ISFI

1
Medium Throughput Surface Entropy Reduction
WonChan Choi1,3, David Cooper1,3, Meiying
Zheng1,3, Natalya Olekhnovitch1,3, Urszula
Derewenda1,3, Lukasz Goldschmidt2,3, David
Eisenberg2,3, Zygmunt S. Derewenda1,3
1Department of Molecular Physiology and
Biological Physics, University of Virginia.
Charlottesville, VA 22908. 2Department of
Chemistry and Biochemistry, University of
California, Los Angeles. Los Angeles, CA 90095.
3PSI Center for Structure and Function
Innovation.
ISFI
Some successes
Abstract
Protein Expression Highlights
ISFI members
Apc1126 (K18Y, E20Y, Q21Y)
Apc1126 (K18A, E20A, Q21A)
Our laboratory is part of the Integrated Center
for Structure and Function Innovation (ISFI),
which is one of the seven specialized centers of
the Protein Structure Initiative. The mission of
the ISFI is to address bottlenecks associated
with high throughput crystallography,
specifically protein solubility and
crystallization. Our main objective is to develop
the methodology of the SER method (Surface
Entropy Reduction), but we also aim to design a
medium-throughput pipeline that can be used as a
salvage pathway for the larger structural
genomics centers and by individual labs alike.
Within this poster, we present the current state
of our pipeline development, as well as highlight
some recent successes in obtaining diffraction
quality crystals using the SER approach. We also
describe some of the tools that we have developed
that may help other crystallographers. One of
these is a Surface Entropy Reduction Prediction
(SERp) Server, which takes a proteins sequence
and predicts the mutations that will increase a
proteins crystallization potential. We are
currently testing the server using proteins that
failed to crystallize at the JCSG, the MCSG, or
the TBsgc. The Surface Entropy Reduction server
is located at http//nihserver.mbi.ucla.edu/SER/.

JCSG
JCSG
TM1024 (K45A, K46A)
2-liter bottles
Two strategies for protein crystallization

• Varying the protein parameter
• Homologues
• Different construct ends
• Reductive Methylation
• Alanine scanning
• Directed Evolution
• Rational Mutagenesis

JCSG
JCSG NaCl
Centrifuge bottles with Zipper bag
TM1024 (K45Y, K46Y)
Protein Purification Highlights Streamlined
Purification Protocol HisTrap ? Phenyl
Sepharose ? Desalt ? Screen Custom web
interface for AKTA Prime Systems Crystallizati
on Alternate reservoir and standard
screening. Mosquito Crystallization Robot for
screening. Custom BioRobot3000 application
with web interface
Crystallization Grid Screen Generator
The ISFI
JCSG
JCSG NaCl
Crystallization by Surface Entropy Reduction
Optimization
Lysines and Glutamates on the proteins surface
create an entropy shield that can prevent
crystallization. SER structures usually have
crystal contacts involving the engineered
residues.
TM1024 (K45A, K46A) JCSG NaCl
Lawrence Berkeley National Laboratory
Lawrence Livermore National Laboratory
University of Chicago

• Candidate Proteins
• Soluble and purify well
• Difficult to crystallize or diffract poorly
• Contain a cluster of highly-entropic residues

University of Virginia
Salts
University of California Los Angeles
Los Alamos National Lab

• ISFI HT pipeline
• Mission to apply the novel methodology to those
  targets that failed to crystallize in standard HT
  PSI pipelines, but are identified as
• Susceptible to one of our approaches
• Of scientific interest to us, our collaborators
  or general public

Streamlining the UVA Pipeline
The SERp Server (The SER Prediction
Server) http//nihserver.mbi.ucla.edu/SER We
have developed a web server that takes a
proteins sequence and predicts the mutations
that will increase its crystallization potential.

Goal reduce the time, expense, and effort it
takes to screen mutants
Overall Standardized protocols Stock and common
buffers Using Google Calendar to schedule
equipment Protein Expression
Highlights Using 2-Liter Bottles doubles shaker
space (Now 9 proteins a day capacity) Lining
centrifuge bottles with zipper bags
(Dramatically reduces harvesting time) Growth
and harvesting are done by a 2 person
team (Reduces demand on 1 individual.)
ISFI Protein Pipeline
Progress on Targets
UCLA Analysis of protein complexes Co-expression
of partners
UChicago Crystallization chaperone design
Selection Criteria No homologues with gt 30
identity. Easy to express, purify, and
concentrate. Failed at Crystallization
stage. High SERp Score.
Los Alamos Protein Production Facility
References

• Zygmunt Derewenda. Rational Protein
  Crystallization By Mutational Surface
  Engineering. Structure. 12529-35.
• Matthew Kimber, et al. Data Mining
  Crystallization Databases Knowledge-based
  Approaches To Optimize Protein Crystal Screens.
  Proteins. 51562-8.
• Janet Newman. Expanding Screening Space Through
  The Use Of Alternative Reservoirs In
  Vapor-diffusion Experiments. Acta Cryst.
  D61490-3.
• Rebecca Page and Raymond Stevens. Crystallization
  Data Mining In Structural Genomics Using
  Positive And Negative Results To Optimize Protein
  Crystallization Screens. Methods. 34373-89.
• Stephen D. Pickett and Michael J. E. Sternberg.
  Empirical Scale Of Side-chain Conformational
  Entropy In Protein Folding. J Mol Biol.
  231825-39.

Crystallization Solutions The Super Screen was
based on data mining experiments from the Stevens
and Edwards labs (see refs). The JCSG (Qiagen)
is very similar to the Super Screen and is what
we currently use. Standard Screens Drops are
mixed 11 with protein solution and Super Screen
reagent. Reservoir is 60 µl of Super Screen
reagent. Salt Screens Drops mixed as above.
Reservoir of every well is 60 µl of 1.5 M NaCl.
LANL Directed Evolution Protein Production
UVA Protein surface engineering
LLNL Crystallization Facility
LBNL Data Collection Facility