Prediction of Hot Spots by Using Structural Neighborhood Properties

PredHS2 Help Getting Started

Input data can be structure files in PDB format or PDB codes. The input structure should contain at least two chain identifiers forming the interface and the interface definition. One can query multiple structures in one run (maximum allowed 10 structures). Please follow the descriptions for the input format. Users could leave their email address; PredHS2 will send the prediction results to the address. Titles also could be specified for the user to distinguish their different jobs. Private Key is set to protect your structure and analysis. Please refer to Figure 1.

Figure 1. Job submission.

The server will check the validity of the input structure, and once confirmed, process to the secend step to select the query protein and its partners. If the selection is done, please click the button "submit" to run the job (Figure 2). Users will then be directed to the result page with job status. Book the link if you want to check your results later. However, the analysis could also be retrieved by user email or job ID in the result page.

Figure 2. Select the query protein and its partners.

PredHS2 will return a lists of residue ids which were predicted to be hot spots. The red residues in the query sequence are predicted hot spots. Users can download the results in text. By default, PredHS2 predicts a interface residue to be a hot spot when the associated score is greater than or equal to 0.5 but this cutoff is adjustable by the user. In order to visualize the 3D structures of the prediction resutls, users can click "View in 3D". (Figure 3)

Figure 3. Prediction results.

The information of the query job is shown at the top. The sturctures of the query protein and its partners will be shown in Jsmol. Predicted hot spots are rendered in different colors from white to red, according to the probability from the lowest to the highest (Figure 4).

Figure 4. Prediction results and visulization.

Users can view the predicted hot spots with output scores listed at the bottom. Interactive operations are also provided (Figure 5).

Figure 5. Interactive operation.

An example

Please follow the link to see an example.


[1].   Deng L, Zhang QC, Chen Z, Meng Y, Guan J and Zhou S. PredHS: a web server for predicting protein–protein interaction hot spots by using structural neighborhood properties. Nucleic Acids Research, 42(W1):W290-W295 (2014) [PubMed]
[2].   Deng L, Guan J, Wei X, Yi Y, Zhang QC and Zhou S. Boosting Prediction Performance of Protein–Protein Interaction Hot Spots by Using Structural Neighborhood Properties. Journal of Computational Biology, 20(11):878–891 (2013) (Presented at RECOMB 2013)[PubMed]