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Biomolecular Interfaces Provide Universal Markers for Drug Specificity and Personalized Medicine

  • Ariel Fernández Stigliano
Chapter

Abstract

Chapter 9 illustrated the power of the wrapping concept as guidance to engineer specificity and enhance safety in a kinase inhibitor. Yet, only a universal selectivity filter, applicable to the entire human kinome—even to kinases with unreported structure——and to idiosyncratic variations of the kinome would be truly useful for the drug designer. This chapter thematically belongs to the bioinformatics realm and addresses this issue at the broadest possible level. The surveyed findings reveal that targeting the epistructural singularities defined by protein dehydrons ushers a new generation of drugs that enable a tighter control of specificity and a personalization of the treatment. The universality of this selectivity filter in the field of therapeutic interference with cell signaling is thus established. The concepts introduced in this chapter are further extended to the realm of personalized molecular therapy (“the right drug for the right person”), since this area is regarded as a major imperative of post-genomic medicine. This perception is reinforced almost daily as promising therapeutic agents are recalled because of idiosyncratic side effects detected in small subpopulations of patients. However pressing the need, rational approaches to personalized drug therapy will ultimately and pivotally depend on our ability to translate genomic individualities and variations into molecular biomarkers that can guide a patient-tailored design. This chapter addresses also this issue and describes how the wrapping design concept can be brought to fruition in the personalization of drug therapy. The chapter introduces plausible scenarios in which genomic idiosyncrasies and oncogenic variations may promote targetable differences in the wrapping patterns of the gene products. Ultimately, the chapter extends an invitation to adopt and exploit protein wrapping as a molecular biomarker for personalized medicine within an enabling platform to tailor drugs to patient idiosyncrasies.

Keywords

Selectivity Filter Nonpolar Group Kinase Target Nonpolar Residue Backbone Hydrogen Bond 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.National Research Council–CONICETBuenos AiresArgentina
  2. 2.Former Karl F. Hasselmann Endowed Chair Professor of BioengineeringRice UniversityHoustonUSA

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