Computational Studies Of Huntington Protein: Classification & Binding Pattern Determination

Huntington's disease (HD) is a dominantly inherited neurodegenerative disorder characterized by progressive motor deficits, psychiatric deterioration, worsening chorea, cognitive impairment due to neuronal cell loss in the basal ganglia, cerebral cortex, and its fragments interactions with themselves and other biomolecules that results in aggregates , transcriptional repression , oxidative injury and mitochondrial dysfunction . The repeat domain of Huntingtin interacting protein (HIP) 14 (PDB id 3eu9) is used to study the structure based drug design. We made the selection of 50 different small molecules which were screened out through various fixed parameters and applied descriptors to generate the model for molecules that shows the drug likeness properties. We also used a docking algorithm to further find out the most suitable molecule which specifically binds to the HIP and refined this by simulation studies. The classifier is used to validate the training set of molecules with the test set. The interaction energy between the ligand and the protein was calculated and analyzed by using the semiempirical method. The results indicated that protein model can account for the regioselectivity of this protein towards the known ligands and van der Waals interactions were the driving force for the ligand binding. Several key residues were identified to be responsible for the binding of nitrogen containing ligands with HIP. These findings provide useful information for the detailed characterization of the biological roles of HIP and binding pattern determination for the new set of analogues