From this test experiment, we decided not to perform blind docking, but supervised dockings instead.
Also in the present study, the computational blind docking method using eHiTS is tested on molecules study group and COX-2 enzyme.
In many docking simulations described in the literature, the approach chosen is blind docking, where the ligand is placed at an initial arbitrary position within the active site of the target receptor, and from there, the docking software seeks to find the best ligand orientation that should correspond to the most negative FEB.
By comparison, for the blind docking, only 16 positions out of the 50 docked structures were observed in the active site, with a rmsd of 1.09 Å.
Computational blind docking of the C-domain to the N-domain of GG-SpaDC was done using the ClusPro50 web server (https://cluspro.bu.edu/).
To assess this possibility, we docked the N-domain (head) and C-domain (tail) of GG-SpaDC (i.e., blind docking) by using the ClusPro protein protein docking tool50.
It is concluded that blind docking can be used for unbiased mapping of the binding patterns of drug candidates.
Blind docking was introduced for the detection of possible binding sites and modes of peptide ligands by scanning the entire surface of protein targets.
In this study, a molecular blind docking (BD) method was used to discover potential mitoNEET LBS and novel ligands, utilizing the program AutoDock Vina (v 1.0.2).
The blind docking results for these compounds show that the compound with quinoline binds with higher affinity than isoquinoline and naphthalene groups.
For the molecular dynamics simulations, we used an Aβ42 pentameric model where the compounds were docked using a blind docking technique.
