Identification of Pharmacophore Responsible for the JNK3 Enzyme Inhibition using KPLS-based QSAR Analysis.

backgroundThe pharmacophoric approach relies on the theory of possessing ubiquitous chemical functionalities, and carrying a uniform spatial conformation that provides a route to enhanced potency on the same target receptor. JNK3, also known as c-Jun N-terminal kinase 3, is a protein kinase that plays a crucial role in various cellular processes, particularly in the central nervous system (CNS). In this study, a kernel-based partial least square (KPLS)- based Two-dimensional Quantitative structural activity relationship (2D QSAR) model to predict pharmacophores responsible for c-Jun-N-terminal kinase 3 (JNK3) inhibition.

methodsA library of small molecule JNK3 inhibitors was created from the literature, and a predictive model was built using Canvas 2.6.

resultsThe analysis revealed key structural determinants of activity. Compounds with high pIC

conclusionThe present study highlights the significant impact of substituents on molecular activity, with steric effects, particularly on the phenyl ring, playing a dominant role. Favorable contributions are linked to substitutions like hydroxyl, methoxy, and fluorine, while bulky and meta substitutions reduce activity. Functional groups like unsubstituted sulfonamide or free hydrogen in urea are crucial for activity. Insights into steric, electronic, and positional factors, combined with analysis of JNK3 inhibitors, will guide the design of more selective molecules.