Methodology article

BMC Chemical Biology

, 12:2

Open Access This content is freely available online to anyone, anywhere at any time.

Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications

  • Hiroki KobayashiAffiliated withDepartment of Biosciences and Informatics, Faculty of Science and Technology, Keio University Email author 
  • , Hiroko HaradaAffiliated withDepartment of Biosciences and Informatics, Faculty of Science and Technology, Keio University Email author 
  • , Masaomi NakamuraAffiliated withDepartment of Biosciences and Informatics, Faculty of Science and Technology, Keio University
  • , Yushi FutamuraAffiliated withDepartment of Biosciences and Informatics, Faculty of Science and Technology, Keio University
  • , Akihiro ItoAffiliated withChemical Genetics Laboratory, RIKEN Advanced Science Institute
  • , Minoru YoshidaAffiliated withChemical Genetics Laboratory, RIKEN Advanced Science Institute
  • , Shun-ichiro IemuraAffiliated withNational Institute of Advanced Industrial Science and Technology (AIST)
  • , Kazuo Shin-yaAffiliated withNational Institute of Advanced Industrial Science and Technology (AIST)
  • , Takayuki DoiAffiliated withGraduate School of Pharmaceutical Sciences, Tohoku University
    • , Takashi TakahashiAffiliated withDepartment of Applied Chemistry, Tokyo Institute of Technology
    • , Tohru NatsumeAffiliated withNational Institute of Advanced Industrial Science and Technology (AIST)
    • , Masaya ImotoAffiliated withDepartment of Biosciences and Informatics, Faculty of Science and Technology, Keio University
    • , Yasubumi SakakibaraAffiliated withDepartment of Biosciences and Informatics, Faculty of Science and Technology, Keio University Email author 

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.