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Within a single generation, researchers discovered
that DNA was the genetic material encoding
RNA, which in turn encodes proteins, and these
proteins carry out the principal enzymatic reac-
tions of life. They established that the sequences of proteins
ultimately determine their 3D structures, which determine their
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sequence genomes, predict the protein structures they encode,
and build accurate models of all of life.
Half a century later, a few problems persist. One of the
toughest is the challenge of getting from an amino acid se-
quence to a 3D protein structure. Though the former ostensi-
bly determines the latter, the exact rules of the peptide-folding
process remain largely inscrutable. Nonetheless, computa-
tional biologists continue to chip away at the problem, pro-
ducing an evolving series of tools that can predict some class-
es of protein structures quite accurately. In the meantime, the
classic technique of X-ray crystallography has become more
accessible to nonspecialists, and a revolutionary series of
developments in electron microscopy is revealing structures
that previously eluded understanding.
Advancing crystallography ��������'�����'�������� �(�������(&����������%����������
principles, X-ray crystallographers attack the problem from
the opposite direction, purifying and crystallizing a protein
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technique can be tedious, often requiring thousands of ex-
periments to determine the conditions that will yield usable
protein crystals. Today, though, biologists can let robots do
much of the work.
ìRobots enable one to set up much smaller crystallization
drops, so that you need smaller amounts of sample to screen
large numbers of conditions,î says Cynthia Wolberger, a pro-
fessor of biophysical chemistry at Johns Hopkins School of
Medicine��'���������������' ���'&%(�&�����'��������
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lization conditions, such as the TTP Labtech mosquito and
the Formulatrix Rock Imager. Meanwhile, rapid cloning and
protein expression platforms let researchers produce multiple
���'����%��������'������' ��'����������(���������������
Crystallographers have also improved their ability to study
membrane proteins, which have been notoriously hard to
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proportions, researchers can form a cubic liquid crystal ame-
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quantities of protein. ìThis is a huge advance,î says Martin
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ity College��'�"&���'��#���' ��!������ ��������& �����%�
G-protein coupled receptors and other critical membrane pro-
teins ìreally underwent an explosion as a result of this cubic
phase methodology.î
Once a protein crystallizes, investigators take it to one of
a few government-funded synchrotron facilities to have it
bombarded with X-rays and to collect their data. That process
has also gotten easier in recent years. ìWe rarely go [to the
synchrotron] anymore; we ship our crystals there,î says Wol-
berger, adding that ìitís all been set up with great software
and robotics so you can operate it from anywhere.î
Improvements in synchrotron data collection systems now
enable analyses that would have been impossible just a few
years ago. A process called ìraster scanningî allows research-
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be unusable. Automated, high-speed data collection also per-
mits scanning many more crystals. For example, Wolberger
and her colleagues recently analyzed over a thousand crystals
to gather enough information for a structure, an approach that
would have been impractical with manual exposures.
GenomicsóOctober 7 NeurotechniquesóNovember 4 Cell AnalysisóNovember 25
Upcoming Features
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still remains a mystery. Yet innovations in X-ray crystallogra-
phy, electron microscopy, and data analysis (think robots and
Google) are yielding answers about protein structures faster
than ever before. By Alan Dove
Structural biology shapes up
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LIFE SCIENCE TECHNOLOGIES Produced by the Science/AAAS Custom Publishing Office
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ìHit and runîThe X-ray beams themselves have improved too, with newer
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That development helped address another longstanding
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reason not to try to do that; in my lab we do that as a matter of
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cont.>
308 sciencemag.org/custom-publishing SCIENCE
LIFE SCIENCE TECHNOLOGIES
PROTEOMICS
Produced by the Science/AAAS Custom Publishing Office
DOI: 10.1126/science.opms.p1600107
Alan Dove is a science writer and editor based in Massachusetts.
FEATURED PARTICIPANTS
Centre for Integrative Systems Biology and Bioinformaticswww.imperial.ac.uk/integrative-systems-biology
Computation Institute,University of Chicagowww.ci.uchicago.edu
Direct Electronwww.directelectron.com
FEIwww.fei.com
Formulatrixwww.formulatrix.com
Gatanwww.gatan.com
Hampton Researchwww.hamptonresearch.com
Johns Hopkins Schoolof Medicinewww.hopkinsmedicine.org
MiTeGenwww.mitegen.com
Molecular Dimensionswww.moleculardimensions.com
Trinity College Dublinwww.tcd.ie
some protein samples we can do pretty well, since now we
have much more data, so we can apply or develop much more
sophisticated techniques to model the sequenceñstructure
relationship,î says Jinbo Xu, a senior fellow of the Computa-
tion Institute at the University of Chicago. Xu is the principal
investigator behind RaptorX, another online portal for predicting
secondary and tertiary protein structures.
In addition to template-based modeling, some researchers
are now exploring a technique called ìcontact prediction.î
This approach searches through vast troves of sequence data
to identify evolutionarily conserved amino acid interactions,
then uses those correlations to predict a novel sequenceís
folding patterns. ìThatís certainly proving very useful for
membrane-bound proteins where there are very few crystal
structures available,î says Sternberg, but he adds that ìyou
still need quite a large number of aligned sequencesî for con-
tact prediction to work.
Besides improving the underlying algorithms, computational
biologists have been working on making their system inter-
faces friendlier. ìWeíre very much following the sort of Google
approach of a very clean screen, not inundating the user with
many options, and really only delivering what the user wants,î
says Sternberg. It seems to be working. Sternberg estimates
that of the 44,000 unique users who accessed Phyre2 last year,
only a few hundred contacted him or Kelley for support.
Expanding options Xu and his colleagues have also embraced the user-friendly
model, with similar results. ìThe broader community is using
the tools, [and] the users of my server have very diverse back-
grounds,î he says. Researchers without structural biology train-
ing may not understand the limitations of the underlying algo-
rithms, so most of the major portals are designed to help users
interpret their results. RaptorX provides a quality evaluation
along with each protein model, scoring how likely the structure
"#$%�$��$������%�$�"�"����$� ���$����"��#$�$������$����$�����$
score, as well as individual scores for substructures down to the
amino acid level.
Because all of the major structure prediction tools are free
online, scientists can also hedge their bets by sending their
target sequences to all of them to see how the models dif-
fer. Another site, CAMEO,$�#�$%�#%#$��$�%�#$% �$�"�$����%$
protein-structure services. Each week, CAMEO sends a test
sequence to all of the participating servers, then calculates
benchmarks based on the systemsí speed, server reliability,
and other characteristics.
�"�$����%$%���#$�#�$ ��$�"#%"��%$#%����% #$��$����
��##�#$������"��$��$$��#��� ���#$#���"�$�$����#�$��%���$
emphasizes template-based modeling for particularly chal-
lenging proteins, while other portals are better suited for rapid
analysis of large numbers of relatively well-characterized
���%�"�$��"�"�#�$� ���$��$��#$$#�"%�$��$��"%"���$#���"��#�$
the ìPhyre Alarm,î for example, will send an email to research-
ers when new data allow the system to calculate an improved
model of their protein.
Regardless of the approach they choose, investigators seek-
ing protein structures should expect more good news. Survey-
ing the progress in all three techniques, Agard echoes the gen-
eral sentiment of structural biologists: ìItís a fabulous time in
% �$�$����$��$% ����#$%��������#$� �"%����%�!
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company, FEI, and sensors for them are made by it, Direct
Electron, and Gatan. Regardless of which vendors and instru-
ments one chooses, a complete cryo-EM system costs several
million dollars to buy, and several hundred thousand annually
to maintain and operate. ìOnly the richest labs or institutions
that are subsidizing this will be able to do this, and thatís not
a good situation in terms of national capabilities,î says Agard.
Germany, the United Kingdom, and China have all established
national-level funding for cryo-EM facilities, while the U.S. Na-
tional Institutes of Health is still deciding how to proceed.
Siri, what does the protein look like?Regardless of how fast X-ray crystallography and cryo-EM
develop, though, neither is likely to satisfy researchersí growing
desires for structural models. ìYou canít beat an experimentally
determined structure, [but] the challenge is the vast number of
�� ���������������� ������ ������ ����������������������
sible task of devising 3D structures for all the proteins,î says
Michael Sternberg, director of the Centre for Integrative
Systems Biology and Bioinformatics at Imperial College Lon-
don, United Kingdom.
To address that challenge, Sternberg and his colleague
Lawrence Kelley have focused on the decades-old dream of
molecular biologists: predicting protein structures directly from
sequence information. The teamís latest tool, Phyre2, uses
template-based modeling, a process that compares a se-
quence against a global database of previously solved protein
structures. Several other research groups have developed simi-
lar tools, which are accessible online to researchers worldwide.
These tools can yield impressive results, at least for pro-
tein families that are well-represented in the databases. ìOn
TTP Labtechwww.ttplabtech.com
University of California, Berkeleywww.berkeley.edu
University of California, San Franciscowww.ucsf.edu
University of Chicagowww.uchicago.edu
ADDITIONAL
RESOURCES
CAMEO
www.cameo3d.org
Phyre2
www.sbg.bio.ic.ac.uk/phyre2
RaptorX
raptorx.uchicago.edu
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