TITLE: Prediction of ligand binding using FunFOLD2
AUTHORS: Chris Berndsen

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block">Clues to functionality can be gleaned from comparing unknown or predicted structures with previously characterized structures of known function and characteristics. These scans can be biased against novel proteins or proteins with similar structures but distinct functions, but for initial guesses can be powerful. These methods align the structure and/or amino acid sequence to a database of structures with known ligand binding sites and look for structures with the similarity in amino acid composition, position, and overall 3-D similarity. The idea being that similar structures lead to similar functions. This protocol describes the use of the FunFOLD2 server which predicts ligand identity and binding site from the amino acid sequence. </div></div>

[STEPS]
?. [Uploading sequence]
Navigate to the FunFOLD2 server submission form.
?. [Uploading sequence]
Paste in your sequence in single letter amino acid code.
?. [Uploading sequence]
Provide an email address and a short name for your protein.  Record the short name as a note in this step.
?. [Uploading sequence]
Press Predict to submit your sequence.
FunFOLD takes 24 to 72 hours to respond.  You should record the results link as a note in this step in case you don't get the email.
?. [Analyzing data]
When the results are ready there will be four areas of results.
?. [Analyzing data]
At top is the predicted binding site in a homology model. The binding site is shown and labeled to be the amino acid numbers in the submitted sequence.Download the structure and view it in YASARA.
?. [Analyzing data]
Save your downloaded file as [date]_[sequencename]_[groupname]_FunFOLD2.pdbReplace [Group_name] with your name/group name without the brackets. Replace [sequence_name] with the name of the sequence.
?. [Analyzing data]
Indicate your file location as a link within a note on this step.
?. [Analyzing data]
Below this is information on the ligand identity and the binding site. The ligand identity is abbreviated as it would be in a crystal structure.
If there are multiple potential ligands, you will need to search each individually.
?. [Analyzing data]
To identify the ligand, in a new broswer window go to the RCSB (www.rcsb.org) and in the search bar, look for you ligand name and wait for the search options to drop down (do not press enter, just input the code and wait).Select in Chemical IDs to search the ligands database.
?. [Analyzing data]
The search should take you to an information page on the ligand lots of information and the name.
?. [Analyzing data]
Record the ligand binding residues and other statistics as well as the ligand identity.  Add rows as needed.  AB1Ligand binding residue(s)2Ligand code(s)3Ligand identity(ies)
AB1Ligand binding residue(s)2Ligand code(s)3Ligand identity(ies)
?. [Analyzing data]
Below the ligand information is a JSmol window for viewing the ligand and binding site in the browser. This is convienient for when you do not have a molecular visualization software available.
?. [Analyzing data]
The last section contains the quality of the fit.
?. [Analyzing data]
Explanation of scores:  AB1BDTalignComparison of the structural match in 3-D between known binding site and modeled binding site.  1 indicates a perfect prediction, while 0 is associated with a random and unreliable prediction.2IdentityNumber of amino acids in the binding site that are equivalent to the known binding site. 1 is a perfect match, 0 is imperfect match3Rescaled BLOSUM62An additional measure of binding site sequence match using the BLOSUM62 algorithm. 1 is a perfect match, 0 is an imperfect match.4Equivalent Residue Ligand DistanceFor the amino acids that are equivalent, this measure looks at how well the distances match. 1 is a perfect match, 0 is an imperfect match.5Model QualityScore based on the ModFOLDclust2 algorithm to give a sense of the overall match of the model.  1 is a perfect match, 0 is an imperfect match.6Predicted BDT scoreBinding site distance test indicates how far a predicted binding site residue is from the observed binding residue location.  1 indicates a perfect prediction, while 0 is associated with a random and unreliable prediction.7Predicted MCC scoreMatthews Correlation Coefficient score is a statistic for looking at accuracy of predicted vs. observed binding site amino acids.  1 indicates a perfect prediction, while 0 is associated with a random and unreliable prediction.
AB1BDTalignComparison of the structural match in 3-D between known binding site and modeled binding site.  1 indicates a perfect prediction, while 0 is associated with a random and unreliable prediction.2IdentityNumber of amino acids in the binding site that are equivalent to the known binding site. 1 is a perfect match, 0 is imperfect match3Rescaled BLOSUM62An additional measure of binding site sequence match using the BLOSUM62 algorithm. 1 is a perfect match, 0 is an imperfect match.4Equivalent Residue Ligand DistanceFor the amino acids that are equivalent, this measure looks at how well the distances match. 1 is a perfect match, 0 is an imperfect match.5Model QualityScore based on the ModFOLDclust2 algorithm to give a sense of the overall match of the model.  1 is a perfect match, 0 is an imperfect match.6Predicted BDT scoreBinding site distance test indicates how far a predicted binding site residue is from the observed binding residue location.  1 indicates a perfect prediction, while 0 is associated with a random and unreliable prediction.7Predicted MCC scoreMatthews Correlation Coefficient score is a statistic for looking at accuracy of predicted vs. observed binding site amino acids.  1 indicates a perfect prediction, while 0 is associated with a random and unreliable prediction.
?. [Analyzing data]
Record the scores of the prediction below:  AB1BDTalign2Identity3Rescaled BLOSUM624Equivalent Residue Ligand Distance5Model Quality6Predicted BDT score7Predicted MCC score
AB1BDTalign2Identity3Rescaled BLOSUM624Equivalent Residue Ligand Distance5Model Quality6Predicted BDT score7Predicted MCC score
?. [Analyzing data]
If you have homology models from other methods (Phyre2, SWISS-Model, etc.) and refined any of those models, it is worth aligning the model with the ligand bound from  to all of these models to compare the predicted binding site.Different programs may predict different conformations for the binding site and by comparing the different models, the reliability of the prediction can be further assessed. If there are distinct binding site shapes, then the prediction may be less reliable.
?. [Analyzing data]
Export this protocol as a PDF and save it in your project folder.