Prediction of dual NF-κB/IκB inhibitors using an integrative in-silico approaches

Abstract

Multiple lines of evidence indicate that the NF-κB signaling pathway plays a pivotal role in carcinogenesis; activation of NF-κB in cancer increases cell proliferation and suppresses apoptosis, both of which define tumor mass development. Inhibiting NF-κB leads to tumor suppression by blocking the IKK-α/β enzymes, thus inhibiting its translocation. Furthermore, protecting p65 from acetylation and phosphorylation inhibits NF-κB through its active site. Some small molecules are assumed to inhibit NF-κB and IκB function separately. This study took one of the previously reported NF-κB inhibitors (compound D4) as a promising lead and predicted some dual NF-κB and IκB inhibitors. We performed a virtual screening (VS) workflow on a library with 186,146 compounds with 75% similarity to compound D4 on both NF-κB and IκB proteins. A total of 186 compounds were extracted from three steps of VS 36 were common in both proteins. These compounds were subjected to the quantum polarized ligand docking to elect potent compounds with the highest binding affinity for NF-κB and IκB proteins. The MM-GBSA method calculates the lowest binding free energy for eight selected compounds. These analyses found three top-ranked compounds for each protein with suitable pharmacokinetics properties and higher in-silico inhibitory ability. In the last screening, compound CID_4969 was introduced to a molecular dynamics (MDs) simulation study as a common inhibitor for both proteins. The MDs confirmed the main interactions between the final elected compound and NF-κB/IκB proteins. Consequently, the presented computational approaches could be used for designing promising anti-cancer agents.

Communicated by Ramaswamy H. Sarma

Keywords:

• NF-κB inhibitor
• IκB inhibitor
• free energy surface analysis
• MM-GBSA binding energy
• QM-polarized ligand docking
• MD simulations

Disclosure statement

The authors declare no conflict of interest, financial or otherwise.

Additional information

Funding

This work was supported by Hormozgan University of Medical Sciences [grant number 970167].