CASP (Critical Assessment of protein Structure Prediction) is in search
for targets for the upcoming CASP15 modeling experiment (starting in May
2022). CASP community experiments aim to advance the state of the art in
protein structure modeling. Every other year since 1994, CASP collects
information on soon-to-be released experimental structures, passes on
sequence data to the structure modeling community, and collects blind
predictions of structure for assessment. Typically, about 100 modeling
groups from around the world participate. Results of CASP experiments
are assessed by leaders in the field
(http://predictioncenter.org/index.cgi?page=assessors_list
<http://predictioncenter.org/index.cgi?page=assessors_list>), and
published in special issues of the journal PROTEINS (see
https://onlinelibrary.wiley.com/toc/10970134/2021/89/12 for the latest
issue).
Following the 2020 CASP14 experiment, it is hard to find a structural
biologist who has not heard about the success of deep learning methods
in modeling protein structures, particularly by the AlphaFold and more
recently RosettaFold. As a result of these advances, computed protein
structures are becoming much more widely used in a broadening range of
applications. Since CASP14, the protein modeling community has
intensified development of these methods and extended their application
to include modeling of protein complexes and protein ensembles. CASP15
will provide definitive insight into how successful these new
developments are.
CASP15’s success depends on generosity of the experimental community in
providing targets as ground truth against which to assess the
computation methods. Over the years more than 150 structure
determination groups have provided over 1100 targets for CASP
challenges. For CASP15, we are requesting submission of all types of
experimental structures determined by X-ray crystallography,
cryo-electron microscopy and NMR as potential targets, but are
particularly interested in the following:
1. High resolution structures of single proteins. Because of the high
accuracy of the new computational methods, it is becoming difficult to
distinguish experimental error from computational error in low
resolution structures.
2. Structures with few or no known sequence relatives. Consistently
accurate computed structures for this class of target requires methods
that do not depend on evolutionary relationships.
3. Protein complexes. Deep learning methods already show increased
performance in this area, and a range of complexes is needed to
establish exactly how powerful these are. Assessment will be in
partnership with CAPRI, as in other recent CASPs.
4. RNA structures, RNA complexes, and protein RNA complexes. Many more
RNA structures are now being determined experimentally, opening this
area for more extensive rigorous assessment.
5. Proteins with clearly determined alternative conformations. An
obvious extension beyond single protein structures is the calculation of
ensembles of conformations. The new computational methods are already
being applied to this problem, but there is a paucity of definitive
experimental data to assess these against, which may limit this category.
6. Protein-organic ligand complexes. Deep learning methods are also
being applied to these structures. We are exploring including this
category in CASP15. A major challenge is obtaining suitable targets.
We also plan to include modeling assisted by sparse experimental data,
in collaboration with experimental groups in NMR, SAXS, and crosslinking
mass spectrometry. For that, protein material is needed (this is not
expected for most targets, but if available, it would be much
appreciated!).
So, if you have suitable targets in any if these areas, we would very
much appreciate you getting in touch by replying to this email or
writing to [email protected]
<mailto:[email protected]>or suggesting your target directly
through the CASP15 target entry page:
http://www.predictioncenter.org/casp15/targets_submission.cgi
<http://www.predictioncenter.org/casp14/targets_submission.cgi>.
Note that CASP target providers are regularly invited to contribute to
CASP special journal issue papers (e.g.
https://onlinelibrary.wiley.com/doi/epdf/10.1002/prot.26223,
https://onlinelibrary.wiley.com/doi/10.1002/prot.26247), and we plan to
continue this practice in the future.
Thank you,
Andriy Kryshtafovych, for CASP15 organizers
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