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User's Manual

The flow diagram of using our server

Our server successfully predicted the association between rosiglitazone for the treatment of Type II diabetes mellitus and fulvestrant for the treatment of hormone receptor positive metastatic breast cancer.

The thiazolidinediones and other PPAR-γ ligands show anti-tumour activity in various preclinical models of breast cancer and have an excellent toxicity profile in humans.[1]

Now we upload the active form of rosiglitazone to show how to use our server.

1. Login

For registered user, you can sign in with your username and password. For testers, click on the "QuickLogin" button. If you forget your password, you can reset your password with your mailbox by clicking on 'Forgot Password?'.

We use a system of user management in order to give every user a separate space to handle their uploaded drugs. Users can register freely and easily by clicking on the "Register" button.

2. Upload a drug molecule

After logging in, you will see a page which allows you to upload a drug molecular.

Click on the "Browse" button to upload a drug file. The drug should not be planar for it won't raise reasonable assessment of the interaction strength of this drug-protein interaction. The file should be in mol2 format with extension name of mol2/ml2 and make sure hydrogens and electricities are added (How to generate and prepare a mol2 file?). Usually, our server could check the suitability of your molecule. If the file suitability does not meet our demand, the results would be incredible. In order to protect the accessibility of other users, your uploaded file should not exceed the limitation of 12 kb. You can download our sample file naphthylamine.mol2 and upload it for a quick test.

3. Wait the interactome of your drug molecule to be constructed (several hours)

When your drug molecule file is uploaded correctly, our program starts to put your molecule in a queue automatically. You can click on the "Refresh" link to see the progress. If you upload our example file, it takes only several minutes to complete, however, for others it might take much longer.

If you are a registered user, you will see a list of your submissions like below. Click on the "Detail" button, you will first see detailed information of this drug.

4. Check the drugs associated with your molecule and their indications and ADRs information

After the docking progress is finished, you can see the association profile of your drug molecule. The "N/A" symbol in some fields does not hamper the result. You will not see the interactome of your molecule across the targetable proteins or the association of Interaction Profile unless the progress rate reaches 100%.

In the middle of this page, you can see a list of library drugs with absolute values of their association scores which reflect the similarity (or disparity) of their interaction profiles to your molecule. An association score is the association degree between your molecule and our library drugs based on their interaction profiles of the Chemical-Protein Interactome. It could be either positive or negative, and the maximum absolute value is 1. The known indications and ADRs information are provided, suggesting the underlying new indication or ADR of your molecule. You can enter a keyword in the "Search" box and press enter, to search for a drug name, ADR or indication. You can click on the "Clear" button to cancel your searching operation. A p-value is calulated by the Kolmogorov-Smirnov statistic, evaluating the probability of the similarity (or disparity) between the library drug and the uploaded molecule. The smaller the p-value is, the greater the association can be indicated. Some drugs have more than one isomers or ionization states. We keep all of them and name them as "somedrug 1", "somedrug 2" ... as more options for the users to analyze. You can view the difference of their structures via Jmol Applet. You can also download the whole table by simply clicking on the "download" link, and you can drag the downloaded text file into Excel to see the whole table.

By clicking on the button "See Chemical-Protein Interactome" at the top, you can view candidate off-targets that tend to interact with your molecule. In the right column of this page, you can view the basic information and 3D model of your molecular.

5. Check the detail information of the associated drugs

Click on the "Detail" button to see the detail information of the library drug. You will see the drug name, DrugBank ID, description, indication and its 3D model. You can see its interaction profile towards the targetable proteins in this page as well.

6. Check the candidate off-targets tend to interact with your molecule

In step 4, Click on the "See Chemical-Protein Interactome" button to see candidate off-targets that tend to interact with your molecule. The targetable proteins are ranked by the Z'-score. The server suggests candidate off-targets that tend to interact with your molecule. You can click on the "Result" button to visualize the binding pattern, with amino acid residues around 6.4Å of the drug molecule colored in the Applet.

The Docking Score fields represent the interaction strength of the molecule to the protein. The server utilizes a 2-directional Z-transformation function to convert docking scores into Z'-scores so as to increase accuracy.[2] The drug molecule tends to interact with the protein if Z'-score is less than -0.5. Z'-scores less or greater than -0.5 are presented in purple/black font. The targetable proteins are ranked by the Z'-score.

If you cannot see the Jmol Applet, or receive a message like "You do not have Java applets enabled in your web browser", you need to install Java Runtime Environment (JRE). JRE could be downloaded at http://www.java.com/en/download/manual.jsp for free. You can choose "label on/off" to show/hide the labels of the amino acid residues around 6.4Å of the drug molecule.

7. Log out

If you want to logout or switch to another account, you can click "Log out" in the left navigation menu, or close your browser, the session will automatically end.

References:

1 Fenner, M.H. et al., Peroxisome proliferator-activated receptor-gamma ligands for the treatment of breast cancer. Expert Opin Investig Drugs, 2005. 14(6): p. 557-68.

2 Yang, L. et al. SePreSA: a server for the prediction of populations susceptible to serious adverse drug reactions implementing the methodology of a chemical-protein interactome. Nucleic Acids Res. 2009;37(Web Server issue):W406-12.