Protein dynamics - Biomolecular Engineering Laboratory
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Protein dynamics at a single molecule level Protein dynamics • Proteins are in motion, sampling the ensemble of different conformations • Energy landscape: Conformational space that a protein can explore - Relative population of different conformational states - Rates of inter-conversion Key biological processes occur on μs to ms scale - Recognition of cognate ligands - Signal transduction - Allosteric regulation of proteins - Enzyme catalysis Relatively long lifetimes - Individual states and kinetics of inter-conversion can be detected experimentally. Henzler-Wildman and Kern, Nature (2007) How do protein dynamics affect their functions? Signal transduction Molecular recognition Ubiquitin Forty-six crystal structures of ubiquitin: conformational dynamics control ubiquitin-protein interactions and influence in vivo signaling. Signals such as ligand binding, mutation, PTMs alter energy landscape, affecting relative population of conformations Enzyme catalysis and allosteric regulation - Active (green) and inactive (blue, red, yellow, and gray) conformations. - Allosteric ligand binding (cyan star) stabilizes the inactive conformation (red), inhibiting the enzyme activity. Lee and Craik, Science (2009) Molecular recognition • • The function of proteins depends on the recognition and binding of specific ligands ο Central to all biological processes Precise molecular recognition mechanism: Crucial for understanding biology at molecular level • Two textbook mechanisms: The protein exists in a single, stable conformation. - Lock-and-key model by Fischer (1894) - Induced-fit mechanism by Koshland (1958) Conformational dynamics and ligand binding • • Existence of conformational substates: Linkage between protein dynamics and molecular recognition Conformational selection model : Dynamics-coupled recognition mechanism • Induced-fit model Ligand binds a highly populated substate, inducing conformational change to a ligand-bound form. • Conformational selection model Ligand selectively binds a weakly populated substate, but no further structural change occurs. The role of conformational dynamics in molecular recognition remains controversial mainly owing to experimental limitations Single molecule FRET measurements Förster (or Fluorescence) Resonance Energy Transfer (FRET) • • • Non-radiative energy transfer from an energy donor to an acceptor Dipole – dipole interactions Energy transfer efficiency between two probes: - Degree of spectral overlap between donor emission and acceptor absorption - ~ 1 / (separation distance)6 - Effective distance : ~ 10 nm E = Ro6/ (Ro6 + R6) Ro : Förster distance at which the energy transfer is about 50% • • • • Analysis of biomolecular interactions Screening of inhibitors Detection of a target analyte Imaging (localization) Single-molecule FRET (smFRET) measurements Analysis of FRET at the level of single molecule which is labeled with a pair of dyes 1) Kinetic analysis of biomolecular interactions and conformational changes at a single molecule level Understanding the molecular mechanism Single-molecule FRET measurements Real-time kinetic analysis of the conformational dynamics of a protein at a single-molecule level Heterogeneous population Ensemble FRET Single-molecule FRET (Histogram of FRET) Counts (Bulk measurement) Counts Active, real molecules FRET efficiency FRET efficiency FRET efficiency FRET efficiency Dynamic behavior Time (s) Time (s) Kinetic rates in the absence and presence of increasing ligand concentration will provide crucial insight into the molecular recognition process Single molecule FRET analysis Answers to many of fundamental biological questions • • • • • • • • • • Real dynamic characteristics of proteins /enzymes Protein folding Conformational change of protein Replication Recombination Transcription Translation RNA folding and catalysis Motor proteins Signal transduction Expected kinetic rates for a molecular recognition process Induced-fit model The closing rate will be faster in the presence of a ligand than in its absence and will be accelerated by increasing ligand concentration. Conformational selection model The closing rates in the presence of a ligand will be the same as those with no ligand because the population of a ligand-binding conformer is limited by the intrinsic conformational transition rate. Kinetic rates by dwell time analysis Real-time changes in FRET efficiency The opening and closing rates Open lifetime Closed lifetime Acceptor bleaching Donor intensity Acceptor intensity Donor bleaching Intensity FRET efficiency Dwell time analysis Closed state Open state FRET efficiency Time (s) Estimation of average dwell time, τ EFRET = IA IA + ID Single exponential decay curve Counts Time (s) Histogram of dwell times of each state Time (s) ID: Donor intensity IA: Acceptor intensity The cπ₯π¨π¬π’π§π π«πππ = π ππ©ππ§ ππ°ππ₯π₯ ππ’π¦π (π) The oπ©ππ§π’π§π π«πππ = π ππ₯π¨π¬ππ ππ°ππ₯π₯ ππ’π¦π (π) Maltose binding protein (MBP) • • • • ATP-binding cassette (ABC) transporter in E. coli : active transport and chemotaxis Large conformational change upon ligand binding: Rotation > 30° at hinge region The highest binding affinity for maltotriose (Kd = ~ 1.6 X 10-7M) Mr = 40 kDa Maltose uptake in E. coli LamB M al LamB Outer membrane M al M al Inner membrane LamB Scheme for single-molecule FRET measurements Labeling of MBP 5.92 nm 5.04 nm Cy5 Cy3 Cy3 K34C Cy5 R354C + Maltose K34C R354C Prism-type Total Internal Reflection Fluorescence (TIRF) Microscope Intrinsic dynamics of wt-MBP 0 µM 0.5 µM 2 µM 10 µM • The intrinsic transition was too fast to detect owing to a low time resolution (~ 2 ms) • Maltose induced a structural change of wt-MBP MBP variants with hinge region mutations Changes in domain closure angles and binding affinity of the MBP by hinge region mutations N-domain 35° C-domain WT(0°) I329C(5.5°) I329W(9.5°) I329W/A96W(28.4°) WT(35°) Introduction of bulky amino acids into the hinge region ο Slow down the intrinsic conformational dynamics ο Allow the analysis of conformational dynamics using smFRET Millet et al., PNAS (2003) Labeling and evaluation of MBP wild-type Circular Dichroism (CD) analysis Amylose-binding assay 30000 Wild-type MBP Double Cys-MBP Labeled MBP ellipticity, mdeg 20000 MBP Double Cys-MBP (wild-type) (K34C, R354C) M L F W 10000 E L F W1 W2 E 100 75 0 50 -10000 35 -20000 25 -30000 200 210 220 230 240 Wavelength, nm 250 260 Cysteine mutations and dye labeling do not affect the folding and the maltose-binding activity of MBP Kim et al. Nature Chemical Biology (2013) Single and double mutants of MBP Real-time traces of MBP mutants Mutant construction Single mutant Double mutant High FRET: Partially closed state Low FRET : Open form • Detection of intrinsic dynamics of the mutants in the absence of a ligand • Transitions between two distinct conformations (open and partially closed forms) Kim et al. Nature Chemical Biology (2013) Maltose-induced effect on the single mutant of MBP Representative time traces • Maltose induced the clear conformational changes of MBP • The intrinsic transition rate could be measured in the absence of ligand Kim et al. Nature Chemical Biology (2013) Investigation of Single Mutant Construction of single mutant Histogram of FRET efficiency Maltose binding induces the population shift of the single mutant of MBP Kim et al. Nature Chemical Biology (2013) Ligand-binding kinetics of the single mutant Dwell time analysis of maltose binding Lifetime of open state Lifetime of the open state Lifetime of closed state The ligand-binding to MBP variant was governed by ligand-induced fit The first experimental evidence showing molecular recognition mechanism based on conformational dynamics analysis Investigation of double mutant similar to the partial closed form Construction of double mutant Histogram of FRET efficiency maltose maltose maltose * Partial closed form = 33.3° ± 6.7° Tang et al. (2007) Nature 449, 1078 maltose The ligand could bind to the partial closed form ο All conformers participate in the ligand binding. Kim et al. Nature Chemical Biology (2013) Representative time traces Intrinsic conformational dynamics of the mutants Relative population of the partially closed state Intrinsic opening rate (s-1) Intrinsic closing rate (s-1) Intrinsic transition rates • The partially closed states of the single and double mutants: 14% and 42% of the total population, respectively. • Double mutant showed much slower closing and opening rates than the single mutant Kim et al. Nature Chemical Biology (2013) Effect of ligand concentration on the kinetic rates of the mutants Representative time traces of the intensity and FRET efficiency for the single mutant Kinetic rates in the absence and presence of a ligand Closing rate Opening rate Single mutant Double mutant Wild- type • • The closing rate increased linearly with an increase in the ligand (maltose , maltotriose) concentration. The opening rate remained almost constant over the range of tested ligand concentrations. • Ligands bind preferentially to the open state, inducing a structural change to a closed form • Direct evidence for the induced-fit mechanism. Kim et al. Nature Chemical Biology (2013) Three-color smFRET using Cy7-maltose Direct quantification of the binding preference of a ligand to an open conformation 633 nm excitation 532 nm excitation Monitoring of the opening and closing dynamics through Cy3-Cy5 FRET or Cy5 intensity Tracking the binding of maltose through Cy7 intensity Binding to a Binding to an partially closed form open form E12 On state (closed form) E23 Off state (open form) Cy7-Maltose binding E13 Lee et al. PLoS ONE (2010) Maltose Binding On time Off time Cy7-Maltose binding (Cy5 ο Cy7) (Cy3 ο Cy7) Time (s) Synthesis of Cy7-maltose Synthesis of PEG-amine-linked maltose followed by conjugation with Cy7-mono NHS ester Mass spectrometry analyses PEG-amine maltose Cy7-maltose Kim et al. Nature Chemical Biology (2013) Cy7-maltose Three-color smFERT for the double mutant Simultaneous analysis of Cy7-maltose binding and conformational dynamics Open state Partially closed state Cy7-Maltose binding events : Jumps of Cy7 signal and concurrent drops of Cy5 signal Relative distribution of the FRET efficiencies (Cy3-Cy5) before the binding and after the dissociation of Cy7-maltose • Ligand binds both the open and partially closed conformations of the mutant • More than 80% of binding and dissociation events occurred in the open form, indicating a strong preference for the open conformation Kim et al. Nature Chemical Biology (2013) Energetic and parameters : Energies of a ligand binding and conformational change The existence of a partially closed form: critical role in the molecular recognition process Protein Ligand Binding energy, Δε (kcal/mol) maltose -7.45 ± 0.10 Wild-type MBP Single mutant (MBP-I329W) Double mutant (MBP-A96W/I329W) • • Energy of conformational change, εc (kcal/mol) 1.54 maltotriose -8.56 ± 0.12 maltose -9.25 ± 0.12 0.74 maltotriose -9.72 ± 0.25 maltose -10.43 ± 0.08 0.19 maltotriose -10.20 ± 0.12 Intrinsic dynamics facilitate a large conformational change that occurs upon sugar binding, with less energy expenditure Conformational dynamics have a role in facilitating the transition to a holo structure or in influencing the chemical step during enzyme catalysis Extended induced-fit model Ligands bind both a highly populated and weakly populated substates, inducing a structural transition to a ligand-bound, closed form. Interplay of conformational dynamics and binding affinity MBP mutants with varying binding affinity • The dissociation constants (Kd) were determined through ITC • Two orders of magnitude variation in Kd MBP mutants Seo et al. Nature Communications (2014) Mutation Kd (nM) Wild-type (WT) A96 I329 1102±65 AY A96 I329Y 22±6 AF A96 I329F 35±8 WI A96W I329 81±18 YI A96Y I329 218±23 FI A96F I329 492±50 WA A96W I329A 515±67 YA A96Y I329A 741±22 AR A96 I329R 905±50 AK A96 I329K 987±25 FA A96F I329A 989±37 Analysis of conformational dynamics of MBP variants by smFRET Partially closed Open kclosing kopening πΆππππππ ππππ = Cππππππ ππππ Calculation of transition rate by dwell time analysis = π ππππππ π ππππ ππππ (π) π ππππ π ππππ ππππ (π) Intrinsic dynamics of MBP mutants MBP mutants show different closed dwell times along with their Kd Cy5 Cy3 Seo et al. Nature Communications (2014) Intrinsic dynamics and binding affinity of MBP mutants Partially closed Open kclosing kopening Intrinsic opening rate directly dictates ligand-binding affinity Seo et al. Nature Communications (2014) Conformational energy and binding affinity of MBP mutants • The energy barrier between an open state and a partially closed state (EOο P.C., EP.C.ο O) determines the rate of inter-conversion (closing rate / opening rate) • Mutant with an increased energy level in an open substate : - Lower structural energy cost (Ec) for transition to a partially closed state, - Higher energy barrier (E‡P.C.ο O) for transition to an open state from a partially closed state, leading to a slower opening rate ο Higher binding affinity for a ligand Seo et al. Nature Communications (2014) Effect of a ligand on the transition rate Time traces and FRET histogram of a MBP mutant Open Variable Closed kclosing kopening Characteristic, constant Ligand dissociation is solely determined by the intrinsic opening rate Seo et al. Nature Communications (2014) Conclusions • A new platform based on FRET between QDs and AuNPs was well established • The FRET-based system were found to be simple and effective for high throughput assays of protein glycosylation and protease activity • Molecular beacon can be used for rapid detection of acquired drug resistance and potential biomarker in lung cancer, offering a way of personalized medicine • smFRET measurement enabled a kinetic analysis of conformational dynamics, providing direct evidence for the mechanism for ligand recognition and dissociation. • Intrinsic dynamics (opening rate) directly dictate the binding affinity for a ligand • The present approach will offer a new method to elucidate the molecular recognition and dissociation mechanisms of proteins with intrinsic dynamics, assisting in the design of more potent drugs and even proteins with new function. Acknowledgements KAIST Department of Biological Sciences Dr. Young-pil Kim Dr. Eunkeu Oh Dr. Young-Hee Oh Sung-Min Cho Dr. Eunkyung Kim Dr. Moon-Hyeong Seo Dr. Jung Min Choi Department of Chemistry Aram Jeon Prof. Hee-Seung Lee SungKyunkwan Univ. School of Medicine Dr. Young-Uk Kim Prof. KeunChil Park Seoul National Univ. Prof. Sungchul Hohng Dr. Sanghwa Lee Jeongbin Park Pennsylvania State Univ., USA Prof. D. D. Boehr The Uppsala Univ., Sweden Prof. S. Mowbray Ministry of Science, ICT & Future Planning - Pioneer Research Program for Converging Technology - BK 21 program - Creative Research Initiatives (S.H.) Collaborative works Flow of ideas ο¬Pennsylvania State ο¬University. ο¬U.S.A ο¬Weizmannο¬Institute ο¬of Science, ο¬Israel. κ³ ν΅ λΆλ΄ : 1 ( N=1, 2, 3, …) ο¬KIST 2 N ο¬KRIBB ο¬Pacific ο¬National Laboratory ο¬U.S.A κΈ°μ¨ : N2 μμΈλ μΈλ¦¬νκ³Ό κ³ λ €λ ν곡과 ο¬KAIST λ°μ΄μ€μμ€ν ( N=1, 2, 3, …) μμ° λ³μ ο¬μΌμ±λ³μ Biomolecular Engineering Lab. Biological role of intrinsic dynamics Protein Energy of conformational change (εc) (kcal/mol) Binding energy (Δε) (kcal/mol) Dissociation constants (Kd) (nM)a Dissociation Constants by ITC (Kd) (nM)b Wild-type 1.77 n.d.(maltose) - 8.91 (maltotriose) n.d.(maltose) 715 (maltotriose) 2180 (maltose) 1950 (maltotriose) Single mutant (I329W) 1.09 - 9.48 (maltose) - 9.82 (maltotriose) 99 (maltose) 56 (maltotriose) 48 (maltose) 53 (maltotriose) Double mutant (A96W/I329W) 0.19 - 10.39 (maltose) - 10.19 (maltotriose) 7.2 (maltose) 10 (maltotriose) 4.7 (maltose) 2.3 (maltotriose) a: The dissociation constants were determined from a hyperbolic Hill fit of the relative population of a closed state b: The dissociation constants were determined through ITC • Correlation between the structural energy costs and the dissociation constants observed in the three MBP mutants • The intrinsic dynamics of MBP facilitate a large conformational change that occurs upon sugar binding, which can be achieved with less energy expenditure Kim et al., Nature Chem. Biol. (2013) FRET efficiency calculation πΌππΊ is the gamma-corrected fluorescence intensity of the ith dye after whole correction steps when excited by the green laser πΌππ is the gamma-corrected fluorescence intensity of the ith dye after whole correction steps when excited by the red laser Lee S, Lee J, and Hohng S (2010) PLoS ONE 5(8): e12270 Estimation of FRET efficiencies on binding of Cy7-maltose to dual labeled wt-MBP Binding to an open form Binding to a closed form Cy7 Cy7 Cy5 23.0 Å Cy5 45.0 Å 60.1 Å C34_Cy3 C354_Cy5 C34_Cy5 C354_Cy3 22.8 Å 48.1 Å Cy3 Cy3 51.6 Å Distance (nm) FRET Efficiency C34_Cy3-Cy7 4.81 0.20 C354_Cy5-Cy7 2.28 1.00 C34_Cy3-Cy7 4.50 0.27 C354_Cy5-Cy7 2.30 1.00 C354_Cy3-Cy7 2.28 0.96 C34_Cy5-Cy7 4.81 0.82 C354_Cy3-Cy7 2.30 0.95 C34_Cy5-Cy7 4.50 0.87 closed form Cy3-Cy5 5.16 0.57 bound, open form Cy3-Cy5 6.01 0.34 closed form bound, open form closed form bound, open form Dynamics-coupled molecular recognition mechanism • Connection between the conformational dynamics and molecular recognition of proteins in the process of ligand binding • Role of conformational dynamics in molecular recognition remains controversial and elusive mainly owing to experimental limitations • Real-time kinetic analysis of the ligand binding and conformational dynamics • Single-molecule FRET analysis : Detection of inter-conversion rate upon ligand binding at the single-molecule level Regulation of ligand residence time Our previous study reveals that the opening rate of MBP is independent of ligand existence. Single mutant other reports, ligand binding affinity of the MBP variants is determined primarily by differences in the off-rate Double mutant ππππ = π1 πΏ + π−1 kobs = observed rate k1 = on-rate k-1 = off-rate Kim E. et al. (2013) Nature Chem. Biol. 9, 313 Marvin. et al. (2013) Nature Struc. Biol. 8(9), 795 We can modulate the protein dynamics by allosteric approach for optimizing ligand residence times to meet the desired pharmaceutical modulation of disease states (ligand residence times control the strength of regulatory process) Conclusion 1. Interactions between a protein and a ligand are essential to all biological processes. 2. MBP mutants constructed through hinge mutations were shown to have a wide range of intrinsic opening rates and dissociation constants for maltose. 3. Intrinsic opening rate of the protein dictates the ligand dissociation, and consequently determines the binding affinity for a ligand. 4. The residence time of a ligand has a significant effect on the signal transduction, regulatory processes, and drug responses. (1) The ligand residence time can be regulated by modulating the intrinsic dynamic characteristics. (2) The changes in the dynamic personalities of a protein by allosteric approach can modulate the ligand-binding affinity and vice versa. Interplay of conformational dynamics and ligand dissociation Intrinsic opening rate (s-1) Single mutant Kd = 48 nM ππππ = π1 πΏ + π−1 Double mutant Kd = 4.7 nM Kd : 7 ~ 1800 nM k1 (on-rate) : 10.8 ~ 18.2 (s-1) k-1 (off-rate) : 0 ~ 100 (s-1) A close correlation between the opening rate of MBPs and their binding affinity for a ligand The binding affinity of the MBP variants for a ligand is determined primarily by differences in the off-rate Kim et al., Nature Chem. Biol. (2013) Marvin et al., Nature Struc. Mol. Biol. (2001) Allosteric mutations of MBP ο Hinge mutations of MBP are known to significantly alter the binding affinity while maintaining the ligand-binding interfaces N-domain 35° C-domain WT(0°) I329C(5.5°) I329W(9.5°) I329W/A96W (28.4°) WT(35°) Millet et al., PNAS (2003) Recognition mechanism of MBP Induced-fit model Conformational selection model Structural difference between ligand-free and ligand-bound forms Existence of the minor partially closed species (~5%) in the absence of a ligand by NMR relaxation experiment Ligand-bound Ligand-free Tang et al., Nature (2007) Sharff et al., Biochem. (1992) Induced-fit or conformational selection model ?
