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Bioinformatic scaling of allosteric interactions in biomedical isozymes

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  • Phillips, J.C.

Abstract

Allosteric (long-range) interactions can be surprisingly strong in proteins of biomedical interest. Here we use bioinformatic scaling to connect prior results on nonsteroidal anti-inflammatory drugs to promising new drugs that inhibit cancer cell metabolism. Many parallel features are apparent, which explain how even one amino acid mutation, remote from active sites, can alter medical results. The enzyme twins involved are cyclooxygenase (aspirin) and isocitrate dehydrogenase (IDH). The IDH results are accurate to 1% and are overdetermined by adjusting a single bioinformatic scaling parameter. It appears that the final stage in optimizing protein functionality may involve leveling of the hydrophobic limits of the arms of conformational hydrophilic hinges.

Suggested Citation

  • Phillips, J.C., 2016. "Bioinformatic scaling of allosteric interactions in biomedical isozymes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 289-294.
    • Handle: RePEc:eee:phsmap:v:457:y:2016:i:c:p:289-294
    DOI: 10.1016/j.physa.2016.03.038
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    References listed on IDEAS

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    1. Phillips, J.C., 2014. "Fractals and self-organized criticality in anti-inflammatory drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 538-543.
    2. Phillips, J.C., 2014. "Fractals and self-organized criticality in proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 440-448.
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