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Simultaneous targeting of MyD88 and Nur77 as an effective approach for the treatment of inflammatory diseases.

Uzma S, Baig MS - Drug Des Devel Ther (2016)

Bottom Line: Myeloid differentiation primary response protein 88 (MyD88) has long been considered a central player in the inflammatory pathway.In this study, we have designed inhibitors that can inhibit both MyD88 and Nur77 at the same time.To perform this, we developed a homodimeric model of MyD88 and, along with the crystal structure of Nur77, screened a virtual library of compounds from the traditional Chinese medicine database containing ~61,000 compounds.

View Article: PubMed Central - PubMed

Affiliation: Divsion of Chemistry, School of Basic Sciences, Indore, MP, India.

ABSTRACT
Myeloid differentiation primary response protein 88 (MyD88) has long been considered a central player in the inflammatory pathway. Recent studies clearly suggest that it is an important therapeutic target in inflammation. On the other hand, a recent study on the interaction between the orphan nuclear receptor (Nur77) and p38α, leading to increased lipopolysaccharide-induced hyperinflammatory response, suggests this binary complex as a therapeutic target. In this study, we have designed inhibitors that can inhibit both MyD88 and Nur77 at the same time. Since both MyD88 and Nur77 are an integral part of the pathways involving lipopolysaccharide-induced activation of NF-κB-mediated inflammation, we tried to target both proteins with the same library in order to retrieve compounds having dual inhibitory properties. To perform this, we developed a homodimeric model of MyD88 and, along with the crystal structure of Nur77, screened a virtual library of compounds from the traditional Chinese medicine database containing ~61,000 compounds. We analyzed the resulting hits for their efficacy for dual binding and probed them for developing a common pharmacophore model that could be used as a prototype to screen compound libraries as well as to guide combinatorial library design to search for ideal dual-target inhibitors. Thus, our study explores the identification of novel leads having dual inhibiting effects due to binding to both MyD88 and Nur77 targets.

No MeSH data available.


Related in: MedlinePlus

The final pharmacophore model based on MyD88 and Nur77.Notes: Pharmacophore model (A) with CP1 (magenta) and CP4 (orange) and (B) without CP1 and CP4 in the background. The six major pharmacophore points have been numbered in black labels. The radii of the spatial constraints have been assigned after comparing the spatial features of CP1 and CP4.Abbreviations: CP1, Compound 1; CP4, Compound 4.
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f8-dddt-10-1557: The final pharmacophore model based on MyD88 and Nur77.Notes: Pharmacophore model (A) with CP1 (magenta) and CP4 (orange) and (B) without CP1 and CP4 in the background. The six major pharmacophore points have been numbered in black labels. The radii of the spatial constraints have been assigned after comparing the spatial features of CP1 and CP4.Abbreviations: CP1, Compound 1; CP4, Compound 4.

Mentions: A common pharmacophore model has been constructed by combining the common features from both ligand–receptor complexes, as discussed earlier (Table 5 and Figure 8A and B). The pharmacophore model consists of a (1) ring system (orange color sphere) for making π–alkyl interactions with Pro53 of MyD88 and Ser110 of Nur77; (2) a H-bond donor group (blue centroid) substituted onto the ring (1) for donating H–to Gln29 in MyD88 and Ser110/Thr264 in Nur77; (3) an acceptor =O close to the ring (red sphere) for accepting H’s from Gln29 in MyD88 and Thr264/Ser110 in Nur77; (4) and (5) two donor H’s at some distance from (1)–(3) points (dark blue spheres), making strong H-bonds with Asp50 in MyD88 and Asp263 in Nur77; and (6) a centroid/spatial hub (cyan sphere) for VdW/C–H bonds with Gln26, Leu52, and the surrounding residues of MyD88 and Ser110, Leu106, and the neighboring residues of Nur77. Another interesting observation of these complexes led us to propose that the distances between all these pharmacophore points was quite similar for both compounds in both the targets. For example, the distance between the pharmacophore feature (1) and (3) is 2.7 Å, which is strictly consistent in all four complexes (Table 6). Hence we applied spatial constraints in the final model according to the tolerance level for each pharmacophore point. For example the spatial constraints for (1) ring feature is 2 Å, which shows that any virtual screening hit should have its ring feature within the 2 Å area of the ring plane of our pharmacophore query. Similarly, the spatial constraints for (2) donor point is 1.5 Å, (3) acceptor point is 1.5 Å, (4) and (5) donor points are 1 Å each, and (6) spatial hub is 1.5 Å. The spatial constraints would help the pharmacophore query to retrieve results not only with the suggested pharmacophore features but also with a specific conformation in the three-dimensional space.


Simultaneous targeting of MyD88 and Nur77 as an effective approach for the treatment of inflammatory diseases.

Uzma S, Baig MS - Drug Des Devel Ther (2016)

The final pharmacophore model based on MyD88 and Nur77.Notes: Pharmacophore model (A) with CP1 (magenta) and CP4 (orange) and (B) without CP1 and CP4 in the background. The six major pharmacophore points have been numbered in black labels. The radii of the spatial constraints have been assigned after comparing the spatial features of CP1 and CP4.Abbreviations: CP1, Compound 1; CP4, Compound 4.
© Copyright Policy
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4862341&req=5

f8-dddt-10-1557: The final pharmacophore model based on MyD88 and Nur77.Notes: Pharmacophore model (A) with CP1 (magenta) and CP4 (orange) and (B) without CP1 and CP4 in the background. The six major pharmacophore points have been numbered in black labels. The radii of the spatial constraints have been assigned after comparing the spatial features of CP1 and CP4.Abbreviations: CP1, Compound 1; CP4, Compound 4.
Mentions: A common pharmacophore model has been constructed by combining the common features from both ligand–receptor complexes, as discussed earlier (Table 5 and Figure 8A and B). The pharmacophore model consists of a (1) ring system (orange color sphere) for making π–alkyl interactions with Pro53 of MyD88 and Ser110 of Nur77; (2) a H-bond donor group (blue centroid) substituted onto the ring (1) for donating H–to Gln29 in MyD88 and Ser110/Thr264 in Nur77; (3) an acceptor =O close to the ring (red sphere) for accepting H’s from Gln29 in MyD88 and Thr264/Ser110 in Nur77; (4) and (5) two donor H’s at some distance from (1)–(3) points (dark blue spheres), making strong H-bonds with Asp50 in MyD88 and Asp263 in Nur77; and (6) a centroid/spatial hub (cyan sphere) for VdW/C–H bonds with Gln26, Leu52, and the surrounding residues of MyD88 and Ser110, Leu106, and the neighboring residues of Nur77. Another interesting observation of these complexes led us to propose that the distances between all these pharmacophore points was quite similar for both compounds in both the targets. For example, the distance between the pharmacophore feature (1) and (3) is 2.7 Å, which is strictly consistent in all four complexes (Table 6). Hence we applied spatial constraints in the final model according to the tolerance level for each pharmacophore point. For example the spatial constraints for (1) ring feature is 2 Å, which shows that any virtual screening hit should have its ring feature within the 2 Å area of the ring plane of our pharmacophore query. Similarly, the spatial constraints for (2) donor point is 1.5 Å, (3) acceptor point is 1.5 Å, (4) and (5) donor points are 1 Å each, and (6) spatial hub is 1.5 Å. The spatial constraints would help the pharmacophore query to retrieve results not only with the suggested pharmacophore features but also with a specific conformation in the three-dimensional space.

Bottom Line: Myeloid differentiation primary response protein 88 (MyD88) has long been considered a central player in the inflammatory pathway.In this study, we have designed inhibitors that can inhibit both MyD88 and Nur77 at the same time.To perform this, we developed a homodimeric model of MyD88 and, along with the crystal structure of Nur77, screened a virtual library of compounds from the traditional Chinese medicine database containing ~61,000 compounds.

View Article: PubMed Central - PubMed

Affiliation: Divsion of Chemistry, School of Basic Sciences, Indore, MP, India.

ABSTRACT
Myeloid differentiation primary response protein 88 (MyD88) has long been considered a central player in the inflammatory pathway. Recent studies clearly suggest that it is an important therapeutic target in inflammation. On the other hand, a recent study on the interaction between the orphan nuclear receptor (Nur77) and p38α, leading to increased lipopolysaccharide-induced hyperinflammatory response, suggests this binary complex as a therapeutic target. In this study, we have designed inhibitors that can inhibit both MyD88 and Nur77 at the same time. Since both MyD88 and Nur77 are an integral part of the pathways involving lipopolysaccharide-induced activation of NF-κB-mediated inflammation, we tried to target both proteins with the same library in order to retrieve compounds having dual inhibitory properties. To perform this, we developed a homodimeric model of MyD88 and, along with the crystal structure of Nur77, screened a virtual library of compounds from the traditional Chinese medicine database containing ~61,000 compounds. We analyzed the resulting hits for their efficacy for dual binding and probed them for developing a common pharmacophore model that could be used as a prototype to screen compound libraries as well as to guide combinatorial library design to search for ideal dual-target inhibitors. Thus, our study explores the identification of novel leads having dual inhibiting effects due to binding to both MyD88 and Nur77 targets.

No MeSH data available.


Related in: MedlinePlus