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Shotgun crystallization of the Shotgun crystallization of the Thermotoga maritimaThermotoga maritima proteome proteome
Protein properties and crystallization Protein properties and crystallization conditions that correlate with conditions that correlate with
crystallization successcrystallization success
Rebecca PageRebecca PageThe Scripps Research InstituteThe Scripps Research Institute3.30.2004 – PSI, NIH3.30.2004 – PSI, NIH
Data mining for faster structure Data mining for faster structure determinationdetermination
Crystallization Conditions
Protein Properties
Data mining for faster structure Data mining for faster structure determinationdetermination
Crystallization Conditions
Protein Properties
Data mining for faster structure Data mining for faster structure determinationdetermination
Crystallization Conditions
Protein Properties
Data mining for faster structure Data mining for faster structure determinationdetermination
Crystallization Conditions
Protein Properties
• Minimize Minimize initial initial crystallization crystallization screensscreens
Data mining for faster structure Data mining for faster structure determinationdetermination
Crystallization Conditions
Protein Properties
• Minimize Minimize initial initial crystallization crystallization screensscreens
• Improve Improve target target selectionselection
Thermotoga maritimaThermotoga maritima
1877 ORFs1877 ORFs
Experimental designExperimental design
• Process all T. maritima proteins through the JCSG structure determination pipeline
• Targets are not prefiltered
• Targets are processed using identical experimental methods
Lesley, et al. (PNAS, 2002)
Thermotoga maritimaThermotoga maritima
1877 ORFs1877 ORFs
Experimental designExperimental design
A more complete, less A more complete, less biased crystallization biased crystallization
dataset for data miningdataset for data mining
Lesley, et al. (PNAS, 2002)
• 258720 crystallization experiments
• 465 of 539 (86%) proteins crystallized
• 472 of 480 (98%) conditions produced crystals
• 5546 total crystal hits
The NumbersThe Numbers
1791
539
1376
539
Targets
Data mining crystallization Data mining crystallization conditionsconditions
Minimize initial crystallization screensMinimize initial crystallization screens
Data mining crystallization Data mining crystallization conditionsconditions
Minimize initial crystallization screensMinimize initial crystallization screens
Many proteins crystallized in 5 or more Many proteins crystallized in 5 or more of the original 480 conditionsof the original 480 conditions
0 1 to 56 to 1011 to 1516 to 2021 to 2526 to 5051 or more
0
1-5
6-10
11-15
16-20
21-25
26-50
51 or more
73; 13.5%
249; 46.2%
24; 4.5%
47; 8.7%
73; 13.5%
19; 3.5%
32; 5.9%
21; 3.9%
MINCOVIterative selection algorithm that identifies minimal screens, subsets of the original 480 conditions that would have crystallized all 465 proteins
Repeat 472 times (each condition)
Slawomir Grzechnik
• 472 minimal 472 minimal screensscreens
• Each Each contained 108-contained 108-116 conditions116 conditions
• Intersection = Intersection = Core ScreenCore Screen
Identify minimalIdentify minimal crystallization screenscrystallization screens
0
20
40
60
80
100
120
140
160
180
High MWPEG
Low MWPEG
Salts Polyalcohols Organics
Core Screen
All Conditions
Core Screen• 67 conditions (14%)
• All precipitants
• 392 proteins crystallized (84%)
Expanded Core Screen• 96 conditions (20%)
• 448 proteins crystallized (96%)
Core ScreenCore ScreenBest 96 conditions crystallize 448 proteinsBest 96 conditions crystallize 448 proteins
Page, et al. (Acta Cryst D, 2003)
180
140
100
60
20
High MWPEG
Low MWPEG
Salts Poly-alcohols
Organics
Original ScreenCore Screen
Data mining protein propertiesData mining protein properties
Improve target selectionImprove target selection
Data mining protein propertiesData mining protein properties
Improve target selectionImprove target selection
20
10
15
5
Fre
qu
ency
-1.0 0.0 1.0
Gravy Index
Gravy Index- hydrophilic+ hydrophobic
Identify upper and lower bounds of crystallized proteins and use these limits in future target selection
Better target selection for JCSG pipelineBetter target selection for JCSG pipeline
Proteins with 40 or more SEG Proteins with 40 or more SEG residues rarely crystallizeresidues rarely crystallize
• SEG: Filtering to identify low complexity segments
• Long SEG segments can be unstructured
Low-complexity segments
TPPTMPPPPTT
GGGSSSSHS
PNGLPHPTPPPP
QQQGRQQQQQLK
Proteins with 40 or more SEG Proteins with 40 or more SEG residues rarely crystallizeresidues rarely crystallize
• SEG: Filtering to identify low complexity segments
• Long SEG segments can be unstructured
0 20 40 60 80 100
30
20
10
0
Number of SEG residues
% c
ryst
alli
zed
New target selectionNew target selection Characteristic Proteins
EliminatedCrystals
Eliminated
Protein Total
(1877)
Crystal Total
(465)
Length120 1 1757 464
Charged AA188 0 1602 464
Gravy204 0 1562 464
pI 57 0 1538 464
TMHMM; SignalP
538 15 1245 448
Coiled-Coil 72 4 1213 445
SEG 144 6 1187 63% 439 94%
Goal: more structures!Goal: more structures!
Crystallization Conditions
Protein Properties
Goal: more structures!Goal: more structures!
Crystallization Conditions
Protein Properties
Crystallization Conditions
Protein Properties
Goal: more structures!Goal: more structures!
Crystallization Conditions
Protein Properties
Goal: more structures!Goal: more structures!
UCSD - BICJohn WooleyAdam GodzikSusan TaylorSlawomir GrzechnikSlawomir Grzechnik Bill WestAndrew MorseJie QuyangXianhong WangJaume CanavesJaume CanavesLukasz JaroszewskiRobert SchwarzenbacherRay Bean, Josie Alaoen
SSRL - SDCKeith HodgsonAshley DeaconMitchell MillerHenry van den BedemGuenter WolfS. Michael SoltisR. Paul PhizackerleyIrimpan MathewsQingping XuAmanda PradoJohn KovarikHsiu-Ju ChiuRoss FloydInna LevinRonald ReyesFred Rezazadeh
GNF / TSRI - CCRay Stevens Ray Stevens Scott LesleyScott LesleyRebecca PageCarina GrittiniJeff VelasquezKin MoyEric SimsBernard CollinsTom Clayton Angela Walker Heath KlockHeath KlockEric KoesemaEric Hampton Jamison CampbellMike HornsbyTanya BioracDan McMullanDan McMullanKevin RodriguesMike DiDonatoMike DiDonatoAndreas KreuschAndreas KreuschGlen SpraggonGlen SpraggonMarianne PatchXiaoping DaiTerry CrossKevin RodriguesPolat AbdubekPolat AbdubekEileen AmbingEileen Ambing
TSRI - ACIan WilsonPeter KuhnMarc ElsligerFrank von DelftVandana SridharDan Taillac
Exploratory ProjectsKurt Wüthrich, TSRILinda ColumbusTouraj EtezadyMargaret JohnsonWolfgang PetiVirgil Wood, UCSD Phillip BourneBarbara CottrellRaymond DeemsJack KimDennis PantazatosGeoffrey Chang, TSRI