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PreprintCited by 29Protein Structure and DynamicsSignaling Pathways in DiseaseComputational Drug Discovery Methods

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Dynamic design: manipulation of millisecond timescale motions on the energy landscape of Cyclophilin A

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Juárez-Jiménez, Jordi, Gupta, Arun A., Karunanithy, Gogulan, Mey, Antonia S. J. S., Georgiou, Charis, Ioannidis, Harris, De Simone, Alessio, Barlow, Paul N., Hulme, Alison N., Walkinshaw, Malcolm D., Baldwin, Andrew J., Michel, Julien·2018·Chemical Science
DOI 10.1101/490987PMC PMC8157532

Preprint — published as 10.1039/c9sc04696h

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Abstract

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they inter-convert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov State modelling (MSM) to explore these ‘excited’ conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By accurately and reliably exploring functionally relevant, but sparsely populated conformations with milli-second lifetimes in silico , our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.

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Metadata

Authors
Juárez-Jiménez, J., Gupta, A. A., Karunanithy, G., Mey, A. S. J. S., Georgiou, C., Ioannidis, H., De Simone, A., Barlow, P. N., Hulme, A. N., Walkinshaw, M. D., Baldwin, A. J., & Michel, J.
Affiliations
  • University of Edinburgh (GB)
  • University of Oxford (GB)
Corresponding author
Michel, Julien
ORCID
Venue
Chemical Science
Publisher
openRxiv
Published
2018-12-08
Volume
11
Issue
10
Pages
2670-2680
ISSN
2041-6520 (ISSN-L)
DOI
10.1101/490987
PMC
PMC8157532
OpenAlex
W3000400250
Cited by
29
References
1
Citations by year
2026: 6 · 2025: 4 · 2024: 4 · 2023: 3 · 2022: 1 · 2021: 7 · 2020: 4
FWCI
1.22
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Chemical Science (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
Funders
  • Wellcome Trust (101527, 101527/Z/13/Z)
  • Diamond Light Source (BAG MX18515)
  • Royal Society
  • European Commission (2007–2013, 655667, FP7 2007-2013, HORIZON2020, FP7/2007)
  • Engineering and Physical Sciences Research Council (EP/M022609/1, EP/P011330/1, FP7/2007–2013, EP/I030395/1, EP/L000253/1)
  • FP7 Ideas: European Research Council (336289)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Signaling Pathways in Disease
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
cyclophilin A, accelerated molecular dynamics, Markov state models, protein engineering, drug discovery

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