PASSer:

Protein Allosteric Sites Server


PASSer is developed by Tao research group from the Department of Chemistry at Southern Methodist University.

The computational resources are provided by SMU and the Center for Scientific Computing.

M2
Please refer to the Tutorial page for guidance.

If you find this server useful, please cite:
1. Tian, H., Jiang, X. Tao, P. PASSer: prediction of allosteric sites server. Machine Learning: Science and Technology, 2021, 2(3), p.035015.
2. Xiao S, Tian H, Tao P. PASSer2.0: Accurate Prediction of Protein Allosteric Sites Through Automated Machine Learning. ChemRxiv, 2021.

Contact Information:
Mailing Address:
Peng Tao
Department of Chemistry
Southern Methodist University
3215 Daniel Avenue
P.O. Box 750314
Dallas, TX 75275-0314

Office:
Fondren Science Room 143
Phone: (214) 768-8802
Fax: (214) 768-4089
E-mail: ptao@smu.edu