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Philip E. Bourne, PhD, FACMI
National Center for Biotechnology Information
philip.bourne@nih.gov
http://www.slideshare.net...
The past 2.5 years has very much been devoted to leading
data science at the NIH and while this is predominantly a
talk se...
Clegg et al. 1980 Nature 5788:298-300
Apoferritin
Iron storage
Clegg et al. 1980 Nature 5788:298-300
Apoferritin
Iron storage
Biologically active molecule
Currently 122,000 structures & ~10TB
Bourne et al. 1997 Meth. Enz. 277 571-590Developed under the auspices of the IUCR
save__atom_site.Cartn_x
_item_description.description
; The x atom site coordinate in angstroms specified according to
a s...
Gu & Bourne (Ed) 2009
Samish, Bourne & Najmanovich Bioinformatics 2015 31:146-150
~~
Bernard M. Nat Rev Drug Disc 8(2009), 959-968
 Can we predict drug efficacy and toxicity?
 Can we reuse old drugs?
 Can we design personalized medicines?
~200 drugs ...
Output: arrhythmia
Xie et al 2015 PLOS Comp Biol 10(5):e1003554
Integrating chemical genomics and structural systems biology
MD
simulation
Mj
Q
Refined
interaction
model
Mj
Q
SMAP
Protei...
 Similar binding sites may bind similar ligands
 A 3D object recognition problem
• Globally different, but locally simil...
 Why? Large search space
 Challenge: inherent flexibility
and errors in predicted
structures
 Representation of the pro...
SMAP - Sequence-order Independent
Profile-Profile Alignment (SOIPPA)
L E R
V K D L
L E R
V K D L
Structure A Structure B
S...
0
0.01
0.02
0.03
0.04
0.05
0.06
0 0.1 0.2 0.3 0.4
True Positive RatioFalsePositiveRatio
PSI-Blast
CE
SOIPPA
0
0.01
0.02
0....
Muller et al. 2015 Nature Chemical Biology 11, 818-821
• Tykerb – Breast cancer
• Gleevac – Leukemia, GI
cancers
• Nexavar – Kidney and liver
cancer
• Staurosporine – natural pr...
PKA
Phosphoinositide-3 Kinase (D) and Actin-
Fragmin Kinase (E)
ChaK (“Channel Kinase”)
PKA
Scheeff & Bourne 2005 PLOS Com...
Zhao et al 2016 J. Med. Chem. 12:59(9) 4326-41
Zhao et al 2016 J. Med. Chem. 12:59(9) 4326-41
 Side effect prediction
 Xie et al. PLoS Comp. Biol., 3(2007):e217
 Xie et al. PLoS Comp. Biol., 5(2009):e1000387
 Dru...
Brunk et al 2016 BMC Sys Biol, 10:26
Proteome
Drug binding
site alignments
SMAP
Predicted drug targets
Drug and endogenous
substrate binding site analysis
Comp...
 Data and tools are not easily used (aka not FAIR)
 Only 12% of output is even reported
 What is available is siloed
 ...
Services: APIs, Containers, Indexing,
Software: Services & Tools
scientific analysis tools/workflows
App store/User Interf...
“… and hopefully get to say I told you so
when they are shown to improve the
human condition.”
-- Phil Bourne
All 135 previous lab members
Lei Xie
Zheng Zhao
PDB Team
Roger Chang (Palsson Lab)
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
Systems Biology & Pharmacology from a Structural Perspective
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Systems Biology & Pharmacology from a Structural Perspective

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University of Virginia, August 30, 2016

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Systems Biology & Pharmacology from a Structural Perspective

  1. 1. Philip E. Bourne, PhD, FACMI National Center for Biotechnology Information philip.bourne@nih.gov http://www.slideshare.net/pebourne August 30, 2016, University of Virginia
  2. 2. The past 2.5 years has very much been devoted to leading data science at the NIH and while this is predominantly a talk setting the context for my research, followed by current and future research, elements of work in open data science will inevitably creep in ….
  3. 3. Clegg et al. 1980 Nature 5788:298-300 Apoferritin Iron storage
  4. 4. Clegg et al. 1980 Nature 5788:298-300 Apoferritin Iron storage Biologically active molecule
  5. 5. Currently 122,000 structures & ~10TB
  6. 6. Bourne et al. 1997 Meth. Enz. 277 571-590Developed under the auspices of the IUCR
  7. 7. save__atom_site.Cartn_x _item_description.description ; The x atom site coordinate in angstroms specified according to a set of orthogonal Cartesian axes related to the cell axes as specified by the description given in _atom_sites.Cartn_transform_axes. ; _item.name '_atom_site.Cartn_x' _item.category_id atom_site _item.mandatory_code no _item_aliases.alias_name '_atom_site_Cartn_x' _item_aliases.dictionary cifdic.c94 _item_aliases.version 2.0 loop_ _item_dependent.dependent_name '_atom_site.Cartn_y' '_atom_site.Cartn_z' _item_related.related_name '_atom_site.Cartn_x_esd' _item_related.function_code associated_esd _item_sub_category.id cartesian_coordinate _item_type.code float _item_type_conditions.code esd _item_units.code angstroms Bourne et al. 1997 Meth. Enz. 277 571-590
  8. 8. Gu & Bourne (Ed) 2009
  9. 9. Samish, Bourne & Najmanovich Bioinformatics 2015 31:146-150 ~~
  10. 10. Bernard M. Nat Rev Drug Disc 8(2009), 959-968
  11. 11.  Can we predict drug efficacy and toxicity?  Can we reuse old drugs?  Can we design personalized medicines? ~200 drugs with identified effects http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.htm
  12. 12. Output: arrhythmia Xie et al 2015 PLOS Comp Biol 10(5):e1003554
  13. 13. Integrating chemical genomics and structural systems biology MD simulation Mj Q Refined interaction model Mj Q SMAP Protein-ligand docking Mj Q Mi 3D model of novel Target 3D model of annotated target Initial interaction model Query chemical Network modeling Experimental support Generalized Network Enrichment of Structure- Activity Relationships Xie & Bourne 2008 PNAS 105(14):5441-6 Xie et al 2012 Ann Rev Pharm & Tox 52:361-79 Xie et al 2016 Ann Rev Pharm & Tox in press
  14. 14.  Similar binding sites may bind similar ligands  A 3D object recognition problem • Globally different, but locally similar • Dynamic • Scalable SMAP – Determining Binding Site Similarity Across Protein Space
  15. 15.  Why? Large search space  Challenge: inherent flexibility and errors in predicted structures  Representation of the protein structure - Ca atoms only - Delaunay tessellation - Graph representation  Geometric Potential (GP) 0.2 0.1)cos( 0.1      i Di Pi PGP neighbors a100 0 Geometric Potential Scale 0 0.5 1 1.5 2 2.5 3 3.5 4 0 11 22 33 44 55 66 77 88 99 Geometric Potential binding site non-binding site Algorithm Xie & Bourne 2007 BMC Bioinformatics 4:S9
  16. 16. SMAP - Sequence-order Independent Profile-Profile Alignment (SOIPPA) L E R V K D L L E R V K D L Structure A Structure B S = 8 S = 4 Algorithm L E R V K D L S = 8 Xie & Bourne 2008 PNAS 105(14):5441-6
  17. 17. 0 0.01 0.02 0.03 0.04 0.05 0.06 0 0.1 0.2 0.3 0.4 True Positive RatioFalsePositiveRatio PSI-Blast CE SOIPPA 0 0.01 0.02 0.03 0.04 0.05 0.06 0 0.1 0.2 0.3 0.4 True Positive Ratio FalsePositiveRatio PSI-Blast CE SOIPPA Proteins with the same global shape Proteins with different global shape Xie & Bourne, PNAS, 105(2008):5441
  18. 18. Muller et al. 2015 Nature Chemical Biology 11, 818-821
  19. 19. • Tykerb – Breast cancer • Gleevac – Leukemia, GI cancers • Nexavar – Kidney and liver cancer • Staurosporine – natural product – alkaloid – uses many e.g., antifungal antihypertensive Collins and Workman 2006 Nature Chemical Biology 2 689-700 10/16/13 ACSSA 25
  20. 20. PKA Phosphoinositide-3 Kinase (D) and Actin- Fragmin Kinase (E) ChaK (“Channel Kinase”) PKA Scheeff & Bourne 2005 PLOS Comp Biol 1(5):e49
  21. 21. Zhao et al 2016 J. Med. Chem. 12:59(9) 4326-41
  22. 22. Zhao et al 2016 J. Med. Chem. 12:59(9) 4326-41
  23. 23.  Side effect prediction  Xie et al. PLoS Comp. Biol., 3(2007):e217  Xie et al. PLoS Comp. Biol., 5(2009):e1000387  Drug repurposing  Kinnings et al. PLoS Comp. Biol., 5(2009):e1000423  Xie et al. PLoS Comp. Biol. 7(2011): e1002037  Ng. et al. PSB Symposium (2014)  Polypharmacological drug design  Durant et al. PLoS Comp. Biol. 6(2010):e100648  Chang et al. BMC Sys. Biol. 7(2013):102  Personalized medicine  Xie et al. BMC Genomics 14(2013):S9
  24. 24. Brunk et al 2016 BMC Sys Biol, 10:26
  25. 25. Proteome Drug binding site alignments SMAP Predicted drug targets Drug and endogenous substrate binding site analysis Competitively inhibitable targets Inhibition simulations in context-specific model COBRA Toolbox Predicted causal targets and genetic risk factors Metabolic network Scientific literature Tissue and biofluid localization data Gene expression data Physiological objectives System exchange constraints Flux states optimizing objective Physiological context-specific model Influx Efflux Drug response phenotypes Drugtargets Physiological objectives Causal drug targets All targets 336 genes 1587 reactions Chang et al PLOS Comp. Biol. 2010 6(9): e1000938
  26. 26.  Data and tools are not easily used (aka not FAIR)  Only 12% of output is even reported  What is available is siloed  It is not easy to stand on the shoulders of giants  Cloud environments are potential technical solutions  Genomics is leading the way eg GA4GH  We need similar approached for systems pharmacology
  27. 27. Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows App store/User Interface Shared Research Objects Structure Space Cell ModelsChemical Space Phenotypes
  28. 28. “… and hopefully get to say I told you so when they are shown to improve the human condition.” -- Phil Bourne
  29. 29. All 135 previous lab members Lei Xie Zheng Zhao PDB Team Roger Chang (Palsson Lab)

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