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Potential application of network descriptions for understanding conformational changes and protonation states of ABC transporters

  • Tamás Hegedus
  • , Gergely Gyimesi
  • , Merse E. Gáspár
  • , Kristóf Z. Szalay
  • , Rajeev Gangal
  • , Peter Csermely*
  • *Corresponding author for this work
  • Hungarian Academy of Sciences
  • Semmelweis University

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

The ABC (ATP Binding Cassette) transporter protein superfamily comprises a large number of ubiquitous and functionally versatile proteins conserved from archaea to humans. ABC transporters have a key role in many human diseases and also in the development of multidrug resistance in cancer and in parasites. Although a dramatic progress has been achieved in ABC protein studies in the last decades, we are still far from a detailed understanding of their molecular functions. Several aspects of pharmacological ABC transporter targeting also remain unclear. Here we summarize the conformational and protonation changes of ABC transporters and the potential use of this information in pharmacological design. Network related methods, which recently became useful tools to describe protein structure and dynamics, have not been applied to study allosteric coupling in ABC proteins as yet. A detailed description of the strengths and limitations of these methods is given, and their potential use in describing ABC transporter dynamics is outlined. Finally, we highlight possible future aspects of pharmacological utilization of network methods and outline the future trends of this exciting field.

Original languageEnglish
Pages (from-to)4155-4172
Number of pages18
JournalCurrent Pharmaceutical Design
Volume19
Issue number23
DOIs
StatePublished - 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • ABC transporters
  • Conformational change
  • Network pharmacology
  • Protein dynamics
  • Protein structure networks
  • Protonation

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