The POST server is a web-based platform for fast and accurate protein oligomeric state prediction.
About trRosettaRNA
The input to POST is the amino acid sequence of the query protein. Shown in Figure 1, the POST works as follows.
(1) When the sequence of query protein is submitted, three different algorithms (POST-DP, POST-PL, POST-HH) are run to obtain homologous templates with known oligomeric state.
(2) These homologous templates can be used either separately or in combination to infer the oligomeric state.

Figure 1. The flowchart of the POST algorithm.
Based on the significance and number of putative templates, we measure the confidence of the prediction of a predicted state. The confidence of the model is defined as the maximum confidence for all predicted states.
Figure 2 shows the relationship between the confidence score cutoff and F1-score on the benchmark tests. The Person's correlation coefficients is 0.80.

Figure 2. The relationship between the confidence score cutoff and F1-score.
Job submission
Job submission guide:
(1) Input a protein sequence in
FASTA format .
(2) (Optional) Provide your email address.
(3) (Optional) Assign your target name.
(4) Submit.

Figure 3. The "Submit" section in POST home page.
Output explanation
The POST predicting results are generally summarized in a webpage, the link of which is sent to the user upon job completion if the email address has been provided during submission(
see an example of the POST output).
This section contains:
(1) Predicted oligomeric states.
(2) Probability distribution of oligomeric states.
(3) Model quality estimation.
(4) Download links for predicted probability.

Figure 4. The "Predicted oligomeric states" section in POST result page.
This section visualizes Template information including:
(1) Template information from POST-DP, POST-PL and POST-HH.
(2) Download links for templates.

Figure 5. The "Recognized Homolgous Templates" section in POST result page.
How to cite POST?
Please cite the following articles when you use the POST server:
Luo et al, Predicting the oligomeric state of proteins using multiple template detected by complementary alignment methods, submitted, 2024.
Need more help?
If you have more questions or comments about the server, please email yangjy

sdu.edu.cn.