AI Article Synopsis
- Identifying target proteins for bioactive compounds is crucial for understanding their action but has been challenging due to low detection sensitivity.
- Researchers tested a new method combining computer predictions and lab experiments to identify proteins that bind to the compound incednine, which inhibits a protein called Bcl-xL.
- Out of 182 predicted candidates, 40% were validated, leading to the discovery of three new proteins that interact with incednine, highlighting the effectiveness of their approach in target protein identification.
Article Abstract
Background: Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis.
Results: We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system.As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins.
Conclusions: This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3471015 | PMC |
| http://dx.doi.org/10.1186/1472-6769-12-2 | DOI Listing |
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