Potent Bioactive Compounds From Seaweed Waste to Combat Cancer Through Bioinformatics Investigation

Abstract

The seaweed industries generate considerable amounts of waste that must be appropriately managed. This biomass from marine waste is a rich source of high-value bioactive compounds. Thus, this waste can be adequately utilized by recovering the compounds for therapeutic purposes. Histone deacetylases (HDACs) are key epigenetic regulators established as one of the most promising targets for cancer chemotherapy. In the present study, our objective is to find the HDAC 2 inhibitor. We performed top-down in silico methodologies to identify potential HDAC 2 inhibitors by screening compounds from edible seaweed waste. One hundred ninety-three (n = 193) compounds from edible seaweeds were initially screened and filtered with drug-likeness properties using SwissADME. After that, the filtered compounds were followed to further evaluate their binding potential with HDAC 2 protein by using Glide high throughput virtual screening (HTVS), standard precision (SP), extra precision (XP), and quantum polarized ligand docking (QPLD). One compound with higher negative binding energy was selected, and to validate the binding mode and stability of the complex, molecular dynamics (MD) simulations using Desmond were performed. The complex-binding free energy calculation was performed using molecular mechanics-generalized born surface area (MM-GBSA) calculation. Post-MD simulation analyses such as PCA, DCCM, and free energy landscape were also evaluated. The quantum mechanical and electronic properties of the potential bioactive compounds were assessed using the density functional theory (DFT) study. These findings support the use of marine resources like edible seaweed waste for cancer drug development by using its bioactive compounds. The obtained results encourage further in vitro and in vivo research. Our in silico findings show that the compound has a high binding affinity for the catalytic site of the HDAC 2 protein and has drug-likeness properties, and can be utilized in drug development against cancer.

Keywords: HDAC 2; MM-GBSA; molecular docking; molecular dynamics simulation; seaweed.

Figure 1

Flowchart of the virtual screening workflow for identification of prospective HDAC 2 inhibitor from edible seaweed.

Figure 2

(A) 2D molecular interactions and (B) 3D interactions in the active site of best-docked compound, cinnamyl dihydrocinnamate (CMNPD5348) with HDAC 2 protein after QPLD docking.

Figure 3

MD simulation analysis of cinnamyl dihydrocinnamate (CMNPD5348) in complex with HDAC 2 during 100 ns MD simulation time (A) Plot of root mean square deviations (RMSD) (protein RMSD (C-α atom of HDAC 2 protein) is shown in gray while RMSD of cinnamyl dihydrocinnamate are shown in red) (B) plot of root mean square fluctuations (RMSF) values (C) plot of ligand interaction in the binding cavity and (D) plot of the number of hydrogen bonding interactions.

Figure 4

MD simulation analysis of cinnamyl dihydrocinnamate (CMNPD5348) in a complex with HDAC 2 during 100 ns MD simulation time (A) stacked bar chart plot of protein–ligand contact analysis. Abscissa represents the amino acid number and ordinate represents interactions fraction (B) analysis of total contacts timeline analysis of MD trajectory. Darker shades correspond to a higher number of contacts.

Figure 5

Analysis of the torsional degree of freedom for the rotatable bonds present in cinnamyl dihydrocinnamate (CMNPD5348) during 100 ns of MD simulation.

Figure 6

Free energy landscape displaying the achievement of global minima (ΔG, kJ/mol) of HDAC 2 in the presence of cinnamyl dihydrocinnamate (CMNPD5348) concerning their RMSD (Å) and radius of gyration (Rg, Å).

Figure 7

Principal component analysis (PCA) of cinnamyl dihydrocinnamate (CMNPD5348) in complex with HDAC 2 displaying (A) PC1 and PC2, (B) PC2 and PC3, (C) PC8 and PC9, and (D) PC9 and PC10 for 100 ns simulation trajectories.

Figure 8

(A) Dynamic cross correlation matrix (DCCM) and (B) correlated amino acids conformed into secondary structural domains (colored; blue) and non-correlated domains (green) of cinnamyl dihydrocinnamate (CMNPD5348) in complex with HDAC 2 from MD simulation trajectories.

Figure 9

(A) HOMO, LUMO and (B) MESP of cinnamyl dihydrocinnamate (CMNPD5348).