localCIDER

version 0.1.21 - May 2023

Introduction

localCIDER is a Python package developed by the lab of Rohit Pappu at Washington University in St. Louis for calculating and plotting parameters associated with intrinsically disordered proteins (IDPs) and disodered regions (IDRs). localCIDER is the Python backend for CIDER, ( Classification of Intrinsically Disordered Ensemble Regions) - a webserver for the calculation of many of those same properties. Essentially, localCIDER lets you run CIDER’s calculations locally, allowing you to create custom analysis pipelines which do not rely on the webserver. It also allows you to take advantage of your own local computing hardware, rather than competing with everyone else for a common set of hardware provided by the Pappu lab.

This project was motivated by the need to rapidly and easily calculate the κ (kappa) parameter, as defined in the 2013 Das & Pappu PNAS paper [1], as well as provide a tool to easily plot a sequence on the diagram-of-states;

The original method for calculating κ involved an incredibly computationally expensive Monte Carlo step (used to determine the maximally segregated sequence), whereas localCIDER makes use of a newly developed algorithm that computes κ in O(1) time. More generally, localCIDER provides a wide range of sequence analysis routines for understanding, classifying, and designing disordered proteins. Beyond charge-based parameters, a wide range of additional parameters can also be calculated. localCIDER represents an ideal tool for the construction of a high-throughput sequence analysis pipelines, and we believe provides a direct route to explore the sequence-to-ensemble relationship of IDPs.

For more information please see the full documentation .