An alignment-independent 3D-QSAR study on series of hydroxamic acid-based tumor necrosis factor-alpha converting enzyme inhibitors

Abstract

Grid-independent descriptors are extensively used in 3D quantitative structure-activity relationship (3D-QSAR) studies. These kinds of descriptors represent the spatial arrangement of the atoms in a 3D fashion. In the current study, we have developed a 3D-QSAR model for a set of hydroxamic acid-based derivatives as tumor necrosis factor- converting enzyme (TACE) inhibitors. The generated model revealed the importance of some main moieties in the potency of these compounds. Quinolinyl and hydroxamate moieties have the ability to act as hydrogen bond acceptors and hot spot points. On the other hand, phenyl ring can participate in hydrophobic contacts with the receptor. 3D-QSAR analyses resulted in the partial least squares model of 3 latent variables with internal and external validation yielding q(2) values of 0.66 and 0.73, respectively. The result of the current study can be used in designing of potent TACE inhibitors where inhibition of TACE enzyme is required, such as inflammatory diseases, atherosclerosis, osteoporosis, autoimmune disorders, allograft rejection, and cancer. An alignment-independent 3D-QSAR study was performed on a set of hydroxamate-based derivatives as TNF- converting enzyme (TACE) inhibitors. The generated model revealed the importance of main moieties in the potency of these compounds. The model is capable of predicting the inhibitory activity of compounds with good statistics. The result of this study can be used in designing of potent TACE inhibitors where inhibition of TACE enzyme is required.