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Regulating the ARNT/TACC3 axis: multiple approaches to manipulating protein/protein interactions with small molecules.

ABSTRACT: For several well-documented reasons, it has been challenging to develop artificial small molecule inhibitors of protein/protein complexes. Such reagents are of particular interest for transcription factor complexes given links between their misregulation and disease. Here we report parallel approaches to identify regulators of a hypoxia signaling transcription factor complex, involving the ARNT subunit of the HIF (Hypoxia Inducible Factor) activator and the TACC3 (Transforming Acidic Coiled Coil Containing Protein 3) coactivator. In one route, we used in vitro NMR and biochemical screening to identify small molecules that selectively bind within the ARNT PAS (Per-ARNT-Sim) domain that recruits TACC3, identifying KG-548 as an ARNT/TACC3 disruptor. A parallel, cell-based screening approach previously implicated the small molecule KHS101 as an inhibitor of TACC3 signaling. Here, we show that KHS101 works indirectly on HIF complex formation by destabilizing both TACC3 and the HIF component HIF-1?. Overall, our data identify small molecule regulators for this important complex and highlight the utility of pursuing parallel strategies to develop protein/protein inhibitors.

SUBMITTER: Guo Y

PROVIDER: S-EPMC3600089 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Regulating the ARNT/TACC3 axis: multiple approaches to manipulating protein/protein interactions with small molecules.

Guo Yirui Y Partch Carrie L CL Key Jason J Card Paul B PB Pashkov Victor V Patel Anjana A Bruick Richard K RK Wurdak Heiko H Gardner Kevin H KH

ACS chemical biology 20121226 3

For several well-documented reasons, it has been challenging to develop artificial small molecule inhibitors of protein/protein complexes. Such reagents are of particular interest for transcription factor complexes given links between their misregulation and disease. Here we report parallel approaches to identify regulators of a hypoxia signaling transcription factor complex, involving the ARNT subunit of the HIF (Hypoxia Inducible Factor) activator and the TACC3 (Transforming Acidic Coiled Coil ...[more]

PMID: 23240775

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Project description:Although the number of available protein sequences is growing exponentially, functional protein annotations lag far behind. Therefore, accurate identification of protein functions remains one of the major challenges in molecular biology. In this study, we presented a novel approach to predict mouse protein functions. The approach was a sequential combination of a similarity-based approach, an interaction-based approach and a pseudo amino acid composition-based approach. The method achieved an accuracy of about 0.8450 for the 1st-order predictions in the leave-one-out and ten-fold cross-validations. For the results yielded by the leave-one-out cross-validation, although the similarity-based approach alone achieved an accuracy of 0.8756, it was unable to predict the functions of proteins with no homologues. Comparatively, the pseudo amino acid composition-based approach alone reached an accuracy of 0.6786. Although the accuracy was lower than that of the previous approach, it could predict the functions of almost all proteins, even proteins with no homologues. Therefore, the combined method balanced the advantages and disadvantages of both approaches to achieve efficient performance. Furthermore, the results yielded by the ten-fold cross-validation indicate that the combined method is still effective and stable when there are no close homologs are available. However, the accuracy of the predicted functions can only be determined according to known protein functions based on current knowledge. Many protein functions remain unknown. By exploring the functions of proteins for which the 1st-order predicted functions are wrong but the 2nd-order predicted functions are correct, the 1st-order wrongly predicted functions were shown to be closely associated with the genes encoding the proteins. The so-called wrongly predicted functions could also potentially be correct upon future experimental verification. Therefore, the accuracy of the presented method may be much higher in reality.

Dataset Information

Regulating the ARNT/TACC3 axis: multiple approaches to manipulating protein/protein interactions with small molecules.

Publications

Regulating the ARNT/TACC3 axis: multiple approaches to manipulating protein/protein interactions with small molecules.

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