wah chiu, professor...lecture outline •de novo model building of a 3.3 Åmap •validation of...

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NIH U24GM129564 Wah Chiu, Professor

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  • NIH U24GM129564

    Wah Chiu, Professor

  • https://commonfund.nih.gov/CryoEM

    Created with funding from the NIH Common Fund –the three Centers interact and coordinate activities

    The Cryo-EM National Centers

    https://cryoem.slac.stanford.edu/s2c2/

    SLAC National Accelerator Laboratory, Stanford University,

    Menlo Park, CA

    PI: Wah Chiu

    Oregon Health and ScienceUniversity and Pacific Northwest

    National Laboratory, Portland, OR

    https://pncc.labworks.org/

    PI: Eric Gouaux

    http://nccat.nysbc.org/

    New York Structural Biology Center, New York, NY

    PI: Bridget Carragher

    National Center for CryoEM Access and Training

  • Cryo-EM Statistics

  • Lecture Outline

    • De novo model building of a 3.3 Å map

    • Validation of model with mass spectroscopy of a 3.5 Å map

    • Detection of water and their validation of a 2.7 Å map

    • Structure details of a 1.34 Å map

    • Cryo-EM structure Challenge with the community

  • Direct Electron Detector (DE20) Image of P22 Phages

    D Chen & J Jakana, 2015

    • 300 keVJEM3200FSC

    • 0.85 µm defocus

    • 1.07Å/pixel

    • 1.56e/Å2/frame

    • Motion corrected and damage weighted

  • 2 Independent Maps from 2 Data Subsets and 2 Initial Models

    Subset 1, N=11,000

    Subset 2, N=11,000

    Map 1

    Map 2

    EMAN2, MPSA, JSPR Hryc, Chen et al PNAS 2017

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    Four

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    elat

    ion

    Frequency (1/Å)

    Gold-standard FSC (FSCg)

    3.3Å

    FSC =(F1å • F2* )F1

    2 • F22

    Estimate CryoEM Map Resolution with 2 Independent Maps

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    ion

    Frequency (1/Å)

    4.5Å-phase-randomized FSC (FSCn)

    Gold-standard FSC (FSCg)

    True FSC (FSCt)

    0.143

    4.3Å4.5Å

    3.3Å

    c

    Hryc, Chen et al PNAS 2017

    FSC =(F1å • F2* )F1

    2 • F22

    Phase Randomization of Images at ¾ of Claimed resolution

  • 3.3 Å Cryo-EM Map of P22 Bacteriophage

    Hryc, Chen et al PNAS 2017

  • De Novo Model of Single Protein Subunit of P22 Phage

    Hryc, Chen et al PNAS 2017

  • Full Atom Modeling of Single Protein Subunit of P22 Phage

    Hryc, Chen et al PNAS 2017

  • THR98

    ARG102

    TYR100 ARG103

    ARG109

    LEU111

    ASN113 GLU116

    LYS118

    MET122

    ALA120

    MET126

    Long Helix

    LYS377THR379

    PHE392

    THR394

    PHE381

    ASP83ASP85

    PHE87

    LEU409

    SER382

    P-Domain

    MET49

    PRO50

    TRP48

    ILE47

    ARG42

    GLN41

    PRO36TYR33

    F-Loop

    TRP61

    GLU59

    GLN58

    ASP56

    THR68

    THR64

    ASP62

    GLU54

    E-Loop

    A-Domain

    GLN173

    TYR175

    GLY179

    TYR177 TYR180

    LEU182

    LYS184

    Structural Details of P22 Phage Capsid Protein

    Hryc, Chen et al PNAS 2017

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    urie

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    Spatial Frequency (1/Å)

    Even Map vs. EvenModel

    3.4Å0

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    Spatial Frequency (1/Å)

    Even Map vs. EvenModel

    Odd Map vs. EvenModel

    3.4Å

    Model Validation: 2 Independent Maps

    Map 1 (Even)

    Map 2 (Odd) Hryc, Chen et al PNAS 2017

  • Penton

    Hexon

    Models of 7 Subunits in an AU of P22 Phage A B

    C

    18.2Å 0 ÅD

    Hryc et al PNAS 2017

  • Fit-to-density for an Asymmetric Unit (7 individual subunits)

    Cross-correlation: 0.836 EMRinger Score: 3.58

    MolProbity (of an asymmetric unit)

    All-Atom ContactsClashscore, All Atoms 10.26 97th percentile * (N=37, 3Å-9999Å)

    Clashscore is the number of steric overlaps (>0.4Å) per 1000 atoms.

    Protein Geometry

    Poor rotamers 0 0.00% Goal: 0.25Å 0 0.00% Goal: 0%

    Bad backbone bonds: 0/23401 0.00% Goal: 0%

    Bad backbone angles: 4/31815 0.01% Goal:

  • Map-Derived Model

    Experimental Map

    Representation of Cryo-EM Map & Model

    Calculated Map from Model

    Apply Weights

    Map-Derived Model

    Weighted Map

    Calculated Map from Model

    25 Å2115ADP

  • Interactions Between Adjacent Subunits Within a Hexon or a Penton Via Salt Bridges

    8 interactions per adjacent subunits Hryc, Chen et al PNAS 2017

  • CryoEM Image of Vo Channel (330 kDa) Biochemically Extracted from Yeast Vacuole

    Osteoporosis/petrosisRenal tubular acidosisDiabetesNeurodegenerationPathogen entryCancer

    pH HomeostasisDevelopmentEndocytosismTOR signalingNotch signalingProtein sorting/trafficking

    150,000 channel particles recorded in JEM3200 and K2Roh, Wilkens et al. Mol Cell 2018

    V1 Motor - ATPase

    VO Proton Channel Mobile Rotor

  • 3.5 Å Cryo-EM Map of Vo Channel (330 kDa)

    Roh, Wilkens et al. 2018 Mol Cell

  • 180°

    Cytoplasm

    Lumen

    Rotor (c-ring)

    Proton channel (a)

    Connecting adaptor (d)

    Full Atomic Models for 14 Protein Subunits of Vo Channel

    Accessary (e/f)

    Roh, Wilkens et al. Mol Cell 2018

  • Helix with an Unknown Biochemical Identity in V0 Channel

    90°?

    Roh, Wilkens et al. Mol Cell 2018

  • Mass-spec Identified the Assembly Factor Voa1

    Roh, Wilkens et al. Mol Cell 2018

  • Roh, Wilkens et al. Mol Cell 2018

    Function of Voa1

  • V0NDa

    d

    c”NT

    f

    C-Term Voa1 is a Component of the V0 Channel Rotor

    Roh, Wilkens et al. Mol Cell 2018

    V0ND (voa1△)a

    d

    c”NT

    f

  • 2.7 Å Cryo-EM Structure of V0 Channel

    Roh, Wilkens et al. Science Adv (2020) accepted

  • Validation of Water in the Channel with MD Simulation

    Roh, Wilkens et al. Science Adv (2020) acceptedWater Finders program (Coot); Q score (Pintilie, Nat Methods, 2020)Distance between H20 and O and N atoms

  • Validation of Water in the Channel Bridging Q80 Sidechain Nitrogen and V7 Carbonyl Oxygen in 10 c-Ring proteins

    Roh, Wilkens et al. Science Adv (2020) accepted

  • 1.34 Å Cryo-EM Map of Apoferritin (Krios-BioQ-K3)

    (Å)

    -0.2

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    Four

    ierS

    hell

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    rela

    tion

    (FSC

    )

    0.143 FSC 1.34 Å

    200 Å

    6

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    0.2 0.3 0.4 0.5

    Ln(N

    umbe

    r of

    Par

    ticle

    s)

    1/Resolution2 (Å-2)

    Particle Number VS Resolution

    Kaiming Zhang, Stanford, unpublished

    FSC =(F1å • F2* )F1

    2 • F22

    ~900,000 ParticlesRelion

    Rosenthal &Henderson (2003) JMB

  • Side Chain Densities of 1.34 Å Cryo-EM Map of Apoferritin

    His118

    Asp126

    Phe51

    Asn25 Val33

    Met158 Lys108

    Arg9

    ChargedHydrophobicPolar

    Thr153

    Gln73 Ile80

    Pro127

    Glu167

    Cys130

    Leu155

    Trp93

    Ala52

    Gly149Ser31

    Tyr32

    Side chains with alternate conformations

    Glu64

    a b

    Gln14 Cys102Lys49 Lys53

    a b a bab

    ca b a b

    Glu61 Glu94

    a b

    Arg156

    a b

    Asn Val

    Pintilie, Li, Zhang et al. (unpublished)

  • Water Finder in 1.34 Å Cryo-EM Map of Apoferritin

    05101520253035404550

    0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 3.6 4.0

    H2O-NH2O-O

    Distance (Å)

    Waters found in the 1.34 ÅcryoEM Map with

    Water Finder232

    Water Molecules in X-ray mapPDB:3ajo. 229

    Pintilie, Li, Zhang et al. (unpublished)

  • 05101520253035404550

    0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 3.6 4.0

    H2O-NH2O-O

    Distance (Å)

    Waters found in the 1.34 ÅcryoEM Map with

    Water Finder. 232

    Water Finder in cryoEM mapPDB:3ajo in Xray map

    Water Finder in 1.34 Å Cryo-EM Map of Apoferritin

    Pintilie, Li, Zhang et al. (unpublished)

  • 2019 Model Challenge Targets

    ADH 2.9 ÅAPOF 1.8 Å APOF 2.3 Å APOF 3.1 Å

    EMD-20026additional map #1

    EMD-20027additional map #2

    EMD-20028additional map #2

    EMD-0406primary map

    BIORXIV/2020/147033

  • 2019 Challenge: 4 Metrics Stood Out

    CaBLAM: virtual dihedrals based on Cɑ, C=O compared to statistics from high quality PDB models [Williams 2018]

    Coordinates alone:

    MAPQ Q-score: Per-atom Correlation vs Reference Gaussian (r=0-2 Å) [Pintilie 2020]

    PHENIX Resolution Map-Model FSC = 0.5 [Afonine 2018]

    EMRinger Z-score “rotamericity” of map for protein Cgatom paths around c1 [Barad 2015]

    Fit-to-Map:

    BIORXIV/2020/147033

  • 2019 Model Challenge Results

  • AcknowledgementsM.I.T.: Cammie Haase-Pettingell, Jon King

    SUNY: Nicholas Stam, Stephan Wilkens

    Arizona State University/University of Illinois: Mrinal Shekhar, Chris Chipot, Abhishek Singharoy

    Rutgers University: Catherine Lawson, Helen Berman

    UC Davis: Andriy Kryshtafovych

    Chiu lab

    Corey Hryc (Industry)

    DongHua Chen (Stanford U)

    Soung Hun Roh (National Seoul U)

    Greg Pintilie (Stanford U)

    Kaiming Zhang (Stanford U)

    Shanshan Li (Stanford U)

    Michael Schmid (Stanford U)

    NIGMS