13th Community Wide Experiment on the
Critical Assessment of Techniques for Protein Structure Prediction
CASP13
CASP13 provides an independent mechanism for the assessment of methods of protein structure modeling. From May through July 2018, CASP organizers had been posting on this website sequences of unknown protein structures for modeling. Protein models were collected from May through mid-August, and evaluated as the experimental coordinates became available. In the Summer and Fall, the tens of thousands of models submitted by approximately 100 research groups worldwide were processed and evaluated. Independent assessors in each of the prediction categories bring objectivity, balance, and independent insight to this process. Tools for viewing, comparison, and analysis of submitted models are available at this site. The results of the CASP13 experiment are first made public immediately before the Conference in December.
The next round of CASP is planned to start in Spring 2020.

Targets Data guide Meeting Results CASP13 in news and blogs
Target List
Domain Definition
CASP13 prediction format
 
NMR restraint format (G.Montelione)
NMR data tutorial (G.Montelione)
SAXS data format (S.Tsutakawa, G.Hura)
XLMS data tutorial (A.Leitner, E.Trabjerg)
SANS data tutorial (A.Martel, S.Grudinin)
FRET data format (C.Seidel)
Energy Landscape Intro (G.Montelione)
FRET data tutorial (C.Seidel)
 
NMR and SAXS data webinars
XLMS data webinar
ProteinDynamics-FRET webinar
Abstracts
Program
Groups Info
Presentations
AUTOMATIC EVALUATION
Results of the official CASP13
assessments have been published in
Proteins 87(12), 2019.
 
Parseable Data
 
Rankings: Regular targets (T)
Rankings: Refinement targets (R)
Rankings: Data-Assisted targets (S,X,N,A)
Rankings: Multimeric targets (H,To)
Rankings: Contact predictions
Science
The Guardian
Forbes
The New York Times
Deep Mind blog
M.Alquraishi blog

CASP13 in numbers

Detailed description of the experiment

CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS. In the most recent CASP round, CASP12, nearly 100 groups from around the world submitted more than 50,000 models on 82 modeling targets (see Critical assessment of methods of protein structure prediction (CASP) - Round XII).

Goals New Call for targets Scope Related Timetable Registration Targets Format Assessment Results Conference Organizers

Goals

CASP assesses many aspects of modeling, including the accuracy of protein topologies, atom co-ordinates, and multi-protein assemblies. The experiment also examines the extent to which models can answer questions of biological interest, and how different types of sparse or low resolution experimental data can improve model accuracy.

CASP13 will begin in April 2018 and will address the following questions:

  • How similar are the models to the corresponding experimental structure?
  • Are domain orientations, subunit interactions, and the protein initeractions in complexes modeled correctly?
  • How much more accurate are template-based models than those that can be obtained by simply copying the best template?
  • How reliable are overall, residue, and atomic level error estimates?
  • How much can current refinement methods improve the accuracy of models?
  • How effective are approaches to predicting protein three dimensional contacts?
  • How well do the models help answering relevant biological questions?
  • How helpful is additional information, particularly sparse NMR data, chemical cross-linking, SAXS and FRET?
  • In which areas has there been progress since the last CASP?
  • Where can future effort be most productively focused?

New in CASP13

It is expected there will be more targets of biological complexes and membrane proteins, and more targets from EM data. The scope of the data-assisted experiment is expanded from SAXS and cross-linking to include sparse NMR data and FRET. The crosslinking technology has changed and improved protocols for the SAXS experiments should lead to more useful data. We also hope to have sparse data for some complexes. There will be further development of the 'does the model answer the biological question' analysis. And of course, we hope for even more spectacular progress in conventional modeling, building on the developments in CASP12, especially contact prediction. But as always, there will also be surprises! Anonymous registration will now be allowed, see the Anonymous policy for details.

Call for targets

The success of CASP to succeed is completely dependent on the generous help of experimental community. As in previous CASPs, protein crystallographers, NMR spectroscopists and cryo-EM scientists are asked to provide details of structures they expect to have made public before September 15, 2018. All types of protein structure may be good modeling targets, but membrane proteins and protein complexes are particularly needed. The last day for suggesting proteins as CASP targets is July 14, 2018. A target submission form is available here.
Details on the target collection and release procedures are available at our Q&A page.

Modeling categories

  • The High Accuracy Modeling category will include domains where majority of submitted models are of sufficient accuracy for detailed analysis. This category replaces the previous Template Based Modeling category.
  • The Topology category (formerly Free Modeling) will assess domains where submitted models are of relatively low accuracy.
  • The Contact Prediction category will assess the ability of methods to predict three dimensional contacts in targets structures.
  • The Refinement category will analyze success in refining models beyond the accuracy obtained in the initial submissions. For each target, one of the best initial models will be selected, and reissued as the starting structure for refinement.
  • The Assembly category will assess how well current methods can determine domain-domain, subunit-subunit, and protein-protein interactions. As in CASPs 11 and 12, we hope to work closely with CAPRI in this category.
  • The Accuracy Estimation category will assess the ability to provide useful accuracy estimates for the overall accuracy of models and at the domain and residue level.
  • The Data Assisted category will assess how much the accuracy of models is improved by the addition of sparse data. Targets for which such data are available will be re-released after initial data independent models have been collected, together with the available data. Data types are expected to include sparse NMR data, crosslinking data, SAXS data and FRET.
  • The Biological Relevance category will assess models on the basis of how well they provide answers to biological questions. Target providers will be asked to say what questions prompted the determination of the experimental structure. The usefulness of the models in answering those questions will be compared with the that of the experimental structures.

Timetable

  • April 2018 - Start of the registration for CASP13 prediction experiment.
  • April 18, 2018 - Start of the testing of server connectivity ("dry run" for server predictors).
  • May 1, 2018 - Release of the first CASP13 modeling targets.
  • May/June 2018 - Early bird registration for the December CASP13 conference.
  • July 16, 2018 - Last date for releasing regular targets.
  • July 31, 2018 - End of the regular modeling season.
  • August 20, 2018 - End of the refinement and data-assisted modeling season.
  • September 2018 - Collection of abstracts describing the methods used in CASP13.
  • October/November 2018 - Invitations to groups with the most accurate models and the most interesting methods to give talks at the CASP13 conference.
  • Novermber 2018 - Program of the conference finalized.
  • December 2018 - CASP13 Conference.

Registration

Participation is open to all.

If you are new to CASP and don't have an account with the Prediction Center, you will have to register with the Prediction Center first and only then proceed to CASP13 registration.

If you already have an account with the Prediction Center, you can go directly to the CASP13 registration page. Please check, though, that your basic registration information is current. If it has changed - please update it through the My Personal Data link from the main Menu.

Participants with servers are requested to register before April 18, 2018 as we are planning to start checking servers' format and connectivity on that day.

Targets

CASP13 modeling targets are available on the Target List page.

Model submission

Models can be submitted through the Prediction Submission form available from this web site or by the email provided on the CASP13 format page . Please comply with the instructions on submission procedures and format provided there. Server predictions will be made publicly available shortly after the closing of the prediction window for a specific target.

Assessment of models

As is the practice in CASP, assessment of the results will be made by the independent assessor teams. Assessment criteria will be based on those previously developed in CASP, but assessors may add new metrics they consider appropriate. Initial metrics will be discussed in the CASP forum before assessment begins. Where possible, results will also be evaluated using CASP12 criteria, so the effects of any changes in criteria can be appreciated.

The CASP 13 Assessors are as follows:

  • High accuracy models - Randy Read (Cambridge University, UK)
  • Topology - Matteo Dal Peraro (EPFL, Lausanne, Switzerland)
  • Contacts - Andras Fiser (Albert Einstein College of Medicine, New York, NY, USA)
  • Refinement - Randy Read (Cambridge University, UK)
  • Assembly (quaternary structure and complexes) - Jose Duarte (RCSB, San Diego, CA, USA)
  • Model accuracy estimation - Chaok Seok (Seoul National University, South Korea)
  • Data assisted models - Gaetano Montelione (Rutgers, USA), Susan Tsutakawa /Greg Hura (LBL, Berkeley, CA, USA), Andras Fiser (Albert Einstein College of Medicine, New York, USA)
  • Biological Relevance of models - Rosalba Lepore (University of Basel, Switzerland)

Click here for the list of assessors in all CASPs held so far.

In accordance with CASP policy, assessors cannot they take part in the relevant parts of the experiment as predictors. Participants must not contact assessors directly with queries, but rather these should be sent to the email address.

Results and publication

All CASP predictions and results of numerical evaluation will be made available through this web site shortly before the meeting. The proceedings will be published in a scientific journal (see publications of previous experiments). All participants will also be required to describe their methods in the abstracts (published locally at our web site) and encouraged to discuss them on the FORCASP forum. These contributions will be discussed and scored by other predictors, and this material will be taken into account in choosing some presentations at the conference. Also, those presenting posters should be prepared to give a short presentation at the conference, as some talks will be invited based on the discussion of poster sessions.

Conference

The conference to discuss results of the CASP13 experiment will be held at the Iberostar Paraiso Maya all-inclusive resort on the Riviera Maya (close to Playa del Carmen), Mexico, December 1-4, 2018 (starting at 6pm on the 1st and ending in the afternoon of the 4th). Registration for the meeting is now open.

Organizing committee

       John Moult, CASP chair and founder; IBBR, University of Maryland, USA
       Krzysztof Fidelis, founder, University of California, Davis, USA
       Andriy Kryshtafovych, University of California, Davis, USA
       Torsten Schwede, University of Basel, Switzerland
       Maya Topf, Birkbeck, University of London, UK

Scientific advisory board

       David Baker, University of Washington
       Michael Feig, Michigan State University
       Nick Grishin, University of Texas
       Andrzej Joachimiak, Argonne National Lab
       David Jones, University College, London
       Rachel Karchin, John Hopkins University
       Chaok Seok, Seoul National University
       Michael Sternberg, Imperial College, London

Funding

                   
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