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Consensus model for identification of novel PI3K inhibitors in large chemical library

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Abstract

Phosphoinositide 3-kinases (PI3Ks) inhibitors have treatment potential for cancer, diabetes, cardiovascular disease, chronic inflammation and asthma. A consensus model consisting of three base classifiers (AODE, kNN, and SVM) trained with 1,283 positive compounds (PI3K inhibitors), 16 negative compounds (PI3K non-inhibitors) and 64,078 generated putative negatives was developed for predicting compounds with PI3K inhibitory activity of IC50 ≤ 10 μM. The consensus model has an estimated false positive rate of 0.75%. Nine novel potential inhibitors were identified using the consensus model and several of these contain structural features that are consistent with those found to be important for PI3K inhibitory activities. An advantage of the current model is that it does not require knowledge of 3D structural information of the various PI3K isoforms, which is not readily available for all isoforms.

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Acknowledgments

Our appreciation to Professor Chen Yu Zong (Bioinformatics and Drug Design Group, National University of Singapore) for his valuable discussions.

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Authors and Affiliations

  1. Pharmaceutical Data Exploration Laboratory, Department of Pharmacy, National University of Singapore, Singapore, Singapore

    Chin Yee Liew & Chun Wei Yap

  2. Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore, Singapore

    Xiao Hua Ma

Authors
  1. Chin Yee Liew
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  2. Xiao Hua Ma
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  3. Chun Wei Yap
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Correspondence to Chun Wei Yap.

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Liew, C.Y., Ma, X.H. & Yap, C.W. Consensus model for identification of novel PI3K inhibitors in large chemical library. J Comput Aided Mol Des 24, 131–141 (2010). https://doi.org/10.1007/s10822-010-9321-0

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  • DOI: https://doi.org/10.1007/s10822-010-9321-0

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