Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement

PLoS Computational Biology - Tập 11 Số 7 - Trang e1004404
Hanyang Jiang1,2, Fu Kit Sheong3, Lizhe Zhu4,3,2, Xin Gao5, Julie Bernauer6,7, Xuhui Huang1,4,3,2
1Bioengineering Graduate Program, Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
2The HKUST Shenzhen Research Institute, Shenzhen, China
3Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
4Center of Systems Biology and Human Health, School of Science and Institute for Advance Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
5Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
6Inria Saclay-Île de France, Bâtiment Alan Turing, Campus de l’École Polytechnique, Palaiseau, France
7Laboratoire d’Informatique de l’École Polytechnique (LIX), CNRS UMR 7161, École Polytechnique, Palaiseau, France

Tóm tắt

Từ khóa


Tài liệu tham khảo

AJ Pratt, 2009, The RNA-induced Silencing Complex: A Versatile Gene-silencing Machine, J Biol Chem, 284, 17897, 10.1074/jbc.R900012200

DJ Obbard, 2009, The evolution of RNAi as a defence against viruses and transposable elements, Philos Trans R Soc, 364, 99, 10.1098/rstb.2008.0168

DG Sashital, 2010, Structural insights into RNA interference, Curr Opin Struct Biol, 20, 90, 10.1016/j.sbi.2009.12.001

RC Wilson, 2013, Molecular Mechanisms of RNA Interference, Annu Rev Biophys, 42, 217, 10.1146/annurev-biophys-083012-130404

FV Rivas, 2005, Purified Argonaute2 and an siRNA form recombinant human RISC, Nat Struct Mol Biol, 12, 340, 10.1038/nsmb918

T Kawamata, 2010, Making RISC, Trends Biochem Sci, 35, 368, 10.1016/j.tibs.2010.03.009

L Joshua-Tor, 2011, Ancestral Roles of Small RNAs: An Ago-Centric Perspective, Cold Spring Harbor Perspect Biol, 3, a003772, 10.1101/cshperspect.a003772

HM Sasaki, 2012, The true core of RNA silencing revealed, Nat Struct Mol Biol, 19, 657, 10.1038/nsmb.2302

G Meister, 2013, Argonaute proteins: functional insights and emerging roles, Nat Rev Genet, 14, 447, 10.1038/nrg3462

YL Wang, 2008, Structure of an argonaute silencing complex with a seed-containing guide DNA and target RNA duplex, Nature, 456, 921, 10.1038/nature07666

YL Wang, 2009, Nucleation, propagation and cleavage of target RNAs in Ago silencing complexes, Nature, 461, 754, 10.1038/nature08434

YL Wang, 2008, Structure of the guide-strand-containing argonaute silencing complex, Nature, 456, 209, 10.1038/nature07315

BP Lewis, 2005, Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets, Cell, 120, 15, 10.1016/j.cell.2004.12.035

A Azuma-Mukai, 2008, Characterization of endogenous human Argonautes and their miRNA partners in RNA silencing, Proc Natl Acad Sci U S A, 105, 7964, 10.1073/pnas.0800334105

A Turchinovich, 2012, Distinct AGO1 and AGO2 associated miRNA profiles in human cells and blood plasma, RNA Biol, 9, 1066, 10.4161/rna.21083

A Dueck, 2012, microRNAs associated with the different human Argonaute proteins, Nucleic Acids Res, 40, 9850, 10.1093/nar/gks705

A Esquela-Kerscher, 2008, The let-7 microRNA reduces tumor growth in mouse models of lung cancer, Cell Cycle, 7, 759, 10.4161/cc.7.6.5834

P Trang, 2009, Regression of murine lung tumors by the let-7 microRNA, J Thorac Oncol, 29, 1580

JA Broderick, 2011, MicroRNA therapeutics, Gene Ther, 18, 1104, 10.1038/gt.2011.50

GG Hammes, 2009, Conformational selection or induced fit: A flux description of reaction mechanism, Proc Natl Acad Sci U S A, 106, 13737, 10.1073/pnas.0907195106

P Csermely, 2010, Induced fit, conformational selection and independent dynamic segments: an extended view of binding events, Trends Biochem Sci, 35, 539, 10.1016/j.tibs.2010.04.009

H Frauenfelder, 1991, The Energy Landscapes and Motions of Proteins, Science, 254, 1598, 10.1126/science.1749933

BY Ma, 1999, Folding funnels and binding mechanisms, Protein Eng, 12, 713, 10.1093/protein/12.9.713

CJ Tsai, 1999, Folding funnels, binding funnels, and protein function, Protein Sci, 8, 1181, 10.1110/ps.8.6.1181

DE Koshland, 1958, Application of a Theory of Enzyme Specificity to Protein Synthesis, Proc Natl Acad Sci U S A, 44, 98, 10.1073/pnas.44.2.98

CD Mackereth, 2011, Multi-domain conformational selection underlies pre-mRNA splicing regulation by U2AF, Nature, 475, 408, 10.1038/nature10171

JP DiNitto, 2003, Mutual induced fit binding of Xenopus ribosomal protein L5 to 5 S rRNA, J Mol Biol, 330, 979, 10.1016/S0022-2836(03)00685-5

DD Boehr, 2009, The role of dynamic conformational ensembles in biomolecular recognition, Nat Chem Biol, 5, 789, 10.1038/nchembio.232

HX Zhou, 2010, From induced fit to conformational selection: a continuum of binding mechanism controlled by the timescale of conformational transitions, Biophys J, 98, L15, 10.1016/j.bpj.2009.11.029

N Greives, 2014, Both protein dynamics and ligand concentration can shift the binding mechanism between conformational selection and induced fit, Proc Natl Acad Sci U S A, 111, 10197, 10.1073/pnas.1407545111

K Nakanishi, 2012, Structure of yeast Argonaute with guide RNA, Nature, 486, 368, 10.1038/nature11211

E Elkayam, 2012, The Structure of Human Argonaute-2 in Complex with miR-20a, Cell, 150, 233, 10.1016/j.cell.2012.06.021

CR Faehnle, 2013, The Making of a Slicer: Activation of Human Argonaute-1, Cell Rep, 3, 1901, 10.1016/j.celrep.2013.05.033

K Nakanishi, 2013, Eukaryote-Specific Insertion Elements Control Human ARGONAUTE Slicer Activity, Cell Rep, 3, 1893, 10.1016/j.celrep.2013.06.010

A Deerberg, 2013, Minimal mechanistic model of siRNA-dependent target RNA slicing by recombinant human Argonaute 2 protein, Proc Natl Acad Sci U S A, 110, 17850, 10.1073/pnas.1217838110

YH Wang, 2010, Mechanism of MicroRNA-Target Interaction: Molecular Dynamics Simulations and Thermodynamics Analysis, PLoS Comput Biol, 6, e1000866, 10.1371/journal.pcbi.1000866

Z Xia, 2012, Molecular dynamics simulations of Ago silencing complexes reveal a large repertoire of admissible 'seed-less' targets, Sci Rep, 2, 569, 10.1038/srep00569

Z Xia, 2013, Large Domain Motions in Ago Protein Controlled by the Guide DNA-Strand Seed Region Determine the Ago-DNA-mRNA Complex Recognition Process, Plos One, 8, e54620, 10.1371/journal.pone.0054620

F Noe, 2008, Transition networks for modeling the kinetics of conformational change in macromolecules, Curr Opin Struct Biol, 18, 154, 10.1016/j.sbi.2008.01.008

JD Chodera, 2007, Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics, J Chem Phys, 126, 155101, 10.1063/1.2714538

F Morcos, 2010, Modeling conformational ensembles of slow functional motions in Pin1-WW, PLoS Comput Biol, 6, e1001015, 10.1371/journal.pcbi.1001015

NV Buchete, 2008, Coarse master equations for peptide folding dynamics, J Phys Chem B, 112, 6057, 10.1021/jp0761665

W Zheng, 2007, Simulating replica exchange simulations of protein folding with a kinetic network model, Proc Natl Acad Sci U S A, 104, 15340, 10.1073/pnas.0704418104

AC Pan, 2008, Building Markov state models along pathways to determine free energies and rates of transitions, J Chem Phys, 129, 064107, 10.1063/1.2959573

JH Prinz, 2011, Markov models of molecular kinetics: Generation and validation, J Chem Phys, 134, 174105, 10.1063/1.3565032

Schütte C, Huisinga W (2000) Biomolecular Conformations as Metastable Sets of Markov Chains. Proceedings of the 38th Annual Allerton Conference on Communication, Control, and Computing. pp. 1106–1115.

D Gfeller, 2007, Complex network analysis of free-energy landscapes, Proc Natl Acad Sci U S A, 104, 1817, 10.1073/pnas.0608099104

G Perez-Hernandez, 2013, Identification of slow molecular order parameters for Markov model construction, J Chem Phys, 139, 015102, 10.1063/1.4811489

A Jain, 2012, Identifying Metastable States of Folding Proteins, J Chem Theory Comput, 8, 3810, 10.1021/ct300077q

GR Bowman, 2009, Using generalized ensemble simulations and Markov state models to identify conformational states, Methods, 49, 197, 10.1016/j.ymeth.2009.04.013

Huang X, Yao Y, Bowman GR, Sun J, Guibas LJ, et al. (2010) Constructing multi-resolution Markov State Models (MSMs) to elucidate RNA hairpin folding mechanisms. Pac Symp Biocomput: 228–239.

X Huang, 2009, Rapid equilibrium sampling initiated from nonequilibrium data, Proc Natl Acad Sci U S A, 106, 19765, 10.1073/pnas.0909088106

LT Da, 2012, Dynamics of pyrophosphate ion release and its coupled trigger loop motion from closed to open state in RNA polymerase II, J Am Chem Soc, 134, 2399, 10.1021/ja210656k

F Noe, 2009, Constructing the equilibrium ensemble of folding pathways from short off-equilibrium simulations, Proc Natl Acad Sci U S A, 106, 19011, 10.1073/pnas.0905466106

GR Bowman, 2011, Taming the complexity of protein folding, Curr Opin Struct Biol, 21, 4, 10.1016/j.sbi.2010.10.006

JD Chodera, 2014, Markov state models of biomolecular conformational dynamics, Curr Opin Struct Biol, 25, 135, 10.1016/j.sbi.2014.04.002

AM Razavi, 2014, Computational Screening and Selection of Cyclic Peptide Hairpin Mimetics by Molecular Simulation and Kinetic Network Models, J Chem Inf Model, 54, 1425, 10.1021/ci500102y

W Zhuang, 2011, Simulating the T-Jump-Triggered Unfolding Dynamics of trpzip2 Peptide and Its Time-Resolved IR and Two-Dimensional IR Signals Using the Markov State Model Approach, J Phys Chem B, 115, 5415, 10.1021/jp109592b

VA Voelz, 2010, Molecular simulation of ab initio protein folding for a millisecond folder NTL9(1–39), J Am Chem Soc, 132, 1526, 10.1021/ja9090353

I Buch, 2011, Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations, Proc Natl Acad Sci U S A, 108, 10184, 10.1073/pnas.1103547108

S Doerr, 2014, On-the-Fly Learning and Sampling of Ligand Binding by High-Throughput Molecular Simulations, J Chem Theory Comput, 10, 2064, 10.1021/ct400919u

C Dominguez, 2003, HADDOCK: a protein-protein docking approach based on biochemical or biophysical information, J Am Chem Soc, 125, 1731, 10.1021/ja026939x

SJ de Vries, 2007, HADDOCK versus HADDOCK: new features and performance of HADDOCK2.0 on the CAPRI targets, Proteins: Struct, Funct, Bioinf, 69, 726, 10.1002/prot.21723

SJ Fleishman, 2011, Community-wide assessment of protein-interface modeling suggests improvements to design methodology, J Mol Biol, 414, 289, 10.1016/j.jmb.2011.09.031

FK Sheong, 2015, Automatic state Partitioning for Multi-body systems (APM): An Efficient Algorithm for Constructing Markov State Models to Elucidate Conformational Dynamics of Multi-body Systems, J Chem Theory Comput, 11, 17, 10.1021/ct5007168

T Wlodarski, 2009, Conformational selection and induced fit mechanism underlie specificity in noncovalent interactions with ubiquitin, Proc Natl Acad Sci U S A, 106, 19346, 10.1073/pnas.0906966106

DA Silva, 2011, A Role for Both Conformational Selection and Induced Fit in Ligand Binding by the LAO Protein, PLoS Comput Biol, 7, e1002054, 10.1371/journal.pcbi.1002054

S Rudel, 2011, Phosphorylation of human Argonaute proteins affects small RNA binding, Nucleic Acids Res, 39, 2330, 10.1093/nar/gkq1032

A Mazumder, 2013, A transient reversal of miRNA-mediated repression controls macrophage activation, EMBO Rep, 14, 1008, 10.1038/embor.2013.149

A Sali, 1993, Comparative Protein Modeling by Satisfaction of Spatial Restraints, J Mol Biol, 234, 779, 10.1006/jmbi.1993.1626

A Fiser, 2000, Modeling of loops in protein structures, Protein Sci, 9, 1753, 10.1110/ps.9.9.1753

MA Marti-Renom, 2000, Comparative protein structure modeling of genes and genomes, Annu Rev Biophys Biomol Struct, 29, 291, 10.1146/annurev.biophys.29.1.291

Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, et al. (2006) Comparative protein structure modeling using Modeller. Curr Protoc Bioinformatics Chapter 5: Unit 5.6.

H Berendsen, 1981, Intermolecular Forces, 331

B Hess, 2008, GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation, J Chem Theory Comput, 4, 435, 10.1021/ct700301q

K Lindorff-Larsen, 2010, Improved side-chain torsion potentials for the Amber ff99SB protein force field, Proteins: Struct, Funct, Bioinf, 78, 1950, 10.1002/prot.22711

T Darden, 1993, Particle Mesh Ewald—an N.Log(N) Method for Ewald Sums in Large Systems, J Chem Phys, 98, 10089, 10.1063/1.464397

B Hess, 1997, LINCS: A linear constraint solver for molecular simulations, J Comput Chem, 18, 1463, 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H

G Bussi, 2007, Canonical sampling through velocity rescaling, J Chem Phys, 126, 014101, 10.1063/1.2408420

M Parrinello, 1981, Polymorphic Transitions in Single-Crystals—a New Molecular-Dynamics Method, J Appl Phys, 52, 7182, 10.1063/1.328693

TF Gonzalez, 1985, Clustering to Minimize the Maximum Intercluster Distance, Theor Comput Sci, 38, 293, 10.1016/0304-3975(85)90224-5

AY Ng, 2002, On spectral clustering: Analysis and an algorithm, Adv Neural Inf Process Syst, 14, 849

K Rother, 2011, RNA and protein 3D structure modeling: similarities and differences, J Mol Model, 17, 2325, 10.1007/s00894-010-0951-x

AT Brunger, 1998, Crystallography &amp; NMR system: A new software suite for macromolecular structure determination, Acta Crystallogr, Sect D: Biol Crystallogr, 54, 905, 10.1107/S0907444998003254

AT Brunger, 2007, Version 1.2 of the Crystallography and NMR system, Nat Protoc, 2, 2728, 10.1038/nprot.2007.406

JP Linge, 1999, Influence of non-bonded parameters on the quality of NMR structures: A new force field for NMR structure calculation, J Biomol NMR, 13, 51, 10.1023/A:1008365802830

JP Linge, 2003, Refinement of protein structures in explicit solvent, Proteins: Struct, Funct, Bioinf, 50, 496, 10.1002/prot.10299

WL Jorgensen, 1988, The Opls Potential Functions for Proteins—Energy Minimizations for Crystals of Cyclic-Peptides and Crambin, J Am Chem Soc, 110, 1657, 10.1021/ja00214a001

MF Lensink, 2007, Docking and scoring protein complexes: CAPRI 3rd edition, Proteins: Struct, Funct, Bioinf, 69, 704, 10.1002/prot.21804