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Computational analysis of natural product B-Raf inhibitors. | LitMetric

Computational analysis of natural product B-Raf inhibitors.

J Mol Graph Model

Integrated Drug Discovery Center, Department of Pharmaceutical Chemistry, Acharya & BM Reddy College of Pharmacy, Bengaluru, 560 107, Karnataka, India. Electronic address:

Published: January 2023

B-Raf protein is a serine-threonine kinase and an important signal transduction molecule of the MAPK signaling pathway that mediates signals from RAS to MEK, ultimately promoting various essential cellular functions. The B-Raf kinase domain is divided into two subdomains: a small N-terminal lobe and a large C-terminal lobe, with a deep catalytic cleft between them. The N-terminal lobe contains a phosphate-binding loop (P-loop) and nucleotide-binding pocket, while the C-terminal lobe binds the protein substrates and contains the catalytic loop. The ligand pharmacophore was generated by using 17 different natural products and the receptor pharmacophore was generated by using protein structures. The reported natural product B-Raf inhibitors were analyzed according to the pharmacophore analysis (HipHop fit), virtual screening tools by Lipinski's rule of five. Thirteen out of seventeen molecules share the best ligand based pharmacophoric model (HipHop_5). The best receptor based pharmacophoric model came as AADHR. The compounds were docked against the B-Raf receptors (PDB ID: 3OG7, 4XV2, 5C9C). The compound DHSilB with cDOCKER interaction energy of -62.7 kcal/mol, -83.3 kcal/mol, -73.6 kcal/mol as well as the compound DHSilA with cDOCKER interaction energy of -63.9 kcal/mol, -63.2 kcal/mol, -74.7 kcal/mol showed satisfactory interaction with the respective receptors. Finally, the MD simulation was run for 100 ns for the top docked compounds DHSilA and DHSilB with the B-Raf proteins (PDB ID: 3OG7, 4XV2 and 5C9C). After the MD simulation run for 100 ns, the ligand 2,3-dehydrosilybin A (DHSilA) was found to be more stable in terms of the trajectories of RMSD, RMSF, Rg and H-bonds.

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http://dx.doi.org/10.1016/j.jmgm.2022.108340DOI Listing

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