Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications
- Equal contributors
1 Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan
2 Chemical Genetics Laboratory, RIKEN Advanced Science Institute, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan
3 National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan
4 Graduate School of Pharmaceutical Sciences, Tohoku University, 6-3 Aza-Aoba, Aramaki, Aoba, Sendai, 980-8578, Japan
5 Department of Applied Chemistry, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro, Tokyo, 152-8552, Japan
Citation and License
BMC Chemical Biology 2012, 12:2 doi:10.1186/1472-6769-12-2Published: 5 April 2012
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.
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.
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.