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Induced fit with replica exchange improves protein complex structure prediction
Open accessPreprint — 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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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Research works printed but not linked: 47
- 2021, D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions, Cell Syst, 12, 969, 10.1016/j.cels.2021.08.010 · DOI
- 2020, Advances to tackle backbone flexibility in protein docking, Curr. Opin. Struct. Biol, 67, 178
- 2019, Modeling protein-protein, protein-peptide, and protein-oligosaccharide complexes: CAPRI, Proteins: Struct. Funct. Bioinforma, -, 1
- 2019, Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment, Proteins: Struct. Funct. Bioinforma, 87, 1200, 10.1002/prot.25838 · DOI · Paper page
- 10.1371/journal.pone.0162755 · DOI
- 10.1371/journal.pone.0022477 · DOI
- 2017, Monte Carlo replica-exchange based ensemble docking of protein conformations, Proteins: Struct. Funct. Bioinforma, 85, 924, 10.1002/prot.25262 · DOI
- 2010, SwarmDock and the use of normal modes in protein-protein docking, Int. journal molecular sciences, 11, 3623, 10.3390/ijms11103623 · DOI
- 2015, iATTRACT: Simultaneous global and local interface optimization for protein-protein docking refinement, Proteins: Struct. Funct. Bioinforma, 83, 248, 10.1002/prot.24728 · DOI
- 2012, Flexible protein docking refinement using pose-dependent normal mode analysis, Proteins: Struct. Funct. Bioinforma, 80, 2262, 10.1002/prot.24115 · DOI
- 10.1093/bioinformatics/bty355 · DOI · Paper page
- 10.1016/j.jmb.2008.05.042 · DOI
- 2011, Conformational selection or induced fit? 50 years of debate resolved, F1000 biology reports, 3, 19
- 10.1021/bi3006913 · DOI
- 2010, FiberDock: Flexible induced-fit backbone refinement in molecular docking, Proteins: Struct. Funct. Bioinforma, 78, 1503, 10.1002/prot.22668 · DOI
- 10.1016/j.str.2016.06.025 · DOI
- 10.1016/j.jmb.2007.07.050 · DOI
- 2014, Enhanced sampling in molecular dynamics using metadynamics, replica-exchange, and temperature-acceleration, Entropy, 16, 163
- M Luitz , R Bomblies , K Ostermeir , M Zacharias , Exploring biomolecular dynamics and interactions using advanced sampling methods. J. Phys. Condens. Matter 27(2015). · DOI
- 10.1038/nchem.2785 · DOI
- 2013, Replica Exchange Improves Sampling in Low-Resolution Docking Stage of RosettaDock, PLoS ONE, 8, e72096, 10.1371/journal.pone.0072096 · DOI
- 2019, Holo-like and Druggable Protein Conformations from Enhanced Sampling of Binding Pocket Volume and Shape, J. Chem. Inf. Model, 59, 1515, 10.1021/acs.jcim.8b00730 · DOI
- 2019, Refinement of protein-protein complexes in contact map space with metadynamics simulations, Proteins: Struct. Funct. Bioinforma, 87, 12, 10.1002/prot.25612 · DOI · Paper page
- 2019, Atomic-level characterization of protein–protein association, Proc. Natl. Acad. Sci. United States Am, 116, 4244, 10.1073/pnas.1815431116 · DOI
- 2020, Prediction of protein–protein complexes using replica exchange with repulsive scaling, J. Comput. Chem, -, 1436, 10.1002/jcc.26187 · DOI
- 2015, Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta, PLOS ONE, 10, e0125941, 10.1371/journal.pone.0125941 · DOI
- K Ostermeir , M Zacharias , Accelerated flexible protein-ligand docking using Hamiltonian replica exchange with a repulsive biasing potential. PLoS ONE 12(2017). · DOI
- 10.1016/j.jmb.2015.07.016 · DOI · Paper page
- 2008, Backrub-like backbone simulation recapitulates natural protein conformational variability and improves mutant side-chain prediction, J. molecular biology, 380, 742, 10.1016/j.jmb.2008.05.023 · DOI
- 1995, Understanding the metropolis-hastings algorithm, The Am. Stat, 49, 327, 10.1080/00031305.1995.10476177 · DOI
- 2017, Computational design of self-assembling cyclic protein homo-oligomers, Nat. Chem, 9, 353, 10.1038/nchem.2673 · DOI
- 10.1038/nprot.2016.169 · DOI
- 10.1093/bioinformatics/btu097 · DOI
- 10.1016/j.jmb.2006.06.012 · DOI
- 10.1016/j.molcel.2004.12.023 · DOI
- 2006, PIPER: An FFT-based protein docking program with pairwise potentials, Proteins: Struct. Funct. Bioinforma, 65, 392, 10.1002/prot.21117 · DOI · Paper page
- D Varela , I André , a Memetic Algorithm Enables Global All - Atom Protein - Protein Docking With Sidechain Flexibility. bioRxiv (2021). · DOI
- R Evans , et al., Protein complex prediction with AlphaFold-Multimer. bioRxiv (2021). · DOI · Paper page
- 10.1038/nsb0698-422 · DOI
- 2017, Sense and simplicity in HADDOCK scoring: Lessons from CASP-CAPRI round 1, Proteins: Struct. Funct. Bioinforma, 85, 417, 10.1002/prot.25198 · DOI
- 2011, Accelerating protein docking in ZDOCK using an advanced 3D convolution library, PLoS ONE, 6, 0
- 10.1016/j.copbio.2009.07.006 · DOI
- 2020, Protein docking and steered molecular dynamics suggest alternative phospholamban-binding sites on the SERCA calcium transporter, The J. biological chemistry, 295, 11262, 10.1074/jbc.RA120.012948 · DOI
- 2012, Level Accuracy, Science, 828, 1171
- 10.1038/nature13404 · DOI
- 2018, Selective targeting of engineered T cells using orthogonal IL-2 cytokine-receptor complexes, Sci. (New York, N.Y.), 359, 1037, 10.1126/science.aar3246 · DOI
- 10.1002/prot.10393 · DOI
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)
- PMC
- PMC9200320
- 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
- gold
- doi.org
- 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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