Help for using DeepHomo server


1. About the DeepHomo

The DeepHomo is a deep learning-based model for accurate prediction of residue-residue contacts across homo-oligomeric protein interfaces by integrating sequential and structural information of monomers.


2. How to provide input for the monomer.

Users need to provide the 3D structure of the monomer which can be a experimental structrue from the PDB or a predicted model by a third party approach like I-TASSER. The DeepHomo server accepts two types of input for the monomer:

Only ONE type of input is needed for the subunit molecule. If more than one types of input is provided, the first one will be used.

3. How to obtain your DeepHomo results.

Once users submit your job, they will be redirected to a status web page showing the status of the job. The status page is automatically refreshed every 10 seconds until the job is finished. Users have three ways to obtain their prediction results. After the job is done, users will then be redirected to the result papge, from which they can download the following files

As the top 10 contacts are normally deemed as the most important ones, the result page provides an interactive view of the top 10 contacts using the NGL viewer, where two identical momomers are shown side-by-side, displaying the two corresponding residues of a contact. Users can choose to view any of the top 10 contacts or all together by different representations and styles.

The page also gives a summary of the rankings and residue pairs for the top 10 contacts. The predicted score ranges from 0.0 to 1.0. The higher a predicted score is, the more likely to be in contact the residue pairs are.

NOTE: It is recommended that users download their prediction results as soon as possible after the job is done, as the job results will only be stored on our server for two weeks.

© Lab of Bioinformatics and Molecular Modeling, huanglab@hust.edu.cn