The ModFOLD server version 3.0 help page
This page contains simple guidelines for using the new version of the ModFOLD server, sample input data which may be downloaded and submitted and examples of output from the server.Guidelines for using the server
The ModFOLD server version 3.0 requires the amino acid sequence of your target protein and either a single 3D model file in PDB format or a tarball containing a directory of multiple separate model files in PDB format.If you also decide to provide your email address then you will be sent a link to the graphical results and machine readable results when your predictions are completed. However, if you do not provide your email address then you must bookmark the results page and so that you may refer to the results when they become available.
Required - Sequence Data
In the text box labelled "Input sequence of protein target" please carefully paste in the full amino acid sequence for your target protein in single letter format. An example sequence (CASP9 target T0515) is shown below:
Sample sequence:
MIETPYYLIDKAKLTRNMERIAHVREKSGAKALLALKCFATWSVFDLMRDYMDGTTSSSL FEVRLGRERFGKETHAYSVAYGDNEIDEVVSHADKIIFNSISQLERFADKAAGIARGLRL NPQVSSSSFDLADPARPFSRLGEWDVPKVERVMDRINGFMIHNNCENKDFGLFDRMLGEI EERFGALIARVDWVSLGGGIHFTGDDYPVDAFSARLRAFSDRYGVQIYLEPGEASITKST TLEVTVLDTLYNGKNLAIVDSSIEAHMLDLLIYRETAKVLPNEGSHSYMICGKSCLAGDV FGEFRFAEELKVGDRISFQDAAGYTMVKKNWFNGVKMPAIAIRELDGSVRTVREFTYADY EQSLSIt is important that you provide the full sequence that corresponds to the sequence of residue coordinates in the model file. If your model does not contain numbering that corresponds directly to the order of residues in the sequence file then the server will attempt to renumber the residues in the model files accordingly. However, if there are residues in any model file that are not contained in the provided sequence then the prediction for that model will not complete.
Required - Model Data
Using the file selector labelled "Upload model/models" you may either upload a single PDB file (to obtain quality predictions for a single model), or multiple PDB files (to obtain quality predictions for many alternative models) in the form of a tarball (a tarred and gzipped directory).
Please ensure that each PDB file contains the coordinates for one model only. Please do not upload a single PDB file containing the coordinates for multiple alternative NMR models. The coordinates for multiple models should always be uploaded as a tarred and gzipped directory of separate files.
The server will attempt to automatically renumber the ATOM records in each model in order to match the residue positions in the sequence i.e. the coordinates for the first residue in the sequence will be renumbered "1" in each model file (if they aren't already), the coordinates for the second residue in the sequence will be numbered "2", and so on.
Sample PDB file:
An example file containing a single model for the sample sequence shown above can be downloaded below:
Model generated by IntFOLD-TS for CASP9 target T0515: IntFOLD-TS_TS1
Sample Tarball file:
The tarball should contain a directory of separate PDB files for your target sequence. This file should be similar in format to the tarballs of 3D models found on the CASP website.
An example tarball file containing multiple models for the sample sequence shown above can be downloaded below:
Tarball of multiple models for CASP9 target T0515: T0515.3D.srv.tar.gz
Steps to produce a tarball file for your own 3D models:
Linux/MacOS/Irix/Solaris/other Unix users
- Tar up the directory containing your PDB files e.g. type the following at the command line: tar cvf my_models.tar my_models/
- Gzip the tar file e.g. gzip my_models.tar
- Upload the gzipped tar file (e.g. my_models.tar.gz) to the ModFOLD server
In Windows you can use a free application such as 7-zip to tar and gzip your models.
- Download, install and run 7-zip
- Select the directory (folder) of model files to add to the .tar file, click "Add", select the "tar" option as the "Archive format:" and save the file as something memorable e.g. my_models.tar
- Select the tar file, click "Add" and then select the "GZip" option as the "Archive format:" - the file should then be saved as my_models.tar.gz
- Upload the the gzipped tar file (e.g. my_models.tar.gz) to the ModFOLD server
Required - Program selection
- ModFOLD3 - this method is the default option and can be used if you have either single or multiple models to compare. The method compares uploaded 3D models with those obtained from the from nFOLD4 fold recognition method using the ModFOLDclust2 model quality assessment method.
- ModFOLDclust2 - this method can only be used if you have multiple models to compare. The method uses a slow, accurate clustering based algrorithm to compare multiple models using structural alignments.
- ModFOLDclustQ - this method can only be used if you have multiple models to compare. The method uses a rapid clustering based algrorithm to compare multiple models which does not require CPU intensive structural alignments. If you have hundreds of models to compare this is the quickest option.
Optional - E-mail address
If you wish, you may provide your e-mail address. You will be sent a link to the graphical results and machine readable results when your predictions are completed.
Optional - Short name for sequence
If you wish, you may assign a short memorable name to your prediction job. This is useful so that you can identify particular jobs in your mailbox. This is particularly important because ModFOLD will not necessarily return your results in the order you submitted them. The set of characters you can use for the filename are restricted to letters A-Z (either case), the numbers 0-9 and the following other characters: .~_-
The name you specify will be included in the subject line of the e-mail messages sent to you from the server.
Output from the server
The ModFOLD server version 3.0 produces a results table containing numerical and graphical prediction results. The raw machine readable prediction data is also provided in CASP QA (QMODE2) format
Examples of output:
- ModFOLD3 results for the single IntFOLD server model (CASP9 target T0515)
- ModFOLD3 results for multiple server models (CASP9 target T0515)
- ModFOLDclust2 results for multiple server models (CASP9 target T0515)
- ModFOLDclustQ results for multiple server models (CASP9 target T0515)
The consistency of the global scores allows us to calculate a p-value which represents the probability that each model is incorrect. That is to say, that for a given predicted model quality score, the p-value is the proportion of models with that score that do not share any similarity with the the native structure (TM-score < 0.2). Each model is also assigned a colour coded confidence level depending on the p-value:
P-value cut-off | Confidence | Description |
p < 0.001 | CERT | Less than a 1/1000 chance that the model is incorrect. |
p < 0.01 | HIGH | Less than a 1/100 chance that the model is incorrect. |
p < 0.05 | MEDIUM | Less than a 1/20 chance that the model is incorrect. |
p < 0.1 | LOW | Less than a 1/10 chance that the model is incorrect. |
p > 0.1 | POOR | Likely to be a poor model with little or no similarity to the native structure. |
Fair usage policy
You are only allowed to have 1 job running at a time for each IP address, so please wait until your previous job completes before submitting further data. If you already have a job running then you will be notified and your uploaded data will be deleted. Once your job has completed your IP address will be unlocked and you will be able to submit new data.