AutoPLI is a fullly automated server for predicting protein-ligand interactions. The server uses all available protein-ligand complex structures in current Protein Data Bank as the resource to improve prediction resutls. A hybrid strategy containing both template-based and docking-based methods was employed. For more details about the server and methods, please go to the "About" page or read the references (at the bottom of this page).

To submit a job, two inputs are required:
(1) A ligand structure in the MOL2 format;
(2) A target protein with UniProt access number/ID or 3D structure in the PDB format.

Detailed instructions about job submition and prediction results are described on the "Tutorial" page.

Job Submission
➺  A ligand structure in MOL2 format:  

➺  A target protein:  
? Find access number in UniProt database: http://www.uniprot.org
         OR
Upload a PDB structure ▼ upload a protein structure in PDB format:
&& the center of the binding site
? The box size will be automatically determined by the peptide length.
:
/ /


➺  Job name (optional):  

➺   Email address (optional)
? Optional but recommended.
If provided, you will receive an email notification after your job is completed.
:   

➺ Do not show my job on the queue page

   Example: Ligand structure : lig.mol2;
                     Protein receptor: UniProt AC Q96RI1 (UniProt ID NR1H4_HUMAN) or PDB file: rec.pdb (Binding site: 43.2 / 14.3 / 2.7)
References:
  1. Xu X, Duan R, Ma Z, Zou X. AutoPLI: A Fully Automated Server for Predicting Protein-ligand Interactions. (submitting)
  2. Xu X, Yan C, Zou X. Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015. Journal of Computer-Aided Molecular Design, 31: 689-699, 2017. [link]
  3. Duan R, Xu X, Zou X. Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor. Journal of Computer-Aided Molecular Design, 2017 (In Press). [link]