Prediction of the Inhibitory Concentration of Hydroxamic Acids by DFT-QSAR Models on Histone Deacetylase 1

Abstract

In order to study the relationship between inhibitory concentration and the molecular structures of hydroxamic acids, a Quantitative Structure Activity Relationship (QSAR) study is applied to a set of 31 histone deacetylase inhibitors (HDACi). This study is performed by using the Principal Component Analysis (PCA) method, the Ascendant Hierarchical Classification (AHC), the Linear Multiple Regression Method (RML) and the nonlinear regression (RMNL). Multivariate statistical analysis allowed to obtain two quantitative models (RML model and RMNL model) by the means of the quantum descriptors those are the dipole moment (μ), the bond length d(C=O) and the valence angles α°(O=C-N) and α°(H-N-O). The RMNL model gives statistically significant results and shows a good predictability R2 = 0.967, S = 0.379 and F = 557.031. The valence angle α°(O=C-N) is the priority descriptor in the prediction of the inhibitory concentration of the studied hydroxamic acids. The obtained results show that geometric descriptors could be useful for predicting the inhibitory concentration of histone deacetylase inhibitors.