Prediction of dual NF-?B/I?B inhibitors using an integrative in-<i>silico</i> approaches

Abstract

Multiple lines of evidence indicate that the NF-kappa B signaling pathway plays a pivotal role in carcinogenesis; activation of NF-kappa B in cancer increases cell proliferation and suppresses apoptosis, both of which define tumor mass development. Inhibiting NF-kappa B leads to tumor suppression by blocking the IKK-alpha/beta enzymes, thus inhibiting its translocation. Furthermore, protecting p65 from acetylation and phosphorylation inhibits NF-kappa B through its active site. Some small molecules are assumed to inhibit NF-kappa B and I kappa B function separately. This study took one of the previously reported NF-kappa B inhibitors (compound D4) as a promising lead and predicted some dual NF-kappa B and I kappa B inhibitors. We performed a virtual screening (VS) workflow on a library with 186,146 compounds with 75 similarity to compound D4 on both NF-kappa B and I kappa B 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-kappa B and I kappa B 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 CID₄₉₆₉ 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-kappa B/I kappa B proteins. Consequently, the presented computational approaches could be used for designing promising anti-cancer agents.