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2011
DOI: 10.1002/anie.201105901
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Immunosuppressive Small Molecule Discovered by Structure‐Based Virtual Screening for Inhibitors of Protein–Protein Interactions

Abstract: Interfering with interferon: A low‐molecular‐weight inhibitor has been discovered that blocks the interaction between interferon‐α (IFN‐α) and its receptor (see picture for a model of the interfaces). The resulting lead compound significantly reduces IFN‐α production in vitro. NMR and SPR experiments confirm the direct interaction of the inhibitor with IFN‐α.

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Cited by 38 publications
(23 citation statements)
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References 37 publications
(36 reference statements)
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“…[1] While targeting these interactions with large alpha-helical mimics [25] has been relatively successful, developing drug-like small molecule inhibitors of PPIs remains highly challenging. Recently, some success has resulted from the use of virtual screening [6] , fragment based approaches [7] and the targeting of hot-spots, [8] however the hit rates for protein interfaces remain low. [1c] …”
mentioning
confidence: 99%
“…[1] While targeting these interactions with large alpha-helical mimics [25] has been relatively successful, developing drug-like small molecule inhibitors of PPIs remains highly challenging. Recently, some success has resulted from the use of virtual screening [6] , fragment based approaches [7] and the targeting of hot-spots, [8] however the hit rates for protein interfaces remain low. [1c] …”
mentioning
confidence: 99%
“…Recent examples of PPI inhibitors identified by virtual screening are summarized in Table 4 and Fig. 141 More recently, Li's group reported a new computational strategy for PPI drug design by combining multiple ligand simultaneous docking (MLSD) and drug repositioning. On the basis of the reported examples, virtual screening is more successful for PPI targets with welldefined hot spots.…”
Section: Virtual Screeningmentioning
confidence: 99%
“…VS approaches have played a significant role in changing the notion about the undruggability of PPIs. Some of these VS studies took advantage of the hierarchical approach to identify initial hits that were later optimized into highly potent SMPPIIs [147,165,167,168,[175][176][177][178]. Some of these VS studies took advantage of the hierarchical approach to identify initial hits that were later optimized into highly potent SMPPIIs [147,165,167,168,[175][176][177][178].…”
Section: Hlvs For the Identification Of Smppiismentioning
confidence: 99%