the Interaction Between Garcinisidone-a and Her2 Protein in Breast Cancer: A Computational Study

Antimalarial drug discovery against malaria parasites through haplopine modification: An advanced computational approach

Pharmacophore-Based Virtual Screening of Potential SARS-CoV-2 Main Protease Inhibitors from Library of Natural Products

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