bioexcel webinar series #11: "robust solutions for cryo-em fitting and visualisation of...

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Robust solutions for cryoEM fitting and visualisation of interaction space

Presenters: Gydo van Zundertwith Mikael Trellet and Jörg Schaarschmidt

Host: Adam Carter

BioExcel Webinar Series

15 February, 2017

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Today’s PresenterGydo van Zundert studied Chemistry (BSc) and Nanomaterials (MSc) at Utrecht University, the Netherlands and obtained his PhD at the Computational Structural Biology group under the supervision of Prof. Alexandre Bonvin in 2015. His research focused on new methods and protocols for integrative modeling, such as cryo-electron microscopy integration in the HADDOCK macromolecular docking package. As of October 2016, he joined Schrodinger Inc. (NY) as a Postdoctoral Associate working on room-temperature crystallography modeling in collaboration with Stanford University and UCSF (CA).

6

Gydo van ZundertSchrodinger - SLAC Stanford – UCSF

Computational Structural Biology, Utrecht Universitywww.bonvinlab.org/softwarewww.github.com/haddocking

PowerFit DisVis

Robust solutions for cryoEM ,tting and visualisation of interaction space

PowerFit

G.C.P. van Zundert and A.M.J.J. Bonvin

AIMS Biophysics 2, 73-87 (2015).

G.C.P. van Zundert and A.M.J.J. Bonvin

J. Struct. Biol. 195, 252-258 (2016).

www.github.com/haddocking/power0t

h1p://milou.science.uu.nl/services/power0t/

Cryo-electron microscopy:

The rising star in structural biology

High resolution modelingwith cryo-EM data

Combine high-resolution structures with cryo-EM data

High resolution modelingwith cryo-EM data

Combine high-resolution structures with cryo-EM data

Rigid body ,t structure in density

High resolution modelingwith cryo-EM data

Combine high-resolution structures with cryo-EM data

Rigid body ,t structure in density

Perform real space (manual) re,nement

z

x

y

● Sensitivity (scoring)● Speed (sampling)

Cross-correlation based rigid body,tting

6D exhaustive search3 translational degrees of freedom3 rotational degrees of freedom

Laplace ,lter: enhances edges

Increasing sensitivity:Laplace pre-,lter

Laplace ,lter: enhances edges

Increasing sensitivity:Laplace pre-,lter

Increasing sensitivity:Overlapping neighboring densities

Up-weight voxels close at the core

Increasing sensitivity:Core-weighted cross-correlation

Fast Fourier Transform for fasttransla�onal scans

GPU accelera�on

Op�mized rota�on sets

Resampling and trimming target

z

x

y

Speeding up the search

Some successful examples:GroEL-GroES

23Å 8.9Å

13.3Å ribosome + KsgA

Some successful examples:Ribosome

9.8Å ribosome + RsgA

5 high-resolu�on ribosome densi�es (5.5Å – 7Å) with -.ed structures: 379 subunits total

Exploring the limits of rigid body,tting

Fitting success rate

Fisher z-transformation

Con,dence intervals

Fisher (1921), Volkmann (2009)

z=1

2ln(1+CC1−CC

)

σz=√

1

N−3

Detecting successful ,ts:Correlation con,dence intervals

Detecting successful ,ts:Reliability measure of ,t

DisVis

G.C.P. Van Zundert and A.M.J.J. Bonvin

Bioinforma5cs 31, 3222-3224 (2015)

.

G.C.P. van Zundert et al.

J. Mol. Biol., Advanced Online Publica5on.

www.github.com/haddocking/disvis

h1p://milou.science.uu.nl/services/disvis

8 cross-links

A modeling problem: how to dealwith distance restraints/constraints?

Given 2 interacting structures and a set ofdistance constraints between them, are there

any solutions that satisfy N constraints?

8 cross-links

On the existence of consistency

core regioninteraction region

receptor

ligand core region

Systematic 6-dimensional search

of conformations

Explorative modeling

Explorative data-consistency

Systematically sample billions of complexes using a 6D search

Explorative data-consistency

Systematically sample billions of complexes using a 6D search

Count for each complex how many constraints are satisfied/consistent

Exploring data-consistency:the accessible interaction space

Exploring data-consistency:Detecting false-positive constraints

Systematically sample billions of complexes using a 6D search

Count for each complex how many constraints are satisfied/consistent

Exploring data-consistency:Detecting false-positive constraints

Systematically sample billions of complexes using a 6D search

Count for each complex how many constraints are satisfied/consistent

For each complex consistent with N constraintscount how often a specific constraint is violated

Exploring data-consistency:Detecting false-positive constraints

Systematically sample billions of complexes using a 6D search

Count for each complex how many constraints are satisfied/consistent

For each complex consistent with N constraintscount how often a specific constraint is violated

Normalize over all complexesconsistent with N restraints

Exploring data-consistency:Detecting false-positive constraints

Exploring data-consistency:Detecting false-positive constraints

Exploring data-consistency:Detecting false-positive constraints

Exploring data-consistency:Detecting false-positive constraints

Exploring data-consistency:Detecting false-positive constraints

Exploring data-consistency:Detecting false-positive constraints

Exploring highly accessed residues

Systematically sample billions of complexes using a 6D search

Count for each complex how many constraints are satisfied/consistent

Exploring highly accessed residues

Systematically sample billions of complexes using a 6D search

Count for each complex how many constraints are satisfied/consistent

Count for each complex how oftena specific residue interacts

Normalize over all counted complexes:Average interactions per complex

Exploring highly accessed residues

Visualizing theaccessible interaction space

Where can the ligand be found for complexes consistent with N restraints?

Accessible interac5on spaceconsistent with all 6 restraints

Visualizing theaccessible interaction space

Visualizing theaccessible interaction space

What space does the ligand most likely occupy for complexes with N restraints?

25% iso-contour 10% iso-contour25% iso-contour

Visualizing theligand space occupancy

25% iso-contour 10% iso-contour25% iso-contour

Visualizing theligand space occupancy

PowerFit: combining speed, sensi�vity, andreliability

DisVis: Explora�ve modeling for determining the accessible interac�on space

Conclusions

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