The interprotein scoring noises in glide docking scores

Authors

  • Wei Wang,

    1. State Key Laboratory of Plant Physiology and Biochemistry, Zhejiang University, Hangzhou, People's Republic of China 310058
    2. Department of Genetics and Bioinformatics, Zhejiang University, Hangzhou, People's Republic of China 310058
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  • Xi Zhou,

    1. Department of Genetics and Bioinformatics, Zhejiang University, Hangzhou, People's Republic of China 310058
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  • Wanlin He,

    1. Department of Genetics and Bioinformatics, Zhejiang University, Hangzhou, People's Republic of China 310058
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  • Yi Fan,

    1. Central Research Institute, Shanghai Pharmaceuticals Holding Co., Ltd., People's Republic of China 201203
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  • Yuzong Chen,

    1. Department of Pharmacy, National University of Singapore, Singapore 117543
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  • Xin Chen

    Corresponding author
    1. State Key Laboratory of Plant Physiology and Biochemistry, Zhejiang University, Hangzhou, People's Republic of China 310058
    2. Department of Genetics and Bioinformatics, Zhejiang University, Hangzhou, People's Republic of China 310058
    • Department of Genetics Bioinformatics, Zhejiang University, Hangzhou, People's Republic of China 310058
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Abstract

Small molecule drugs are rarely selective enough to interact solely with their designated targets. Unintended “off-target” interactions often lead to side effects, but also serendipitously lead to new therapeutic uses. Identification of the off-targets of a compound is therefore of significant value to the evaluation of its developmental potential. In computational biology, the strategy of “reverse docking” has been introduced to predict the targets of a compound, which uses a compound to virtually screen a library of proteins, reversing the bait and prey in “normal” docking screenings. The present study shows that, in reverse docking, additional optimization of the scoring function may help to improve the target prediction accuracy. In a case study with the Glide scores, we found that only 57% of the ligand–protein relationships could be correctly identified in a library of 58 complexes whose crystal binding conformations were all able to be accurately reproduced. This was likely a result of the constant over- or under-estimation of the scores for specific proteins. In other words, there were interprotein noises in the Glide scores. Introducing a correction term based on protein characteristics improved the target-prediction accuracy by 27% (57–72%). It is our hope that this focused discussion on the Glide scores would invite further efforts to characterize and normalize this type of interprotein noises in all docking scores, so that better target prediction accuracy can be achieved with the strategy of reverse docking. Proteins 2012; © 2011 Wiley Periodicals, Inc.

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