Virtual Screening against p50 NF‐κB Transcription Factor for the Identification of Inhibitors of the NF‐κB–DNA Interaction and Expression of NF‐κB Upregulated Genes

Abstract

Virtual screening against NF-kappaB p50 using docking simulations was applied by starting from a three-dimensional (3D) database containing more than 4.6 million commercially available structures. This database was filtered by specifying a subset of commercially available compounds sharing a (2E,Z)-3-(2-hydroxyphenyl)-2-propenoate substructure and relevant druglike properties. Docking to p50 NF-kappaB was performed with a test set of six known inhibitors of NF-kappaB-DNA interactions. In agreement with docking results, the highest-scored compound displayed a high level of inhibitory activity in electrophoretic mobility shift assay (EMSA) experiments (inhibition of NF-kappaB-DNA interactions) and on biological functions dependent on NF-kappaB activity (inhibition of IL-8 gene expression in cystic fibrosis IB3-1 cells). We found that this in silico screening approach is suitable for the identification of low-molecular-weight compounds that inhibit NF-kappaB-DNA interactions and NF-kappaB-dependent functions. Information deduced from the discovery of the new lead compound and its binding mode could result in further lead optimization resulting in more potent NF-kappaB inhibitors.

Virtual screening against nuclear factor κB (NF-κB) of a focus library: Identification of bioactive furocoumarin derivatives inhibiting NF-κB dependent biological functions involved in cystic fibrosis

“…Docking simulations to p50 NF-jB were performed with a test set of six known inhibitors of NF-jB/DNA interactions. 18,19 In agreement with docking results, the highest-scored compound (compound 1, see Fig. 1) displayed a high level of inhibitory activity in electrophoretic mobility shift assay (EMSA) experiments (inhibition of NF-jB/DNA interactions) 20,21 and on biological functions dependent on NF-jB activity (inhibition of IL-8 gene expression in cystic fibrosis IB3-1 cells).…”

“…1) displayed a high level of inhibitory activity in electrophoretic mobility shift assay (EMSA) experiments (inhibition of NF-jB/DNA interactions) 20,21 and on biological functions dependent on NF-jB activity (inhibition of IL-8 gene expression in cystic fibrosis IB3-1 cells). 15,22 We demonstrated that this in silico screening approach is suitable for the identification of low-molecular-weight compounds that inhibit NF-jB/DNA interactions and NF-jB-dependent functions 19 , confirming a previously published study. 18 This and similar approaches are relevant in medicinal chemistry, as information deduced from the discovery of new lead compounds and their binding mode could result in further lead optimization resulting in more potent NF-jB inhibitors.…”

“…18 This and similar approaches are relevant in medicinal chemistry, as information deduced from the discovery of new lead compounds and their binding mode could result in further lead optimization resulting in more potent NF-jB inhibitors. 18,19 In this respect, the VS strategy is one of the most promising in the field of the discovery of novel bioactive compounds, as recently reviewed. 23 Interestingly, the most active compound of our study resulted to be a furocoumarin analogue, with a cyclopentane ring instead of furan function.…”

“…23 Interestingly, the most active compound of our study resulted to be a furocoumarin analogue, with a cyclopentane ring instead of furan function. 19 Therefore, in the present study we constructed a focus library of differently substituted furocoumarins and analogues for an in silico screening against NF-jB, with the aim of finding more potent NF-jB inhibitors.…”

“…15 In addition to direct screening, we have recently reported the possible use of a structured-based VS procedure to identify possible NF-jB binders. 18,19 In this study, VS against NF-jB p50 using docking simulations was applied by starting from a three-dimensional (3D) database containing more than 4.6 million commercially available structures. This database was filtered by specifying a subset of commercially available compounds sharing a (2E,Z)-3-(2-hydroxyphenyl)-2-propenoate substructure and relevant drug like properties.…”