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Drug Inhibition Profile Prediction for NFκB Pathway in Multiple Myeloma

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  • Huiming Peng
  • Jianguo Wen
  • Hongwei Li
  • Jeff Chang
  • Xiaobo Zhou

Abstract

Nuclear factor κB (NFκB) activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFα) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are not any quantitative or qualitative results of comparison assessment on inhibition effect between different drugs either used alone or in combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific drugs used alone or in combinations on the NFκB pathway in MM and to predict the potential synergistic drug combinations.

Suggested Citation

  • Huiming Peng & Jianguo Wen & Hongwei Li & Jeff Chang & Xiaobo Zhou, 2011. "Drug Inhibition Profile Prediction for NFκB Pathway in Multiple Myeloma," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-13, March.
    • Handle: RePEc:plo:pone00:0014750
    DOI: 10.1371/journal.pone.0014750
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    References listed on IDEAS

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    1. Diego Calzolari & Stefania Bruschi & Laurence Coquin & Jennifer Schofield & Jacob D Feala & John C Reed & Andrew D McCulloch & Giovanni Paternostro, 2008. "Search Algorithms as a Framework for the Optimization of Drug Combinations," PLOS Computational Biology, Public Library of Science, vol. 4(12), pages 1-14, December.
    2. Adam Smith, 2002. "Screening for drug discovery: The leading question," Nature, Nature, vol. 418(6896), pages 453-455, July.
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