PASSer:

Protein Allosteric Sites Server

Introduction

Allostery is the process by which proteins transmit perturbations caused by the binding effect at one site to another distal site. Allosteric process is fundamental in regulation of activity. The identification of allosteric sites is important for allosteric drug development and has attracted a wide range of interests.

To approach this problem, PASSer is designed for accurate allosteric sites prediction. Ensemble learning, consisting of eXtreme gradient boosting and graph convolutional neural network, is used to learn the physical properties and topology information. PASSer is further advanced to PASSer2.0 with automated machine learning.

PASSer is deployed with trained machine learning models and has been extensively tested to complete prediction within seconds.