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

被引:2
|
作者
Mathur, Yash [1 ]
Mohammad, Taj [2 ]
Anjum, Farah [3 ]
Shafie, Alaa [3 ]
Elasbali, Abdelbaset M. [4 ]
Uversky, Vladimir N. [5 ,6 ]
Hassan, Md. Imtaiyaz [2 ]
机构
[1] Jamia Millia Islamia, Dept Comp Sci, New Delhi 110025, India
[2] Jamia Millia Islamia, Ctr Interdisciplinary Res Basic Sci, New Delhi 110025, India
[3] Taif Univ, Dept Clin Lab Sci, Coll Appl Med Sci, POB 11099, Taif 21944, Saudi Arabia
[4] Jouf Univ, Coll Appl Sci Qurayyat, Clin Sci Lab, Jouf, Saudi Arabia
[5] Univ S Florida, Dept Mol Med, Tampa, FL 33620 USA
[6] Univ S Florida, Morsani Coll Med, Byrd Alzheimers Res Inst, Tampa, FL 33620 USA
来源
PROTEIN AND PEPTIDE LETTERS | 2022年 / 29卷 / 04期
关键词
PyPAn; !text type='python']python[!/text]-based protein analysis; protein analysis GUI; modelling method recommendation; protein sequence analysis; protein structure analysis; multiple protein sequence alignment; protein model refinement; PREDICTION; SERVER; ALIGNMENTS; TOOLS; MODEL;
D O I
10.2174/0929866529666220210155421
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:306 / 312
页数:7
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