Dynamic allostery-based molecular workings of kinase:peptide complexes

Lalima G. Ahuja, Phillip C. Aoto, Alexandr P. Kornev, Gianluigi Veglia, Susan S. Taylor

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


A dense interplay between structure and dynamics underlies the working of proteins, especially enzymes. Protein kinases are molecular switches that are optimized for their regulation rather than catalytic turnover rates. Using long-simulations dynamic allostery analysis, this study describes an exploration of the dynamic kinase:peptide complex. We have used protein kinase A (PKA) as a model system as a generic prototype of the protein kinase superfamily of signaling enzymes. Our results explain the role of dynamic coupling of active-site residues that must work in coherence to provide for a successful activation or inhibition response from the kinase. Amino acid networks-based community analysis allows us to ponder the conformational entropy of the kinase:nucleotide:peptide ternary complex. We use a combination of 7 peptides that include 3 types of PKA-binding partners: Substrates, products, and inhibitors. The substrate peptides provide for dynamic insights into the enzyme:substrate complex, while the product phospho-peptide allows for accessing modes of enzyme: product release. Mapping of allosteric communities onto the PKA structure allows us to locate the more unvarying and flexible dynamic regions of the kinase. These distributions, when correlated with the structural elements of the kinase core, allow for a detailed exploration of key dynamics-based signatures that could affect peptide recognition and binding at the kinase active site. These studies provide a unique dynamic allostery-based perspective to kinase:peptide complexes that have previously been explored only in a structural or thermodynamic context.

Original languageEnglish (US)
Pages (from-to)15052-15061
Number of pages10
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number30
StatePublished - 2019

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS. We thank Dr. Christopher L. McClendon for the initial scripts used for analysis of the simulations and for determining of mutual-information maps. This work was supported by Public Health Service/ NIH Grant GM100310 (to G.V. and S.S.T.) and NIH Grant GM034921 (to S.S.T.). P.C.A. was supported by Ruth L. Kirschstein National Research Service Award NIH/NCI T32 CA009523.

Publisher Copyright:
© 2019 National Academy of Sciences. All rights reserved.


  • Allostery
  • Community maps
  • Dynamics
  • Protein kinase
  • Violin model


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