how can access to experimental x-ray data further our understanding of structures used in structure...
DESCRIPTION
As part of the drug discovery process, computational chemistry is constantly evolving and adapting to meet the latest scientific challenges and business demands. An approach to computational drug discovery that is both flexible and adaptable is essential. This talk highlights the developing trends in computational chemistry and biology with an emphasis on demonstrating innovative and routine workflows in structure-based design and biotherapeutics projects. Examples include how best to leverage experimental X-ray data to gain insight for structure based drug design and making most of the PDB data. Given the increased interest in protein therapeutics, examples will also be given for protein engineering and for methods in building antibody framework structures and predicting the antibody-antigen binding interfaces.TRANSCRIPT
Francisco Hernandez-Guzman, Ph.D.
Product Manager, Life Sciences
ACS 2010 – San Francisco, CA
March 22, 2010
How can access to experimental X-ray data further our understanding
of structures used in structure based studies?
© 2008 Accelrys, Inc. 2
Agenda
• Goals
• Background– X-ray crystallography 101
• Expectations– Theoretical & Experimental
• Methods for analysis: – Map theory
– Resolution
– 2Fo-Fc vs. Fo-Fc vs. –(Fo-Fc)
• Examples
• Custom protocols
• Conclusion
• Acknowledgements/References
© 2008 Accelrys, Inc. 3
Goals
Access to experimental structural data can:
1. Be a HUGE resource of information• DO NOT need to be an expert crystallographer to use this information
2. Help establish reasonable expectations from X-ray structures
3. Right mix technology powerful tool for structure base discovery
© 2008 Accelrys, Inc. 4
Background:
X-ray crystallography 101 for structure solution:
Steps:
• Crystallization (apo or with ligand)
• Data Collection
• Data Processing
• Phase Determination
• Model Building and Refinement
1
-987
115.986 115.986 44.151 90.000
90.000 120.000 p6
1 0 0 -0.2 0.4
2 -1 0 0.2 0.6
2 -1 2 2471.3 119.7
2 0 1 3166.3 237.6 2602.5 113.7
2 0 2 3257.2 112.9 3532.6 154.7
3 -2 0 895.5 32.6
3 -2 1 3618.7 120.2 5126.5 180.6
3 -2 2 3016.3 106.0 2722.1 122.3
3 -2 3 1124.7 42.6 1003.7 35.4
3 -2 4 6620.5 419.3 7735.3 386.1
3 -1 1 4332.0 425.0
3 -1 2 674.4 17.9 102.5 8.1
3 -1 3 174.2 12.3 52.7 11.9
3 -1 4 15478.4 827.1 12906.3 844.7
3 0 1 10052.2 496.7 10107.3 504.2
3 0 2 15486.2 469.7 15548.0 590.2
3 0 3 4730.2 167.5 4454.7 188.8
3 0 4 9840.6 543.6 8136.2 375.4
4 -3 1 23731.2 553.5 20271.4 584.9
X-ray data model
© 2008 Accelrys, Inc. 5
Points to remember from X-ray steps
• Crystallization:– Molecules are in the crystal form
• Packing lattice• pH• Additives• Temperature• Molarity/concentration
• Data collection– High energy X-rays
• Room temperature vs Cryo x-ray data collection• Radiation Damage
• Data processing– Data completion/redundancy
• Space group– Data resolution– B-factors
• Phase Determination– Molecular replacement– Experimental phasing (isomorphous replacement, anomalous scattering)
• Model Building– Automated tools and manual tools
• QUANTA, CNX, DS*, PP*, COOT and others. *DS version 2.5.5 and PP version 7.5.4
© 2008 Accelrys, Inc. 6
Other important points to remember
• X-ray structures are models!!!– Guided by experimental observations
– Subject to interpretation
– Not immune to error
– Hydrogens are usually missing…
• Observations limited to available data– Reliability depends on questions asked
– Need to clearly define the expectations properly
© 2008 Accelrys, Inc. 7
Expectations
THEORETICAL:
• Reasonable representation of the “biologically active” molecule
• Static representations are significant– Structures Space and Time averaged
– Protein dynamics can be “simplified”
• End point structures (before and after) can provide useful
information
EXPERIMENTAL:
• Solved structures match experimental observations
• Structures are biologically and chemically meaningful
• Protein-ligand interactions are properly modeled
© 2008 Accelrys, Inc. 8
Methods for Analysis: Map theory
• Electron density map equation:
• In the case of standard model based maps:
• So in theory as Fc Fo:
|Fhkl|e2πiФhkl
ExperimentCalculated phases from model
ρ ≈ 2Fo – Fc ≈ Fo and ρ ≈ Fo – Fc ≈ 0
R = Σ||Fo| – Fc||/ Σ|Fo|
© 2008 Accelrys, Inc. 9
Methods for Analysis: Resolution
• 2Fo-Fc as a function of resolution: (1r2q.pdb)
4.0 Å
low high
3.0 Å 2.0 Å 1.05 Å
In general, level of detail and confidence increases as a function of resolution
© 2008 Accelrys, Inc. 10
Methods for Analysis: 2Fo-Fc, Fo-Fc, & -(Fo-Fc)
• Map analysis of a misplaced residue:
2Fo-Fc
Fo-Fc
-(Fo-Fc)
© 2008 Accelrys, Inc. 11
Example: 1 – questionable chemistry
• 1LEE.pdb (1.9 Å)
??
K238
R238 + SO4
RS367
RS370
2Fo-Fc
2Fo-Fc
Fo-Fc
Fo-Fc
Fo-Fc
Fo-Fc
© 2008 Accelrys, Inc. 12
Example: 2 – questionable ligand density
• 1nhu (2.0 Å)
Fo-Fc
-(Fo-Fc)
© 2008 Accelrys, Inc. 13
Example: 3 – questionable structure
• 2q76 (B:134 – B:137) ( 2.0 Å)
• Unexplained Fo-Fc density
• Incomplete B:Gln134
• Ramachandran inconclusive
•R= 0.199 (pdb - 0.198)
•R-free= 0.239 (pdb - 0.233)
vs.
•R=0.197
•R-free= 0.230
© 2008 Accelrys, Inc. 14
Example: 3 – questionable structure
• 2q76 (B:134 – B:137) ( 2.0 Å)
© 2008 Accelrys, Inc. 15
Example: 4 – SBDD - Kinases
• 1nu3 (1.75 Å) – bad ligand geometry… 147.49° vs. 104°
2Fo-Fc
Fo-Fc -(Fo-Fc)
© 2008 Accelrys, Inc. 16
Automatic ED Map Generation
© 2008 Accelrys, Inc. 17
Advanced PDB search functionality in DS
© 2008 Accelrys, Inc. 18
Interactive Kinome Viewer
• Kinome Viewer: http://accelrys.com/events/webinars/human-kinome/
© 2008 Accelrys, Inc. 19
Conclusion
1. Crystal structures are time and space averaged models
based on experimental data • Structures not immune to error
2. Access to X-ray data is critical for assessing
expectations of crystal structures• Electron Density map visualization is a very useful and powerful tool
3. Software solutions should provide insights into further
discovery
• Discovery Studio / Pipeline Pilot
• Custom protocols Kinome Viewer
RCSB Search
Automatic ED Map Generation
© 2008 Accelrys, Inc. 20
Acknowledgements and References
• Yi-Shiou Chen, Ph.D. X-ray components and protocols
• Guillaume Paillard, Ph.D. Kinome Viewer
• NOJ Malcom, Ph.D. Auto ED Map Generation (wrapping)
• Accelrys R&D and Marketing
• H.M. Berman, K. Hendrick, H. Nakamura. (2003) Announcing the worldwide Protein Data Bank. Nature Structural Biology 10(2):980
• Davids, E. et al. (2008). Drug Discovery Today. 13(19-20), 831-841
• Gert Vried, Radbound Univ. Nijmegen Med. Centre, The Netherlands.