AUTHOR=Sinha Siddharth , Goyal Sukriti , Somvanshi Pallavi , Grover Abhinav 

TITLE=Mechanistic Insights into the Binding of Class IIa HDAC Inhibitors toward Spinocerebellar Ataxia Type-2: A 3D-QSAR and Pharmacophore Modeling Approach

JOURNAL=Frontiers in Neuroscience

VOLUME=10

YEAR=2017

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2016.00606

DOI=10.3389/fnins.2016.00606

ISSN=1662-453X

ABSTRACT=<p>Spinocerebellar ataxia (SCA-2) type-2 is a rare neurological disorder among the nine polyglutamine disorders, mainly caused by polyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein. The expanded trinucleotide repeats within the ataxin-2 protein sequesters transcriptional cofactors i.e., CREB-binding protein (CBP), Ataxin-2 binding protein 1 (A2BP1) leading to a state of hypo-acetylation and transcriptional repression. Histone de-acetylases inhibitors (HDACi) have been reported to restore transcriptional balance through inhibition of class IIa HDAC's, that leads to an increased acetylation and transcription as demonstrated through <italic>in-vivo</italic> studies on mouse models of Huntington's. In this study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were used for developing three dimensional (3D) QSAR and pharmacophore models. These models were then employed for screening and selection of anti-ataxia compounds. The chosen QSAR model was observed to be statistically robust with correlation coefficient (<italic>r</italic><sup>2</sup>) value of 0.6774, cross-validated correlation coefficient (<italic>q</italic><sup>2</sup>) of 0.6157 and co-relation coefficient for external test set (<italic>pred</italic>_<italic>r</italic><sup>2</sup>) of 0.7570. A high <italic>F</italic>-test value of 77.7093 signified the robustness of the model. Two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) were selected after a coalesce procedure of pharmacophore based screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulations. The pharmacophore and the 3D-QSAR model generated were further validated for their screening and prediction ability using the enrichment factor (EF), goodness of hit (GH), and receiver operating characteristics (ROC) curve analysis. The compounds SEI and ACI exhibited a docking score of −10.097 and −9.182 kcal/mol, respectively. An evaluation of binding conformation of ligand-bound protein complexes was performed with MD simulations for a time period of 30 ns along with free energy binding calculations using the g_mmpbsa technique. Prediction of inhibitory activities of the two lead compounds SEI (7.53) and ACI (6.84) using the 3D-QSAR model reaffirmed their inhibitory characteristics as potential anti-ataxia compounds.</p>