Design of Novel IRAK4 Inhibitors Using Molecular Docking, Dynamics Simulation and 3D-QSAR Studies

by Selleckchem | Aug 09 2023

Treatment of several autoimmune diseases and types of cancer has been an intense area of research over the past two decades. Many signaling pathways that regulate innate and/or adaptive immunity, as well as those that induce overexpression or mutation of protein kinases, have been targeted for drug discovery. One of the serine/threonine kinases, Interleukin-1 Receptor Associated Kinase 4 (IRAK4) regulates signaling through various Toll-like receptors (TLRs) and interleukin-1 receptor (IL1R). It controls diverse cellular processes including inflammation, apoptosis, and cellular differentiation. MyD88 gain-of-function mutations or overexpression of IRAK4 has been implicated in various types of malignancies such as Waldenström macroglobulinemia, B cell lymphoma, colorectal cancer, pancreatic ductal adenocarcinoma, breast cancer, etc. Moreover, over activation of IRAK4 is also associated with several autoimmune diseases. The significant role of IRAK4 makes it an interesting target for the discovery and development of potent small molecule inhibitors. A few potent IRAK4 inhibitors such as PF-06650833, RA9 and BAY1834845 have recently entered phase I/II clinical trial studies. Nevertheless, there is still a need of selective inhibitors for the treatment of cancer and various autoimmune diseases. A great need for the same intrigued us to perform molecular modeling studies on 4,6-diaminonicotinamide derivatives as IRAK4 inhibitors. We performed molecular docking and dynamics simulation of 50 ns for one of the most active compounds of the dataset. We also carried out MM-PBSA binding free energy calculation to identify the active site residues, interactions of which are contributing to the total binding energy. The final 50 ns conformation of the most active compound was selected to perform dataset alignment in a 3D-QSAR study. Generated RF-CoMFA (q2 = 0.751, ONC = 4, r2 = 0.911) model revealed reasonable statistical results. Overall results of molecular dynamics simulation, MM-PBSA binding free energy calculation and RF-CoMFA model revealed important active site residues of IRAK4 and necessary structural properties of ligand to design more potent IRAK4 inhibitors. We designed few IRAK4 inhibitors based on these results, which possessed higher activity (predicted pIC50) than the most active compounds of the dataset selected for this study. Moreover, ADMET properties of these inhibitors revealed promising results and need to be validated using experimental studies.

Comments:

The research described focuses on the development of small molecule inhibitors targeting Interleukin-1 Receptor Associated Kinase 4 (IRAK4), a serine/threonine kinase that plays a significant role in regulating signaling pathways involved in innate and adaptive immunity, as well as various cellular processes. IRAK4 has been implicated in autoimmune diseases and several types of cancer.

The researchers performed molecular modeling studies using 4,6-diaminonicotinamide derivatives as potential IRAK4 inhibitors. They conducted molecular docking and dynamics simulations, as well as MM-PBSA binding free energy calculations, to identify active site residues and interactions contributing to the binding energy. Additionally, they used the selected conformation from the simulations to perform a dataset alignment in a 3D-QSAR study.

The results of these studies led to the development of a RF-CoMFA model with reasonable statistical results (q2 = 0.751, ONC = 4, r2 = 0.911). This model provided insights into important active site residues of IRAK4 and the necessary structural properties of ligands to design more potent inhibitors.

Based on these findings, the researchers designed several IRAK4 inhibitors with higher predicted activity (pIC50) than the most active compounds in the dataset used for the study. Additionally, the ADMET properties (absorption, distribution, metabolism, excretion, and toxicity) of these inhibitors showed promising results, but experimental validation is still required.

Overall, this research contributes to the ongoing efforts in developing selective IRAK4 inhibitors for the treatment of cancer and autoimmune diseases. The combination of molecular modeling, dynamics simulations, binding free energy calculations, and 3D-QSAR studies provides valuable insights into the interactions between inhibitors and IRAK4, aiding in the design of more effective therapeutic agents.