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Title: Eigenvector centrality for characterization of protein allosteric pathways

Determining the principal energy-transfer pathways responsible for allosteric communication in biomolecules remains challenging, partially due to the intrinsic complexity of the systems and the lack of effective characterization methods. In this work, we introduce the eigenvector centrality metric based on mutual information to elucidate allosteric mechanisms that regulate enzymatic activity. Moreover, we propose a strategy to characterize the range of correlations that underlie the allosteric processes. We use the V-type allosteric enzyme imidazole glycerol phosphate synthase (IGPS) to test the proposed methodology. The eigenvector centrality method identifies key amino acid residues of IGPS with high susceptibility to effector binding. The findings are validated by solution NMR measurements yielding important biological insights, including direct experimental evidence for interdomain motion, the central role played by helix h α 1 , and the short-range nature of correlations responsible for the allosteric mechanism. Beyond insights on IGPS allosteric pathways and the nature of residues that could be targeted by therapeutic drugs or site-directed mutagenesis, the reported findings demonstrate the eigenvector centrality analysis as a general cost-effective methodology to gain fundamental understanding of allosteric mechanisms at the molecular level.
Authors:
ORCiD logo [1] ;  [2] ;  [3] ;  [2] ;  [4] ;  [2] ;  [5] ;  [6] ; ORCiD logo [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Yale Univ., New Haven, CT (United States)
  2. Yale Univ., New Haven, CT (United States)
  3. Yale Univ., New Haven, CT (United States); Lafayette College, Easton, PA (United States)
  4. Yale Univ., New Haven, CT (United States); Brown Univ., Providence, RI (United States)
  5. Univ. degli Studi di Bologna (Italy); Univ. Claude Bernard Lyon (France)
  6. Univ. of New South Wales, Sydney, NSW (Australia)
Publication Date:
Report Number(s):
LA-UR-17-22957
Journal ID: ISSN 0027-8424
Grant/Contract Number:
89233218CNA000001
Type:
Accepted Manuscript
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 115; Journal Issue: 52; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Biological Science; Allosteric regulation, protein, graphs
OSTI Identifier:
1492535

Negre, Christian F. A., Morzan, Uriel N., Hendrickson, Heidi P., Pal, Rhitankar, Lisi, George P., Loria, J. Patrick, Rivalta, Ivan, Ho, Junming, and Batista, Victor S.. Eigenvector centrality for characterization of protein allosteric pathways. United States: N. p., Web. doi:10.1073/pnas.1810452115.
Negre, Christian F. A., Morzan, Uriel N., Hendrickson, Heidi P., Pal, Rhitankar, Lisi, George P., Loria, J. Patrick, Rivalta, Ivan, Ho, Junming, & Batista, Victor S.. Eigenvector centrality for characterization of protein allosteric pathways. United States. doi:10.1073/pnas.1810452115.
Negre, Christian F. A., Morzan, Uriel N., Hendrickson, Heidi P., Pal, Rhitankar, Lisi, George P., Loria, J. Patrick, Rivalta, Ivan, Ho, Junming, and Batista, Victor S.. 2018. "Eigenvector centrality for characterization of protein allosteric pathways". United States. doi:10.1073/pnas.1810452115.
@article{osti_1492535,
title = {Eigenvector centrality for characterization of protein allosteric pathways},
author = {Negre, Christian F. A. and Morzan, Uriel N. and Hendrickson, Heidi P. and Pal, Rhitankar and Lisi, George P. and Loria, J. Patrick and Rivalta, Ivan and Ho, Junming and Batista, Victor S.},
abstractNote = {Determining the principal energy-transfer pathways responsible for allosteric communication in biomolecules remains challenging, partially due to the intrinsic complexity of the systems and the lack of effective characterization methods. In this work, we introduce the eigenvector centrality metric based on mutual information to elucidate allosteric mechanisms that regulate enzymatic activity. Moreover, we propose a strategy to characterize the range of correlations that underlie the allosteric processes. We use the V-type allosteric enzyme imidazole glycerol phosphate synthase (IGPS) to test the proposed methodology. The eigenvector centrality method identifies key amino acid residues of IGPS with high susceptibility to effector binding. The findings are validated by solution NMR measurements yielding important biological insights, including direct experimental evidence for interdomain motion, the central role played by helix hα1, and the short-range nature of correlations responsible for the allosteric mechanism. Beyond insights on IGPS allosteric pathways and the nature of residues that could be targeted by therapeutic drugs or site-directed mutagenesis, the reported findings demonstrate the eigenvector centrality analysis as a general cost-effective methodology to gain fundamental understanding of allosteric mechanisms at the molecular level.},
doi = {10.1073/pnas.1810452115},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 52,
volume = 115,
place = {United States},
year = {2018},
month = {12}
}