Results Recalculated in 2019
Retrospective view

Description of the experiment

Goals Scope Related Timetable Participation Targets Predictions Format Assessment Results Meeting Organizers

Goals

The main goal of CASP is to obtain an in-depth and objective assessment of our current abilities and inabilities in the area of protein structure prediction. To this end, participants will predict as much as possible about a set of soon to be known structures. These will be true predictions, not ‘post-dictions’ made on already known structures.

CASP7 will particularly address the following questions:

  1. Are the models produced similar to the corresponding experimental structure?
  2. Is the mapping of the target sequence onto the proposed structure (i.e. the alignment) correct?
  3. Have similar structures that a model can be based on been identified?
  4. Are comparative models more accurate than can be obtained by simply copying the best template?
  5. Has there been progress from the earlier CASPs?
  6. What methods are most effective?
  7. Where can future effort be most productively focused?

Scope

Tertiary structure predictions. For CASP7, categories have been redefined to reflect developments in methods. The 'Template based modeling' category will include all former comparative modeling, homologous fold based models and some analogous fold based models. As in CASP6, the 'Template free modeling' category will include models of proteins with previously unseen folds and hard analogous fold based models.

High resolution models. This new category will include a subset of tertiary structure models where the backbone is sufficiently accurate that the details of side chains, loops, and active sites can be meaningfully assessed. Particular attention will be paid to success in refining these models beyond the quality obtained by simply copying a best template. A separate assessor will judge these high accuracy modeling cases.

Other predictions. As in previous CASPs, we will be assessing the ability of predictors to define boundaries of structural domains, detect residue-residue contacts and identify disordered regions in target proteins. Function prediction, a new category introduced in CASP6, will again be assessed in CASP7. As suggested at the CASP6 meeting, we will also evaluate ability of predictors to judge on quality of models (without knowing native structures) and reliability of predicting certain residues in the structure.

Related Experiments

There will be additional activities included in or related to CASP7, which extend its scope.

Large scaling benchmarking: It is hoped that the results of well run benchmarking experiments such as EVA and LIVEBENCH will also be discussed at the CASP meeting.

SAC-CASP7: Alike to 2002 and 2004, the CASP meeting will be joined by the Student Addendum Conference. SAC-CASP7 will use the same conference facilities as CASP7. It will start (tentatively) the day before CASP7 and will last one day.

Timetable

Registration for the experiment starts in April. The first targets are expected to be available at the beginning of May. The prediction season will run for approximately three months from May through July. The CASP meeting will take place at the end of November, and approximately one month before that, groups with the most accurate and interesting predictions will receive invitations to give talks. There will also be discussion of predictions and methods on the FORCASP web site.

Participation

Participation is open to all. Intending participants, and those interested in receiving mailings concerning progress of the experiment should register for the experiment. The predictors with servers are requested to register immediately as we are planning on having a dry run for servers in mid-April.

Targets

For the experiment to succeed, it is essential that we obtain the help of the experimental community. As in previous CASPs, we will invite protein crystallographers and NMR spectroscopists to provide details of structures they expect to have made public before October 1, i2006. A target submission form will be available at this web site in mid-April. Prediction targets will be made available through this web site. All targets will be assigned an expiry date, and predictions must be received and accepted before that expiration date.

Submission of Predictions

Predictions must be submitted to this web site in CASP format. For 3D coordinate predictions, this is a simple PDB-like file with consecutive numbering of residues 1 -> N and a small number of required headers.

Assessment of Predictions

As in previous CASPs, independent assessors will evaluate the predictions. Assessors will be provided with the results of numerical evaluation of the predictions, and will judge the results primarily on that basis. They will be asked to focus particularly on the effectiveness of different methods. Numerical evaluation criteria will as far as possible be similar to those used in previous CASPs, although the assessors may be permitted to introduce some additional ones.

There are four assessors, representing expertise in the template-based modeling, template-free modeling, high accuracy modeling and function prediction:
       Torsten Schwede (University of Bazel, Switzerland) - for template based modeling
       Neil Clarke (Genome Institute of Singapore) - for template free modeling
       Randy Read (University of Cambridge, UK) - for high resolution modeling
       Alfonso Valencia (CNB, Madrid) - for function prediction

In accordance with CASP policy, assessors are not directly involved in the organization of the experiment, nor can they take part in the experiment as predictors. Predictors must not contact assessors directly with queries, but rather these should be sent to the casp@predictioncenter.org email address. Click here for the list of previous CASP assessors.

Results and Publication

All CASP predictions and evaluations will be made available through this web site shortly before the meeting. The proceedings of the meeting will be published. All participants will also be encouraged to fully report their results and methods on the FORCASP web site. Contributions to the site will be discussed and scored by other predictors, and this material will be taken into account in choosing some presentations at the meeting.

Meeting

A meeting to evaluate the results of the prediction experiment will be held at the Asilomar Conference Center (Pacific Grove, California, USA) on November 26-30, 2006. The meeting will be limited to about 200 participants and precedence will be given to active predictors. Some financial assistance will be available for the most successful predictors.

Organizing Committee

       John Moult, CARB, University of Maryland, USA

       Krzysztof Fidelis, University of California, Davis, USA
       Tim Hubbard, Welcome Trust Sanger Institute, Hinxton, UK
       Andriy Kryshtafovych, University of California, Davis, USA
       Burkhard Rost, Columbia University, New York, USA
       Anna Tramontano, University of Rome, Italy


Formats for Prediction Submission

General rules

  • Server models should be returned automatically to servers AT predictioncenter.org following a query from CASP7 distribution server

  • Predictions for CASP7 may be submitted in 7 separate formats:
      TS    # 3D atomic coordinates (Tertiary Structure) prediction
      AL    # Format to express unambiguous ALignments to PDB entries
      RR    # Residue-Residue separation distance prediction
      DR    # Order-Disorder Regions prediction
      DP    # Domain boundary prediction
      FN    # Function prediction
      QA    # Quality assessment
    
    

  • One team may make a prediction of a target by submitting up to five models in TS/AL, RR, DR, DP, FN and QA formats (models in AL format are considered equivalent to those in TS format and will be translated to TS internally before evaluation). Most of the evaluation and assessment will focus on the model labeled '1' (model index 1, see MODEL record).

  • Each submission may contain only one of the seven format categories.

  • Submission of each model begins with PFRMAT and ends with END record.

  • Each submission may contain only one model, beginning with the MODEL record, ending with END, and no target residue repetitions.

  • Submission of a duplicate model (same target, format category, group, model index) will replace previously accepted model, provided it is received before the target has expired.
    Note: models in AL format are considered equivalent to those in TS format.

  • Each submitted model is automatically verified by the format verification server. Only accepted models will be assigned an ACCESSION CODE. A unique ACCESSION CODE is composed from the number of the target, prediction format category, prediction group number, and model index.
       Examples:
    
       Accession code  T0044TS005_2  has the following components:
         T0044   target number
         TS      Tertiary Structure (PFRMAT TS)
         005     prediction group 5
         2       model index 2 (by default considered as FINAL/REFINED)
    
       Accession code  T0044TS005_2u  has the following components:
         T0044   target number
         TS      Tertiary Structure (PFRMAT TS)
         005     prediction group 5
         2u      model index 2 UNREFINED set of coordinates 
    


Format description

All submissions contain records described below. Each of these records must begin with a standard keyword. In all submissions standard keywords must begin in the first column of a record. The keyword set is as follows:
PFRMAT     Format specification code:  TS , AL , RR , DR, DP, FN, QA 
TARGET     Target identifier from the CASP7 target table
AUTHOR     XXXX-XXXX-XXXX   Registration code of the Group Leader 
SCORE      Reliability of the model (optional) 
REMARK     Comment record (may appear anywhere after the first 3 required lines, optional)
METHOD     Records describing the methods used
MODEL      Beginning of the data section for the submitted model
PARENT     Specifies structure template used to generate the TS/AL model 
TER        Terminates independent segments of structure in the TS/AL model
END        End of the submitted model

Models should be submitted in Plain Text format.
One model per submission is a rule for 'human groups' and recommendation
for servers. Servers can also reply to our request by a single email with
all models included one after the other. Only 5 first models will be considered.
PLEASE DON'T USE 'tab' AS A SEPARATOR. PLEASE USE 'space' INSTEAD.


Record PFRMAT should appear on the first line of the prediction and is used for all submissions.

   PFRMAT TS
     TS  indicates that submission contains 3D atomic coordinates
         in standard PDB format

   PFRMAT RR
     RR  indicates that submission contains residue-residue 
         separation distance prediction

   PFRMAT AL
     AL  indicates that submission contains unambiguous alignments
         to PDB entries

   PFRMAT DR
     DR  indicates that submission contains order-disorder regions
         prediction

   PFRMAT DP
     DP  indicates that submission contains domain prediction

   PFRMAT FN
     FN  indicates that submission contains function prediction

   PFRMAT QA
     QA  indicates quality ranking submission


Record TARGET should appear on the second line of the prediction and is used for all submissions.

   TARGET Txxxx
     Txxxx indicates id of the target predicted.


Record AUTHOR should appear on the third line of the prediction and is used for all submissions.

 For human groups:
   AUTHOR XXXX-XXXX-XXXX
          XXXX-XXXX-XXXX indicates the Group Leader's registration code.
          This code is the prediction submission code obtained upon
          CASP7 group registration.
          Members of prediction groups who intend to submit predictions
          should use the registration code of the Group Leader for all
          predictions submitted by that group.

 For server groups:
   AUTHOR MY_GROUP_NAME     
          where MY_GROUP_NAME is a name selected for the group at registration.

 Alternative way of identification for server groups:
   REMARK AUTHOR MY_GROUP_NAME
 


SCORE Optional. This record may be used to report a model reliability score. It will not influence the evaluation.


REMARK Optional. PDB style 'REMARK' records may be used anywhere in the submission. These records may contain any text and will in general not influence evaluation.


Records METHOD are used for all submissions.
These records describe the methods used. Predictors are urged to provide as full a description of the methods as possible, including references, data libraries used, and values of default and non-default parameters. These descriptions will be made available via the Prediction Center WEB pages as well as printed along with the other materials distributed at the meeting. Length of 100 - 500 words is suggested.


Record MODEL is used for all submissions.
Signifies the beginning of model data (3D atomic coordinates, an unambiguous alignment to a PDB entry, residue-residue separation distance prediction and order-disorder region predictions).

   MODEL  n  [REFINED|UNREFINED]
     n          Model index n is used to indicate predictor's ranking
                according to her/his belief which model is closest to the 
                target structure (1 <= n <= 5). Model index is included
                automatically in the ACCESSION CODE. All models with index
                higher than 5 will be discarded.
     REFINED    The set of coordinates labeled REFINED will be considered
                as a final model (to allow the evaluation of the results
                of an automated refinement process, such as molecular 
                dynamics). Models submitted without any label: REFINED or 
                UNREFINED will be considered by default as final.
     UNREFINED  Coordinates labeled UNREFINED will be compared only to 
                the final set (REFINED) with the same model index n, to 
                evaluate the effectiveness of the refinement method. If 
                UNREFINED model is submitted, a REFINED model must be 
                submitted as well. The letter "u" will be added to the 
                model index in the ACCESSION CODE of the UNREFINED model.


Record PARENT is used for all submissions in the TS (and AL) format.
PARENT record indicates structure templates used to generate any independent segment of MODEL (see description of the TS format below). The PARENT record should be placed as the first record of any such independent segment. Only one PARENT record per structure segment is allowed.

   PARENT N/A
     Indicates an ab initio prediction, not directly based on any known
     structure. Note that this is the only indication in the file that the
     prediction is ab initio, so is a critical piece of information.

   PARENT NONE [n1 n2]
     Indicates that the predictor believes that there is no structure in
     the present PDB that is close enough to be used as a template. This
     is an entry requested by those predictors who use threading and
     sequence comparison methods. With structural genomics projects being
     designed to determine the structure of proteins with novel folds, the
     ability to predict when a fold is unknown is becoming increasingly
     important, and predictors are urged to make such submissions.
     Delimiters n1 n2 indicate the range of the target sequence predicted
     as having no homologue in the current PDB.
     Omission of n1 n2 indicates the entire target (see Example 1 (C)).

   PARENT mabc_A
     Indicates that the model or the independent segment of structure is
     based on a single PDB entry mabc chain A (use _A to indicate chain A).
     Most threading and sequence search submissions would now be submitted
     with this form of the PARENT record. A comparative modeler using a
     single parent structure would also use this form. Note that, in order
     to be accepted, the code must correspond to a current PDB entry.

   PARENT mcdc ndef_g [ohij_k ...]
     Is used only in comparative modeling and indicates that the model is
     based on more than one structure template. Up to five PDB chains
     may be listed here with additional detailed information included in
     the METHOD records. In threading and sequence search, subdomains of
     the target structure found to correspond to different known folds
     should be submitted as independent segments of structure with
     reference to only one PDB chain per segment.  


Record TER is used to terminate an independent segment of structure (PFRMAT TS and PFRMAT AL).

   TER


3D atomic coordinates (PFRMAT TS).
Standard PDB atom records are used for the atomic coordinates. Format of the submission requires that 80 column long records are used. These may be spaces when needed (see target template PDB files as provided in specific target descriptions available through the CASP7 target table). This requirement is necessitated by some of the software used in the evaluation of predictions.

Coordinates for each model or an independent structure segment should begin with a single PARENT record and terminate with a TER record (see above).

It is requested that coordinate data be supplied for at least all non-hydrogen main chain atoms, i.e. the N, CA, C and O atoms of every residue. Specifically, if only CA atoms are predicted by the method, predictors are encouraged to build the main chain atoms for every residue before submission to CASP. One program that can make such a conversion is Maxsprout server of Liisa Holm and co-workers. (If only CA atoms were submitted it would not be possible to run most of the analysis software, which would severely limit the evaluation of that prediction.) When multiple independent segments of structure are used in a prediction, they will be evaluated separately with no assumption of a common frame of reference between the segments. For any given MODEL, no target residue may be repeated among all such independent structure segments. Potential multi-domain nature of targets will be addressed in the evaluation even if the prediction is made in a single frame of reference (i.e. without separation into multiple segments of structure). For such predictions segmentation should only be used to allow multiple model predictions (effectively up to 5 predictions for each such domain).

   Notes:
     - atoms for which a prediction has been made must contain "1.0" in
       the occupancy field; those for which no prediction is made must
       either contain "0.0" in that field or be skipped altogether
     - error estimates, in Angstroms, when given should be provided in the 
       temperature factor field


An unambiguous alignment to a PDB entry used for threading predictions (PFRMAT AL).
Alignment for each model or an independent structure segment should begin with a single PARENT record and terminate with a TER record (see above). The (four column) alignment data records provide: target residue one letter symbol, target residue sequence number, PDB residue one letter symbol, and PDB residue sequence number with an insertion code if necessary (see Example 3):

   aa1 n1  aa2 n2

   Note:
     - residues for which no prediction is made must be skipped
     - if a chain ID is specified in the PDB template of the target, then 
       the target residue sequence number should be composed of a chain ID 
       and residue number, e.g. A2, B44

The PDB code with chain extension of the structure the alignment is based on should be placed in the PARENT record. Only one PDB code per independent structure segment is allowed. PDB codes should refer to structures containing at least the main chain atomic coordinates (see the TS format). As in the case of coordinate submissions, when multiple independent segments of structure are used in a prediction, they will be evaluated separately with no assumption of a common frame of reference between the segments. For any given MODEL, no target residue may be repeated among all such independent structure segments. Potential multi-domain nature of targets will be addressed in the evaluation even if the prediction is made in a single frame of reference (i.e. without separation into multiple segments of structure). For such predictions segmentation should only be used to allow multiple model predictions (effectively up to 5 predictions for each such domain).
Note: The facility to translate sequence - structure alignments (AL format) into standard PDB atom records (TS format) is available as an additional AL2TS service.


Residue-Residue separation prediction (PFRMAT RR).
Data in this format are inserted between MODEL and END records of the submission file.
Format for the predicted separation distance between pairs of residues. The distance is defined as the separation between C-beta atoms (C-alpha for glycine residues).

The (five column) RR format:

   i  j  d1  d2  p

   Notes (see Example 2):
     - entire target sequence should be split over multiple lines with a
       maximum of 50 residues per line
     - for intrachain residue-residue contacts residue number indices 
       i and j should be used for distance specification (i < j), i.e. 
       only one diagonal of the separation matrix should be supplied
     - the distances d1 and d2 (real numbers) should indicate the range of 
       Cb-Cb distance predicted for the residue pair (C-alpha for glycines)
     - the real number p should range from 0.0 - 1.0 to indicate
       probability of the distance falling between the predicted range
     - residue 'contacts' (defined here - as in CASP2 - as Cb-Cb<8A) can be 
       predicted with this format as:
         i  j  0  8  p
     - any pair NOT listed is assumed to be NOT considered by predictor


Order-disorder regions prediction (PFRMAT DR).
Data in this format are inserted between MODEL and END records of the submission file.
The (three column) format record consists of residue code, Order/Disorder prediction code, and a number specifying the associated confidence level:

   aa  OD  p
The symbols for the 2 state order/disorder prediction are 'O'=order, 'D'=disorder. Last column should indicate a probability of a residue being in the disordered region. The value of this confidence level is in the range of 0.0 - 1.0. The entire sequence of the target should always be given. If parts cannot be predicted a probability of 0.5 should be used (see Example 5).


Domain boundary prediction (PFRMAT DP).
Data in this format are inserted between MODEL and END records of the submission file.
You may also specify PARENT field (optional) if you used homologues in assigning domains. It should be only one parent field per model and order of parents should correspond to the domain number, i.e. parent listed first corresponds to the domain assigned by you as number 1 and so on.
The format record consists of consecutive residue number n , residue code aa, domain number D and reliability score p (a real number between 0 (unreliable) and 1 (sure), optional).

   n  aa  D  p
The domain numbers are Arabic numerals going from 1 (for the first domain) to N for the N-th domain (which allows split domains to be easily coded). Put a dash '-' instead of a domain number if you cannot predict the domain for a particular residue. (see Example 6).


Protein function prediction (PFRMAT FN).
Data are inserted between MODEL and END records of the submission file (see Example 7 at the bottom of the page).
The data consist of four lines, each line starting with one of the following keywords

GO Molecular Function:
EC number:
Binding site:
Prediction techniques:

and any additional number of lines starting with the keyword

Comment:

The format for each of the lines is described below (angle brackets designate optional/additional data and should not be included into the prediction; semicolon separates several entries on one row, e.g. different GO functions or different binding sites, etc. ; comma separates entries within the same logical block, e.g. numbers of residues within the same binding site or numbers of residues related to GO category):

GO Molecular Function: N1 <, res1 - res2 ; N2 , res3-res4 ; ...>
** Ni is a Genome Ontology identifier; resi (i=1, 2, ...) is a residue number in the target

EC number: N1.N2.N3.N4 <, res1-res2 ; M1.M2.M3.M4 , res3-res4 ; ...>
where Ni (Mi), i=1-4, are integer numbers from the Enzyme Nomenclature Table
** Non enzymes should be labeled as 0.0.0.0

Binding site: res1, res2, ...
   or
Binding site: res1 - res2, <res3 - res4>, ...
** Residues considered as binding sites are those in direct contact with heteroatoms bound in the structure of the target protein. For the purposes of binding site residues predictors should be aiming to predict residues that have any atom in contact with the ligand at a distance of 0.5A plus the van der Waals radii. For example under this defintion the vast majority of single magnesium atoms are in contact with 2-4 residues per chain and ATP is usually bound by 11-18 residues per chain.
Over-prediction of binding residues will not be advantageous.

Prediction techniques: N1.N2.N3.N4.N5.N6
where Ni (i=1-6) is either 0 (for "not used") or 1 (for "used") in a vector of six numbers (e.g. 1.1.0.0.1.0) corresponding to:
N1 Sequence analysis
N2 Feature based predictions (e.g. sequence composition, postranslational modifications, etc.)
N3 Predictions based on structural information
N4 Text mining and information extraction
N5 GO database (used in any way other than for deducing the numbers for submission)
N6 Manual annotation

Comment: free text
** The predictors are encouraged to use this section to include the description of their predictions (eg EC name, GO definition). Although this section will not be evaluated it might be useful in the case of any changes in GO codes and it will provide useful information for the next function evaluation.


Quality assessment prediction (PFRMAT QA).
Data are inserted between MODEL and END records of the submission file. You may submit your quality assessment prediction in one of the two different modes:
QMODE 1 :   global model quality score (MQS - one number for a model)
QMODE 2 :   MQS and error estimate on per-residue basis.

The first line of data should specify mode identifier, i.e. QMODE (see Example 8).

In both modes, the first column in each line contains model identifier (file name of the accepted 3D prediction). The second column contains reliability score for a model as a whole. The reliability score is a real number between 0.0 and 1.0 (1.0 being a perfect model). If you don't provide MQS for a model please put "X" in the corresponding place. If you don't want to additionally provide error estimates on per residue basis (QMODE 1), your data table will consist of these two columns only.
If you do additionally provide residue error estimates (QMODE 2), each consecutive column should contain error estimate in Angstroms for all the consecutive resides in the target (i.e., column 3 corresponds to residue 1 in the target, column 4 - to residue 2 and so on). This way data constitute a table (Number_of_models_for_the_target) BY (Number_of_residues_in_the_target + 1). Do not skip columns if you are not predicting error estimates for some residues - instead put "X" in the corresponding column.
Please specify in the REMARKS what you consider to be an error estimate for a residue (CA location error, geometrical center error, etc.).

Note. Please, be advised that a QA record line may be very long and then some editors/mailing programs may force line wrap potentially causing unexpected parsing errors. To avoid this problem we recommend that you split long lines into shorter sublines (50-100 columns of data) by yourself. Our parser will consider consecutive sublines (starting with the line containing evaluated model name and ending with the line containing the next model name or tag END) a part of the same logical line.




END record is used for all predictions and indicates the end of a single model submission.


Predictions of multichain targets.
Atomic coordinates should contain chain IDs as provided in template files. In residue-residue contact predictions residue indices should be composed of chain ID and residue number, e.g. A2, B44 (see Example 4B).


Example 1. Atomic coordinates (Tertiary Structure)

The primary CASP7 format used for comparative modeling, threading and ab initio submission categories.

(A) An example of comparative modeling prediction. As this model is labeled UNREFINED, submission of a REFINED model is also required.

PFRMAT TS
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1  UNREFINED
PARENT 1abc 1def_A
ATOM      1  N   GLU     1      10.982  -9.774   1.377  1.00  0.50
ATOM      2  CA  GLU     1       9.623  -9.833   1.984  1.00  0.50
ATOM      3  C   GLU     1       8.913 -11.104   1.521  1.00  0.50
ATOM      4  O   GLU     1       9.187 -11.630   0.461  1.00  0.50
ATOM      5  CB  GLU     1       8.814  -8.614   1.546  1.00  0.50
ATOM      6  CG  GLU     1       7.372  -8.754   2.039  1.00  0.50
ATOM      7  CD  GLU     1       7.339  -8.625   3.562  1.00  0.50
ATOM      8  OE1 GLU     1       8.370  -8.307   4.131  1.00  0.50
ATOM      9  OE2 GLU     1       6.284  -8.846   4.132  1.00  0.50
ATOM     10  N   THR     2       7.998 -11.599   2.304  1.00  1.60
ATOM     11  CA  THR     2       7.266 -12.832   1.907  1.00  1.60
ATOM     12  C   THR     2       6.096 -12.456   1.005  1.00  1.60
ATOM     13  O   THR     2       5.008 -12.217   1.466  1.00  1.60
ATOM     14  CB  THR     2       6.731 -13.533   3.157  1.00  1.60
ATOM     15  OG1 THR     2       7.662 -13.379   4.220  1.00  1.60
ATOM     16  CG2 THR     2       6.526 -15.019   2.864  1.00  1.60
ATOM     17  N   VAL     3       6.308 -12.396  -0.278  1.00  1.70
ATOM     18  CA  VAL     3       5.190 -12.030  -1.187  1.00  1.70
ATOM     19  C   VAL     3       3.954 -12.870  -0.844  1.00  1.70
ATOM     20  O   VAL     3       2.834 -12.471  -1.090  1.00  1.70
ATOM     21  CB  VAL     3       5.608 -12.274  -2.641  1.00  1.70
ATOM     22  CG1 VAL     3       5.542 -13.771  -2.959  1.00  1.70
ATOM     23  CG2 VAL     3       4.664 -11.514  -3.573  1.00  1.70
ATOM     24  N   GLU     4       4.146 -14.029  -0.272  1.00  1.70
ATOM     25  CA  GLU     4       2.976 -14.882   0.086  1.00  1.60
ATOM     26  C   GLU     4       2.153 -14.190   1.175  1.00  1.50
ATOM     27  O   GLU     4       0.942 -14.141   1.109  1.00  1.40
ATOM     28  CB  GLU     4       3.465 -16.238   0.597  1.00  1.30
ATOM     29  CG  GLU     4       2.336 -17.264   0.479  1.00  1.20
ATOM     30  CD  GLU     4       2.929 -18.671   0.391  1.00  1.10
ATOM     31  OE1 GLU     4       4.056 -18.846   0.823  1.00  1.00
ATOM     32  OE2 GLU     4       2.246 -19.551  -0.108  1.00  0.90
TER
END
(B) A model consisting of 2 independent structure segments (could be a target modeled from two PDB domains, where relative orientation is unknown; could be 2 fragments predicted by ab initio methods - ab initio example shown). In a single MODEL no residue should appear twice among all such segments.
PFRMAT TS
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
PARENT N/A
ATOM      1  N   GLU     1      10.982  -9.774   1.377  1.00  0.50
ATOM      2  CA  GLU     1       9.623  -9.833   1.984  1.00  0.50
ATOM      3  C   GLU     1       8.913 -11.104   1.521  1.00  0.50
ATOM      4  O   GLU     1       9.187 -11.630   0.461  1.00  0.50
ATOM      5  CB  GLU     1       8.814  -8.614   1.546  1.00  0.50
ATOM      6  CG  GLU     1       7.372  -8.754   2.039  1.00  0.50
ATOM      7  CD  GLU     1       7.339  -8.625   3.562  1.00  0.50
ATOM      8  OE1 GLU     1       8.370  -8.307   4.131  1.00  0.50
ATOM      9  OE2 GLU     1       6.284  -8.846   4.132  1.00  0.50
ATOM     10  N   THR     2       7.998 -11.599   2.304  1.00  1.60
ATOM     11  CA  THR     2       7.266 -12.832   1.907  1.00  1.60
ATOM     12  C   THR     2       6.096 -12.456   1.005  1.00  1.60
ATOM     13  O   THR     2       5.008 -12.217   1.466  1.00  1.60
ATOM     14  CB  THR     2       6.731 -13.533   3.157  1.00  1.60
ATOM     15  OG1 THR     2       7.662 -13.379   4.220  1.00  1.60
ATOM     16  CG2 THR     2       6.526 -15.019   2.864  1.00  1.60
ATOM     24  N   GLU     4       4.146 -14.029  -0.272  1.00  1.70
ATOM     25  CA  GLU     4       2.976 -14.882   0.086  1.00  1.60
ATOM     26  C   GLU     4       2.153 -14.190   1.175  1.00  1.50
ATOM     27  O   GLU     4       0.942 -14.141   1.109  1.00  1.40
ATOM     28  CB  GLU     4       3.465 -16.238   0.597  1.00  1.30
ATOM     29  CG  GLU     4       2.336 -17.264   0.479  1.00  1.20
ATOM     30  CD  GLU     4       2.929 -18.671   0.391  1.00  1.10
ATOM     31  OE1 GLU     4       4.056 -18.846   0.823  1.00  1.00
ATOM     32  OE2 GLU     4       2.246 -19.551  -0.108  1.00  0.90
TER
PARENT N/A
ATOM     17  N   VAL     3       6.308 -12.396  -0.278  1.00  1.70
ATOM     18  CA  VAL     3       5.190 -12.030  -1.187  1.00  1.70
ATOM     19  C   VAL     3       3.954 -12.870  -0.844  1.00  1.70
ATOM     20  O   VAL     3       2.834 -12.471  -1.090  1.00  1.70
ATOM     21  CB  VAL     3       5.608 -12.274  -2.641  1.00  1.70
ATOM     22  CG1 VAL     3       5.542 -13.771  -2.959  1.00  1.70
ATOM     23  CG2 VAL     3       4.664 -11.514  -3.573  1.00  1.70
TER
END
(C) Threading/Fold Recognition prediction stating that target has no homologue in the current PDB.
PFRMAT TS
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
PARENT NONE
TER
END


Example 2. Residue-Residue contact prediction

The flexibility offered by the new format allows algorithms parameterized to predict any distance range to be used. Below is an example of how to use the new residue-residue separation distance format to submit a prediction of residue contacts defined as Cb-Cb distances < 8 A.
PFRMAT RR
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
HLEGSIGILLKKHEIVFDGC       # <- entire target sequence (up to 50 
HDFGRTYIWQMSD              #    residues per line)
1  9  0  8  0.70        
1 10  0  8  0.70           # <- indices of residues: i and j (integers), 
1 12  0  8  0.60           # <- the range of Cb-Cb distance predicted
1 14  0  8  0.20           #    for the residue pair: d1 and d2 (real),
1 15  0  8  0.10           # <- probability of the distance between 
1 17  0  8  0.30           #    Cb atoms being within the specified
1 19  0  8  0.50           #    range: p (real)
2  8  0  8  0.90
3  7  0  8  0.70
3 12  0  8  0.40
3 14  0  8  0.70
3 15  0  8  0.30
4  6  0  8  0.90
7 14  0  8  0.30
9 14  0  8  0.50
END


Example 3. An alternative alignment format for Threading/Fold Recognition predictions

Alignments will be converted into a 3D structures.

(A) Format to express unambiguous alignments to PDB entries 'mabc_A' and 'nefg'.

PFRMAT AL
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
PARENT mabc_A
M  21    V  11 
P  22    D  12  
N  23    A  12A 
F  24    F  12B 
A  25    L  13  
P  32    D  22  
N  33    A  23 
F  34    F  24 
A  35    L  25  
TER
PARENT nefg
E  75    T  73   
T  76    T  74   
V  77    A  75  
D  78    D  76  
G  79    D  77  
R  80    R  78  
TER
END
(B) Format to express unambiguous alignments to PDB entry 'mabc_D'. An example of how to use the AL format to submit a prediction of the target with a chain name of 'A'.
PFRMAT AL
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
PARENT mabc_D
M  A21    V  11 
P  A22    D  12  
N  A23    A  12A 
F  A24    F  12B 
A  A25    L  13  
P  A32    D  22  
N  A33    A  23 
F  A34    F  24 
A  A35    L  25  
TER
END


Example 4. Predictions of multichain targets (chains A and B)

(A) An example of 3D atomic coordinates model prediction.
PFRMAT TS
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1 
PARENT N/A
ATOM     17  N   VAL A   3       6.308 -12.396  -0.278  1.00  1.70
ATOM     18  CA  VAL A   3       5.190 -12.030  -1.187  1.00  1.70
ATOM     19  C   VAL A   3       3.954 -12.870  -0.844  1.00  1.70
ATOM     20  O   VAL A   3       2.834 -12.471  -1.090  1.00  1.70
ATOM     21  CB  VAL A   3       5.608 -12.274  -2.641  1.00  1.70
ATOM     22  CG1 VAL A   3       5.542 -13.771  -2.959  1.00  1.70
ATOM     23  CG2 VAL A   3       4.664 -11.514  -3.573  1.00  1.70
ATOM     24  N   GLU A   4       4.146 -14.029  -0.272  1.00  1.70
ATOM     25  CA  GLU A   4       2.976 -14.882   0.086  1.00  1.60
ATOM     26  C   GLU A   4       2.153 -14.190   1.175  1.00  1.50
ATOM     27  O   GLU A   4       0.942 -14.141   1.109  1.00  1.40
ATOM     28  CB  GLU A   4       3.465 -16.238   0.597  1.00  1.30
ATOM     29  CG  GLU A   4       2.336 -17.264   0.479  1.00  1.20
ATOM     30  CD  GLU A   4       2.929 -18.671   0.391  1.00  1.10
ATOM     31  OE1 GLU A   4       4.056 -18.846   0.823  1.00  1.00
ATOM     32  OE2 GLU A   4       2.246 -19.551  -0.108  1.00  0.90
REMARK 
REMARK  NOTE: Predictor should NOT use TER separator between chains 
REMARK        if multichain independent segment of structure has to 
REMARK        be evaluated as a one fragment
REMARK
ATOM      1  N   GLU B   1      10.982  -9.774   1.377  1.00  0.50
ATOM      2  CA  GLU B   1       9.623  -9.833   1.984  1.00  0.50
ATOM      3  C   GLU B   1       8.913 -11.104   1.521  1.00  0.50
ATOM      4  O   GLU B   1       9.187 -11.630   0.461  1.00  0.50
ATOM      5  CB  GLU B   1       8.814  -8.614   1.546  1.00  0.50
ATOM      6  CG  GLU B   1       7.372  -8.754   2.039  1.00  0.50
ATOM      7  CD  GLU B   1       7.339  -8.625   3.562  1.00  0.50
ATOM      8  OE1 GLU B   1       8.370  -8.307   4.131  1.00  0.50
ATOM      9  OE2 GLU B   1       6.284  -8.846   4.132  1.00  0.50
ATOM     10  N   THR B   2       7.998 -11.599   2.304  1.00  1.60
ATOM     11  CA  THR B   2       7.266 -12.832   1.907  1.00  1.60
ATOM     12  C   THR B   2       6.096 -12.456   1.005  1.00  1.60
ATOM     13  O   THR B   2       5.008 -12.217   1.466  1.00  1.60
ATOM     14  CB  THR B   2       6.731 -13.533   3.157  1.00  1.60
ATOM     15  OG1 THR B   2       7.662 -13.379   4.220  1.00  1.60
ATOM     16  CG2 THR B   2       6.526 -15.019   2.864  1.00  1.60
TER
END
(B) An example of how to use the RR format to submit a prediction of interchain (chains A and B) residue-residue contacts defined as Cb-Cb distances < 8 A.
PFRMAT RR
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
HLEGSIGILLKKHEIVFDGC         # <- entire target sequence (up to 50 
HDFGRTYIWQMSD                #    residues per line)
A1 B9   0  8  0.70        
A1 B10  0  8  0.70           # <- indices of residues: Ai and Bj, 
A1 B12  0  8  0.60           # <- the range of Cb-Cb distance predicted
A1 B14  0  8  0.20           #    for the residue pair: d1 and d2 (real),
A1 B15  0  8  0.10           # <- probability of the distance between 
A1 B17  0  8  0.30           #    Cb atoms being within the specified
A1 B19  0  8  0.50           #    range: p (real)
A2 B8   0  8  0.90
A3 B7   0  8  0.70
A3 B12  0  8  0.40
A3 B14  0  8  0.70
A3 B15  0  8  0.30
A4 B6   0  8  0.90
A7 B14  0  8  0.30
A9 B14  0  8  0.50
END


Example 5. Order-disorder regions prediction

Example of order-disorder regions prediction.

PFRMAT DR
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
H D 0.70           # <- residue code,
L D 0.80           # <- order/disorder assignment code,
E D 0.80           # <- the number specifying the associated
G D 0.60           #    confidence level: 0.5 - residue not predicted 
S D 0.90           #                     >0.5 - disordered region 
I O 0.50           #                     <0.5 - ordered region
G O 0.40
I O 0.40
L O 0.30
L O 0.50
K O 0.50
K O 0.30
H O 0.20
E O 0.20
I O 0.40
V O 0.45
F D 0.60
D D 0.90
G D 0.60
C D 0.80
END


Example 6. Domain boundary prediction

PFRMAT DP
TARGET Txxxx
AUTHOR xxxx-xxxx-xxxx
REMARK Predictor remarks
METHOD Description of methods used
METHOD Description of methods used
METHOD Description of methods used
MODEL  1
PARENT 1abc 1efg   # optional; 1abc was used to assign domain #1, 1efg - #2  
1 H 1 0.90         
2 L 1 0.90        
3 E 1 0.90       
4 G 1 0.90           
5 S 1 0.90          
6 I 1 0.90         
7 G 1 0.60
8 I - 0.60
9 L - 0.80
10 L 2 0.80
11 K 2 0.90
12 K 2 0.90
13 H 2 0.90
14 E 2 0.90
15 I 2 0.90
16 V 2 0.75
17 F - 0.60
18 D 1 0.90
19 G 1 0.90
20 C 1 0.90
END


Example 7. Function prediction

PFRMAT FN
TARGET T0283
AUTHOR 1111-2222-3333
REMARK Predictor remarks
METHOD Description of methods used
MODEL  1
GO Molecular Function: 00000049 ; 00005525
EC number: 3.6.5.3
Binding site: 50-54, 76-79 ; 81, 82, 93-95
Prediction techniques: 1.1.0.0.1.0
Comment: my comment
END


Example 8. Quality assessment prediction

(A) Global Model Quality Score

PFRMAT QA
TARGET T0283
AUTHOR 1111-2222-3333
METHOD Description of methods used
MODEL 1
QMODE 1
3D-JIGSAW_TS1 0.8 
FORTE1_AL1.pdb 0.7 
END
(B) Residue-based Quality Assessment (fragment of the table). Note, that this case includes case (A) and there is no need to submit QMODE 1 predictions additionlly to QMODE 2.

PFRMAT QA
TARGET T0283
AUTHOR 1111-2222-3333
REMARK Error estimate is CA-CA distance in Angstroms
METHOD Description of methods used
MODEL 1
QMODE 2
3D-JIGSAW_TS1 0.8 10.0 6.5 5.0 2.0 1.0 ... 
FORTE1_AL1.pdb 0.7 8.0 5.5 4.5 X X ... 
END
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