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Protein & Peptide Letters

Editor-in-Chief

ISSN (Print): 0929-8665
ISSN (Online): 1875-5305

Research Article

PyPAn: An Automated Graphical User Interface for Protein Sequence and Structure Analyses

Author(s): Yash Mathur, Taj Mohammad, Farah Anjum, Alaa Shafie, Abdelbaset M. Elasbali, Vladimir N. Uversky and Md. Imtaiyaz Hassan*

Volume 29, Issue 4, 2022

Published on: 28 March, 2022

Page: [306 - 312] Pages: 7

DOI: 10.2174/0929866529666220210155421

Price: $65

Abstract

Background: Protein sequence and structure analyses have been essential components of bioinformatics and structural biology. They provide a deeper insight into the physicochemical properties, structure, and subsequent functions of a protein. Advanced computational approaches and bioinformatics utilities help solve several issues related to protein analysis. Still, beginners and non-professional may struggle when encountering a wide variety of computational tools and the sheer number of input parameter variables required by each tool.

Methods: We introduce a free-to-access graphical user interface (GUI) named PyPAn 'Python-based Protein Analysis' for varieties of protein sequence/structure analyses. PyPAn serves as a universal platform to analyze protein sequences, structure, and their properties. PyPAn facilitates onboard analysis of each task in just a single click. It can be used to calculate the physicochemical properties, including instability index and molar extinction coefficient, for a protein. PyPAn is one of the few computational tools that allow users to generate a Ramachandran plot and calculate solvent accessibility and the radius of gyration (Rg) of proteins at once. In addition, it can refine the protein model along with computation and minimization of its energy.

Results: PyPAn can generate a recommendation for an appropriate structure modelling method to employ for a query protein sequence. PyPAn is one of the few, if not the only, Python-based computational GUI tools with an array of options for the user to employ as they see fit.

Conclusion: PyPAn aims to unify many successful academically significant proteomic applications and is freely available for academic and industrial research uses at https://hassanlab.org/pypan.

Keywords: PyPAn, python-based protein analysis, protein analysis GUI, modelling method recommendation, protein sequence analysis, protein structure analysis, multiple protein sequence alignment, protein model refinement.

Graphical Abstract
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