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Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013
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Page 1: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Using X-ray structures for bioinformatics

Robbie P. JoostenNetherlands Cancer Institute

Autumnschool 2013

Page 2: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Structures in bioinformatics

• Understand biology– Direct interpretation

– Data mining– Homology modeling

• Drug design• Molecular dynamics

Basic rule: Better structures → Better

results

Introduction

Page 3: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Right structure(s) for the job

1.Selection: find (a number of) PDB entries

2.Validation: check the quality of your selection

3.Optimisation: maximise the quality of your selection

Focus on X-ray structures

Introduction

Page 4: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

X-ray structures have a history

1. Protein expression2. Crystallisation3. X-ray diffraction

experiment4. Model building and

refinement5. Deposition at the PDB

All these steps affect the final PDB

file

Selection

Page 5: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Protein expressionA ‘construct’ is made• Partial proteins– E.g. only extracellular domain of membrane protein

• Frankenstein proteins– Fusion proteins or chimeras

• Mutants are introduced – Some by accident!

• Poly-histidine tags added for purification

• Altered glycosylation state– Large sugars hamper crystallisation

History

Page 6: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

CrystallisationThe protein stacks regularly to form a crystal• Protein still functional in the crystal

• Much solvent in the crystal (~40%)• Some residues can move– Disorder: missing loops/side chains– Alternate conformation

History

Page 7: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

CrystallisationBeware of crystal packing• One copy of the protein can influence the next

History

Page 8: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

CrystallisationChemicals are used for crystallisation• Buffers to stabilise the pH• Precipitants– Change solubility of the protein– Neutralise local charges– Bind water– High concentrations are used• Compounds compete with natural ligands

• Examples:– Polyethylene glycol (PEG)– Ammonium sulphate

History

Page 9: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

CrystallisationBeware of the crystallisation conditions

History

Page 10: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

CrystallisationBeware of the crystallisation conditions

History

Page 11: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

X-ray diff ractionTypical experiment

History

X-ray source

Detector

Page 12: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

X-ray diff raction• X-rays interact with electrons– Atoms with few electrons (H, Li) do not diffract well

• X-rays cause damage to the protein– Acidic groups (ASP en GLU) can be destroyed

– Disulphide bridges are broken– Hydrogens are stripped– Cooling crystals in liquid nitrogen helps• Glycerol added to the crystal!

History

Page 13: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

X-ray diff raction• We are not using a microscope• We don’t measure everything we need

History

X-ray diffraction gives an indirect and incomplete measurement

ρ (𝑥 , 𝑦 , 𝑧 )= 1𝑉 ∑

h∑𝑘∑𝑙

𝐹h𝑘𝑙𝑒[− 2𝜋 𝑖 (h𝑥+𝑘𝑦+𝑙𝑧 )−𝛼]

MeasuredMissing: phase

Page 14: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Model building and refinement

Iterative process

History

Phases + calculated X-ray data

Electron density maps

Structure model

Measured X-ray diffraction

data

Initial phases

FT

FT

Model building

Page 15: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

History

Two types of maps1. Regular electron density map (2mFo-

DFc)2. Difference map (mFo-DFc)

Model building and refinement

Page 16: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Fitting atoms to the ED map and trying to remove difference density peaks

HistoryModel building and refinement

Page 17: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• Requires skill and experience• Requires time and patience• Requires good software

Lack of any of these can be seen in the final PDB file

HistoryModel building and refinement

Page 18: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• Both coordinates and experimental X-ray data are deposited

• PDB standardises files and adds annotation

• Sometimes things go wrong

History

Deposition at the PDB

Page 19: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

LINKs between alternate conformations

History

Deposition at the PDB

Page 20: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

History

Deposition at the PDBUn-biological LINKs (in 1a1a)

LINK C ACE C 100 N PTH C 101

LINK C PTH C 101 N GLU C 102

LINK CF PTH C 101 OG SER A 188

LINK N DIP C 103 C GLU C 102

LINK C ACE D 100 N PTH D 101

LINK C PTH D 101 N GLU D 102

LINK N DIP D 103 C GLU D 102

Page 21: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Think of what happened to the

structure before you downloaded it

Page 22: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Use the experimental data• Resolution says very little about the structure

• (free) R-factor gives the overall fit of the structure to the experimental data

• For biological interpretation more detail is needed

Use the maps

Validation

X-ray specific validation

Page 23: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Which is the better structure of berenil bound to DNA?

Validation

X-ray specific validation

PDB id Resolution R

268d 2.0 0.160

1d63 2.0 0.183

Page 24: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Validation

X-ray specific validationThe real-space R-factor (RSR)• A per-residue score of how well the atoms fit the map

• Works like the R-factor (lower is better)

Page 25: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Maps can help distinguish the good and bad bits of a structure

Validation

X-ray specific validation

Page 26: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Poorly fitted side-chains

Evil peptides

ValidationThings you can find in maps

Page 27: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

The wrong drug

ValidationThings you can find in maps

Page 28: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Sequence error K -> R• Accidental mutant• Also a missing sulfate

ValidationThings you can find in maps

Page 29: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Missing water Missing alternate conformation

ValidationThings you can find in maps

Page 30: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• Visualisation in Coot– http://www2.mrc-lmb.cam.ac.uk/personal/pemsley/coot/

• Get maps and real-space R values from the Electron Density Server– http://eds.bmc.uu.se/eds/index.html– Direct interface with Coot

• Get maps and updated models from PDB_REDO

Practical session

Validation

Checking maps

Page 31: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Maps show things you cannot see

otherwise

Page 32: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• Solved by a diverse group of scientists– People make errors & gain experience

• Since 1976– Structures are not updated

• Solved with the methods of their era– Methods improve over time

Structures in the PDB do not represent the best we can do

NOW

Optimisation

Structures in the PDB

Page 33: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• Take structure + experimental data• Use latest X-ray crystallography methods– Decision making: use case-specific methods

– Create new methods when needed

• Improve model quality– Fit with experimental data– Geometric quality

• Fix errorsPDB_REDO

OptimisationImprove structures in PDB

Page 34: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Step 1: prepare data• Clean-up structure and X-ray data• Data mining

Step 2: establish baseline• Fit with experimental data (R-factors)

• Geometric quality– Validation with WHAT_CHECK

Optimisation

PDB_REDO method

Page 35: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Step 3: re-refine structure (with Refmac)

• Improve fit with experimental data– Use restraints to improve geometric quality

• Improve description of protein dynamics– Concerted movement of groups of atoms (TLS)

– Anisotropic movement of individual atoms

Optimisation

PDB_REDO method

Page 36: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Step 4: rebuild structure • Delete nonsense waters• Flip peptide planes• Rebuild side-chains– Add missing ones– Optimise H-bonding

Step 5: validate structure • Geometry• Density map fit• Ligand interactions

Optimisation

PDB_REDO method

Page 37: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• www.cmbi.ru.nl/pdb_redo– > 72,000 structures (98%)– Detailed methods & reprints

• Directly in molecular graphics software– YASARA– CCP4mg– Coot (needs plugin)– PyMOL (needs plugin)

• Linked via PDBe & RCSB

Availability

PDB_REDO databank

Page 38: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Worse Same Better0%

25%

50%

75%

100%

8%12%

80%

Ramachandran plot

• Improved fit with the data• Better geometry

Worse Same Better0%

25%

50%

75%

100%

9%17%

74%

R-free

Worse Same Better0%

25%

50%

75%

100%

4%

22%

74%

Fine packing

Optimisation

Does it work? ( 1 2 , 0 0 0 s t r u c t u re s )

Page 39: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

MolProbity validation ( 1 e o i )

PDB PDB_REDO

Optimisation

Page 40: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

OptimisationElectrostatics calculations

• ‘Missing’ positive lysine atoms distort electrostatics calculations

• Adding missing atoms correctly describes C-terminus interaction with side chains

Page 41: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

• Wrong peptide plane in peptide ligand

• Fixed by PDB_REDO• Better understanding of H-bonds in the interaction

Optimisation

Protein-ligand interaction

Page 42: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

OptimisationProtein-protein interaction

• Packing interface with poor ionic interactions

• Rebuilt interface properly describes ionic dimerisation interactions

Page 43: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

Optimised structures give a better view of

the biology of the protein

Page 44: Using X-ray structures for bioinformatics Robbie P. Joosten Netherlands Cancer Institute Autumnschool 2013.

PDB_REDOersAmsterdam:• R Joosten• K Joosten• A Perrakis

Key contributors:Eleanor Dodson, Ian Tickle, Paul Emsley, Ethan Merritt, Elmar Krieger, Thomas Lütteke, Rachel Kramer Green, Sanchayita Sen

Nijmegen:• T te Beek• M Hekkelman• G Vriend

Cambridge:• G Murshudov• F Long


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