PreprintCited by 16Protein Structure and DynamicsEnzyme Structure and FunctionComputational Drug Discovery Methods

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Induced fit with replica exchange improves protein complex structure prediction

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Harmalkar, Ameya, Mahajan, Sai Pooja, Gray, Jeffrey J.·2021·PLoS Computational Biology

Preprint — published as 10.1371/journal.pcbi.1010124 · Paper page

Abstract

Despite the progress in prediction of protein complexes over the last decade, recent blind protein complex structure prediction challenges revealed limited success rates (less than 20% models with DockQ score > 0.4) on targets that exhibit significant conformational change upon binding. To overcome limitations in capturing backbone motions, we developed a new, aggressive sampling method that incorporates temperature replica exchange Monte Carlo (T-REMC) and conformational sampling techniques within docking protocols in Rosetta. Our method, ReplicaDock 2.0, mimics induced-fit mechanism of protein binding to sample backbone motions across putative interface residues on-the-fly, thereby recapitulating binding-partner induced conformational changes. Furthermore, ReplicaDock 2.0 clocks in at 150-500 CPU hours per target (protein-size dependent); a runtime that is significantly faster than Molecular Dynamics based approaches. For a benchmark set of 88 proteins with moderate to high flexibility (unbound-to-bound iRMSD over 1.2 Å), ReplicaDock 2.0 successfully docks 61% of moderately flexible complexes and 35% of highly flexible complexes. Additionally, we demonstrate that by biasing backbone sampling particularly towards residues comprising flexible loops or hinge domains, highly flexible targets can be predicted to under 2 Å accuracy. This indicates that additional gains are possible when mobile protein segments are known. Significance Statement: Proteins bind each other in a highly specific and regulated manner, and these associated dynamics of binding are intimately linked to their function. Conventional techniques of structure determination such as cryo-EM, X-ray crystallography and NMR are time-consuming and arduous. Using a temperature-replica exchange Monte Carlo approach that mimics the kinetic mechanism of “induced fit” binding, we improved prediction of protein complex structures, particularly for targets that exhibit considerable conformational changes upon binding (Interface root mean square deviation (unbound-bound) > 1.2 Å. Capturing these binding-induced conformational changes in proteins can aid us in better understanding biological mechanisms and suggest intervention strategies for disease mechanisms.

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Metadata

Authors
Harmalkar, A., Mahajan, S. P., & Gray, J. J.
Affiliations
Johns Hopkins University (US)
Corresponding author
Gray, Jeffrey J.
Venue
PLoS Computational Biology
Publisher
openRxiv
Published
2021-12-10
Volume
18
Issue
6
Pages
e1010124-e1010124
ISSN
1553-734X (ISSN-L)
OpenAlex
W4281708617
Cited by
16
References
1
Citations by year
2026: 1 · 2025: 8 · 2024: 3 · 2023: 4
FWCI
1.22
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Johns Hopkins University
  • National Institutes of Health
  • National Institute of General Medical Sciences (R01GM078221, R35GM141881)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
protein complex structure prediction, induced fit, parallel tempering, protein-protein docking, Rosetta
MeSH terms
Monte Carlo Method, Protein Binding, Protein Conformation, Proteins

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