Skip to main navigation Skip to search Skip to main content

Cell phenotypes can be predicted from propensities of protein conformations

  • Ruth Nussinov*
  • , Yonglan Liu
  • , Wengang Zhang
  • , Hyunbum Jang
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

22 Scopus citations

Abstract

Proteins exist as dynamic conformational ensembles. Here we suggest that the propensities of the conformations can be predictors of cell function. The conformational states that the molecules preferentially visit can be viewed as phenotypic determinants, and their mutations work by altering the relative propensities, thus the cell phenotype. Our examples include (i) inactive state variants harboring cancer driver mutations that present active state-like conformational features, as in K-Ras4BG12V compared to other K-Ras4BG12X mutations; (ii) mutants of the same protein presenting vastly different phenotypic and clinical profiles: cancer and neurodevelopmental disorders; (iii) alterations in the occupancies of the conformational (sub)states influencing enzyme reactivity. Thus, protein conformational propensities can determine cell fate. They can also suggest the allosteric drugs efficiency.

Original languageEnglish
Article number102722
JournalCurrent Opinion in Structural Biology
Volume83
DOIs
StatePublished - Dec 2023

Funding

FundersFunder number
U.S. Government
National Institutes of HealthHHSN261201500003I
U.S. Department of Health and Human Services
National Cancer Institute
Institut National du Cancer

    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

    • Cancer
    • Cell fate
    • Conformational ensembles
    • Neurodevelopmental disorders
    • Occupancy
    • RASopathies

    Fingerprint

    Dive into the research topics of 'Cell phenotypes can be predicted from propensities of protein conformations'. Together they form a unique fingerprint.

    Cite this