An insight into pyruvate dehydrogenase kinase (PDHK) inhibition through pharmacophore modeling and QSAR studies

• Inhibitory activity of anilides of (R)-3,3,3-trifluoro-2-hydroxy-2-methylpropionic acid investigated.
• Two hydrogen bond acceptors, one hydrogen bond donor and hydrophobic area at o-position of phenyl ring essential.
• Hydrophobic area should be at specific orientation from H bond donors and acceptors.
• Electron withdrawing groups, preferably those containing hydrogen bond acceptors para to amide group, highly favorable.
• Aliphatic chains containing large number of rotatable bonds, preferably attached to the amine group, also desirable.

Quantitative-Structure-Activity-Relationship (QSAR) studies have been performed on PDHK inhibitors based on anilides of (R)-3,3,3-trifluoro-2-hydroxy-2-methylpropionic acid. A pharmacophore model has also been developed and a predictive atom based 3D-QSAR model for the studied data set has been derived. The obtained 3D-QSAR model scores high on all statistical parameters. The model suggests that a hydrophobic zone plays a crucial role in the activity of the ligands. This zone is occupied by a chlorine atom at the ortho position of the benzene ring in the active ligands. This is followed by statistical analysis of the data to elucidate the most important descriptors governing the inhibitory activity of the dataset. The descriptor set has been selected so as to capture important topological, geometric, electronic, structural and spatial features of the analogs. By using the Genetic Function Approximation (GFA), robust models have been generated. Principal Component Analysis (PCA) has been used to reduce the descriptors to a manageable set. The importance of hydrogen bonding, molecular flexibility with large number of rotatable bonds, hydrophobicity, and electron-withdrawing substituents at the para position of the phenyl ring contribute to the activity. Hierarchical Cluster Analysis (HCA) has been used to divide the dataset into three clusters on the basis of similarity. The same properties as deciphered from PCA are found to contribute to the activity of the compounds in the cluster containing the most active molecules.