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=Volume 10 - 2016

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=Spinocerebellar ataxia (SCA-2)type-2 is one of the rare neurological disorder, mainly caused due topolyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein, and is one among the nine polyglutamine disorders. The mutant ataxin-2 protein having expanded trinucleotide repeat sequesters transcriptional factors 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 In-vivostudies on mouse models of Huntington´s. In present study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were utilized for generating three dimensional QSAR and pharmacophore model for screening and selection of anti-ataxia compounds. Selected QSAR model is statistically robust with correlation coefficient (r2) value of 0.6774, cross validated correlation coefficient (q2) of 0.6157 and co-relation coefficient for external test set (pred_r2) of 0.7570. High F-test value of 77.7093signifies the robustness of the model. We selected two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) selected after a coalesce procedure of pharmacophore placed screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulation. 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 demonstrated docking score of -10.097 and -9.182 kcal/mol, and a stable binding conformation on evaluation with MD simulation for a time period of 30 ns along with free energy binding calculations using the g_mmpbsa technique. High predicted activities of two 7.53 and 6.84 generated using the 3D-QSAR model reaffirmed the inhibitory characteristics of SEI and ACI, leading to their consideration as anti-ataxia compounds.