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The transcription factor NF-kappaB is a very interesting target molecule for the design on anti-tumor, anti-inflammatory and pro-apoptotic drugs. However, the application of the widely-used molecular docking computational method for the virtual screening of chemical libraries on NF-kappaB is not yet reported in literature. Docking studies on a dataset of 27 molecules from extracts of two different medicinal plants to NF-kappaB-p50 were performed with the purpose of developing a docking protocol fit for the target under study.
We enhanced the simple docking procedure by means of a sort of combined target- and ligand-based drug design approach. Advantages of this combination strategy, based on a similarity parameter for the identification of weak binding chemical entities, are illustrated in this work with the discovery of a new lead compound for NF-kappaB. Further biochemical analyses based on EMSA were performed and biological effects were tested on the compound exhibiting the best docking score. All experimental analysis were in fairly good agreement with molecular modeling findings.
The results obtained sustain the concept that the docking performance is predictive of a biochemical activity. In this respect, this paper represents the first example of successfully individuation through molecular docking simulations of a promising lead compound for the inhibition of NF-kappaB-p50 biological activity and modulation of the expression of the NF-kB regulated IL8 gene.
The main aim of our molecular modelling investigations was to identify natural compounds for their ability to bind to the NF-kappaB p50 as a strategy to identify molecules exhibiting inhibitory activity on the molecular interactions of the transcription factor with its target DNA sequence. p50–p65 heterodimer is the predominant NF-kappaB complex in T-cells regulating HIV-1 infection and recent studies have shown that p50 unit of NF-kappaB is the one that mainly interacts with HIV-1 LTR [
In particular, Sharma et al. [
The database of 27 natural structures used in our molecular docking studies, were derived from different medicinal plant extracts (Figure
Structures of compounds found in
NF-kappaB/DNA binding inhibitors used for atom-pair similarity scoring in docking.
Two inhibitory molecules (
The three dimensional structure of the complex NF-kappaB-DNA [
All molecules of plant extracts (
Unfortunately, complexes of NF-kappaB cocrystallized with inhibitors has not been solved. Therefore, a common self-docking procedure to evaluate the accuracy of the docking protocol adopted was not practicable. In order to overcame this situation, two structurally similar active compounds (
1. if 0.0 ≤ SimilScore < 0.3 → G-score = G-score+6.0
2. if 0.3 ≤ SimilScore < 0.7 → G-score = G-score+(0.7-Similscore)/(0.7-0.3)*6.0
3. if 0.7 ≤ SimilScore < 1.0 → G-score = G-score+0.0
All inhibitors molecules, except for
Based on the best final GlideScore ranking, the similarity docking procedure for subsequently docking simulations on p50 subunits was chosen.
Nuclear extracts were prepared as described [
EMSA was perfomed as previously described [
IB3-1 cells have been obtained from LGC Promochem [
Total RNA from IB3-1 cells was isolated using High Pure RNA Isolation Kit (Roche. Mannheim. Germany) [
The docking results for all the reference inhibitory compounds and the natural compounds under study are reported in Table
Ranking of the poses of references inhibitory molecules (1i-8i and 11i-12i) in the target NF-kappaB p50 both as dimer (p50-p50) and as monomers (p50 A and B).
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-5.88 |
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-6.06 |
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-6.08 |
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-5.88 |
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-5.83 |
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-5.35 |
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-5.84 |
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-5.20 |
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-5.06 |
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-5.78 |
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-5.07 |
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-4.58 |
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-3.87 |
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-2.79 |
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-3.59 |
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-3.57 |
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-2.77 |
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-1.82 |
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-0.76 |
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> 0 |
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> 0 |
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> 0 |
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> 0 |
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> 0 |
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- |
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> 0 |
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- |
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- |
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> 0 |
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- |
Ranking of the poses of natural compounds and test set inhibitors (9i and 10i) in the target NF-kappaB p50 both as dimer (p50-p50) and as monomers (p50 A and B). In the docking protocol 1 the similarity scoring algorithm is not used.
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-5.50 |
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-5.24 |
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-4.94 |
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-0.50 |
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-0.07 |
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> 0 |
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-0.05 |
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> 0 |
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> 0 |
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-4.74 |
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> 0 |
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> 0 |
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> 0 |
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> 0 |
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> 0 |
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> 0 |
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-4.40 |
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> 0 |
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> 0 |
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> 0 |
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-4.37 |
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> 0 |
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> 0 |
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> 0 |
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-4.28 |
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> 0 |
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> 0 |
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> 0 |
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-4.13 |
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> 0 |
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> 0 |
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> 0 |
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-3.48 |
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> 0 |
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> 0 |
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> 0 |
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-3.71 |
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> 0 |
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> 0 |
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> 0 |
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-3.39 |
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> 0 |
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> 0 |
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> 0 |
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-3.09 |
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> 0 |
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> 0 |
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> 0 |
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-3.05 |
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> 0 |
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> 0 |
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> 0 |
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-2.89 |
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> 0 |
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> 0 |
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> 0 |
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-2.69 |
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> 0 |
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> 0 |
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> 0 |
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-2.47 |
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> 0 |
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> 0 |
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> 0 |
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-2.00 |
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> 0 |
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> 0 |
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> 0 |
In order to evaluate the impact of the introduction of the similarity penalty in the docking algorithm on the results, the positions of
Known active compound
Docked compounds
Stereoview of compounds
Superimposition of the docked poses of inhibitors
Moreover, OH groups of coumarin moiety (carboxylate group in
intramolecular hydrogen bonds of the docked poses of 9i, 10i and 21 with the involved residues of the DNA binding region of NF-kappaB (see Figure 5 for ligand atom labels). The interatomic distances in Angstroms are shown.
| Residue interaction | Ligand atom | Distance (Å) |
| O5 |
2.12 | |
| O8 |
1.88 | |
| O2' |
1.90 | |
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| H5 |
1.91 | |
| H8 |
2.09 | |
| H2' |
2.00 | |
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| H7 |
1.96 | |
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| O7 |
2.60 | |
| O1a |
2.17 | |
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| O1 |
2.18 | |
Binding modes of
Poses of docked compound
Interestingly, the best pose of compound
All compounds with higher GlideScore and E-Model score clearly showed the ability to make a maximum number of hydrogen bonding, according with the result as previously reported on a flexible docking studies of known inhibitors
The effects of compound
EMSA analysis. NF-kappaB p50 has been incubated for 15 min in the presence of increasing amounts of compounds
Several experimental model system are available for biological validation of molecules inhibiting NF-kappaB function. In a recent paper we report that decoy oligonucleotides targeting NF-kappaB are powerful inhibitors of
When the effects of
A. Effects of PAO-1 infection of cystic fibrosis IB3-1 cells on the expression of the indicated mRNA. Cells were infected with PAO-1 for 4 hours and then the mRNA analysed by RT-PCR. For RT-PCR analysis the PCR primers have been described in Bezzerri et al. [
Since NF-kappaB is one of the most important transcription factors regulating the expression of IL-8 gene [23] and the data reported in Figure
In the present work, we carried out docking studies on the dataset of 27 molecules found in different plant extracts to NF-kappaB-p50, with the purpose of developing a docking protocol fit for the target under study, eventually applicable for more time-consuming virtual screening of larger database of compounds.
Usually, docking to protein structures that do not have a ligand present, as in the case of NF-kappaB, dramatically reduces the expected performance of structure-based methods. Therefore, the use of NF-kappaB as a target for virtual docking of natural compounds is not feasible. To overcome such a limitation, we proposed to enhance the simple docking procedure by means of a sort of combined target- and ligand-based drug design approach. Advantages of this combination strategy, based on a similarity parameter for the identification of weak binding chemical entities, are illustrated in this work with the discovery of a new lead compound for NF-kappaB. In this respect, this paper represents the first example of successfully individuation of a potential lead compound through molecular docking simulations on a NF-kappaB target. At the same time, information derived from this structure and its different binding modes, could carry through further lead optimization to more potent NF-kappaB inhibitors.
In order to validate the approach, biochemical analyses based on EMSA were performed on compound
Our results are of interest also from the practical point of view. The transcription factor NF-kappaB is indeed a very interesting target molecules in the design on anti-tumor, anti-inflammatory, pro-apoptotic drugs.
In order to validate this last hypothesis, we have employed human cystic fibrosis IB3-1 tracheal epithelial cells. We have elsewhere reported that these cells activate, upon exposure to the bacterium
LP carried out all the bioinformatic procedures and the docking experiments. EF participated to the EMSA assays; MB purified the nuclear factors for EMSA analysis; I.M. performed semi-quantitative RT-PCR analysis; VB performed the treatment of IB3-1 cells with selected compounds; MCD performed infection IB3-1 cells with P. aeruginosa; EN performed quantitative RT-PCR analysis of IB-8 mRNA; GC was the responsible of the conception, design, analysis and interpretation of the data on cystic fibrosis cell lines; RG was the responsible of the coordination of the project and of the drafting of the manuscript. All authors read and approved the final manuscript.
RG is granted by Fondazione CARIPARO, AIRC, Telethon and by MUR COFIN-2005. VB is fellow of the "Fondazione Cariverona", FQ and EN are fellows of the "Azienda Ospedaliera di Verona". This work was supported also by grants from the Italian Cystic Fibrosis Research Foundation (grants # 15/2004 and # 13/2007 to RG and GC) and Fondazione Cariverona – Bando 2005 – Malattie rare e della povertà (to GC).