PyPAn: An Automated Graphical User Interface for Protein Sequence and Structure Analyses
Document Type
Article
Publication Date
2022
Digital Object Identifier (DOI)
http://dx.doi.org/10.2174/0929866529666220210155421
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.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Protein & Peptide Letters, v. 29, issue 4, p. 306-312
Scholar Commons Citation
Mathur, Yash; Mohammad, Taj; Anjum, Farah; Shafie, Alaa; Elasbali, Abdelbaset M.; Uversky, Vladimir N.; and Hassan, Md. Imtaiyaz, "PyPAn: An Automated Graphical User Interface for Protein Sequence and Structure Analyses" (2022). Molecular Medicine Faculty Publications. 971.
https://digitalcommons.usf.edu/mme_facpub/971
