2016
DOI: 10.7554/elife.20352
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Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer

Abstract: Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines rev… Show more

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Cited by 76 publications
(94 citation statements)
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“…To match the mini-protein scaffolds with the desired target helix-binding motifs, we used the Rosetta MotifGraft Mover 7,24 . The inputs were composed of: (1) HB36, HB80 or Syt-II helical binding motifs (Protein Databank (PDB) IDs: 3R2X, 4EEF and 2NM1, respectively); (2) the context target protein (influenza HA or BoNT H C B); and (3) the above described library of de novo mini-protein scaffolds.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…To match the mini-protein scaffolds with the desired target helix-binding motifs, we used the Rosetta MotifGraft Mover 7,24 . The inputs were composed of: (1) HB36, HB80 or Syt-II helical binding motifs (Protein Databank (PDB) IDs: 3R2X, 4EEF and 2NM1, respectively); (2) the context target protein (influenza HA or BoNT H C B); and (3) the above described library of de novo mini-protein scaffolds.…”
Section: Methodsmentioning
confidence: 99%
“…Computational protein design has the potential to overcome these limitations by efficiently sampling both shape and sequence space on a much larger scale, and by generating readily producible proteins, as recently demonstrated by the design of stapled mini-protein scaffolds with a wide range of shapes 5 . Despite this potential, the high cost of synthesizing genes for each designed protein has, until recently 6 , limited testing to small numbers (tens) of designs for any one application, which is too few to systematically explore the determinants of protein binding and folding and provide feedback to improve the computational model 7,8 .…”
mentioning
confidence: 99%
“…Berger et al used a 3-helix bundle protein, BINDI that utilizes a BH3-like central helix with two flanking helices for additional contacts [46]. Computational mutagenesis and docking was used to develop a series of mutants capable of selectively inhibiting each of the six anti-apoptotic BCL-2 proteins.…”
Section: Non-canonical Targeting Of Anti-apoptotic Bcl-2 Proteinsmentioning
confidence: 99%
“…62 In summary, we have identified non-natural protein ligands that exhibit selectivity for different BCL-2 family members. Although computational protein design has been applied to discovery of BCL-2 family selective binders, 63 to our knowledge non-antibody based binding proteins have not previously been shown to differentiate between these proteins notably BCL-xL and MCL-1; this is noteworthy given the role of MCL-1 in driving several cancers. 64,65 We note the attrition rate that is a consequence of applying a variety of activity criteria as we progressed along this pipeline.…”
Section: Discussion (Without Subheadings)mentioning
confidence: 99%