webPIPSA

Protein Interaction Property Similarity Analysis

Introduction

This PIPSA service is provided for the comparison of the electrostatic interaction properties of proteins. It permits the classification of proteins according to their interaction properties. PIPSA may assist in function assignment, the estimation of binding properties and enzyme kinetic parameters. See References for details.

You may also download the original PIPSA code, including a python wrapper called multipipsa. This allows to run PIPSA analysis on multiple sites of the protein and also provides comparative analysis of the binding properties of user-defined groups of proteins. See also the references page.

PIPSA source code is now bundled in a python wrapper: multipipsa: python wrapper for performing standalone PIPSA and comparison of the interaction properties of user-defined groups of proteins.

Method

To perform PIPSA on this webserver, you need to upload a set of related protein structures in PDB format. After calculation of the protein electrostatic potentials, the server will calculate similarity indices for all pairs of proteins based on the electrostatic similarity. These indices will be computed for complete protein 'skins' or for a user defined region. The similarity indices are then converted to electrostatic 'distances'. The electrostatic potential distance matrix is displayed in color coded form (heat map) and as a tree (epogram).

Start a PIPSA analysis (input PDB format coordinate files).

Start a PIPSA analysis (input SWISSPROT entries with EC annotation)^*.

^* This type of analysis involves a protein structural modelling step utilizing Modeller. Therefore this part is subject to the Modeller license conditions. Please obtain a Modeller license to use this service.

Funding and Acknowledgments

recent project funding:

This open source software was developed in part in the Human Brain Project funded from the European Union's Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreements No 720270 and No. 78907 (Human Brain Project SGA1 and SGA2).

For additional information on funding and acknowledgments, please go to our funding page