Login Register Cart 0
Generic placeholder image

Protein & Peptide Letters

Editor-in-Chief

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

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
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

conference banner
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.

« Previous Next »
Graphical Abstract

[1]
Schwede, T.; Kopp, J.; Guex, N.; Peitsch, M.C. SWISS-MODEL: An automated protein homology-modeling server. Nucleic Acids Res., 2003, 31(13), 3381-3385.
[http://dx.doi.org/10.1093/nar/gkg520] [PMID: 12824332]
[2]
Fiser, A.; Sali, A. Modeller: Generation and refinement of homology-based protein structure models. Methods Enzymol., 2003, 374, 461-491.
[http://dx.doi.org/10.1016/S0076-6879(03)74020-8] [PMID: 14696385]
[3]
McGuffin, L.J.; Atkins, J.D.; Salehe, B.R.; Shuid, A.N.; Roche, D.B. IntFOLD: An integrated server for modelling protein structures and functions from amino acid sequences. Nucleic Acids Res., 2015, 43(W1), W169-73.
[http://dx.doi.org/10.1093/nar/gkv236] [PMID: 25820431]
[4]
Lambert, C.; Léonard, N.; De Bolle, X.; Depiereux, E. ESyPred3D: Prediction of proteins 3D structures. Bioinformatics, 2002, 18(9), 1250-1256.
[http://dx.doi.org/10.1093/bioinformatics/18.9.1250] [PMID: 12217917]
[5]
Chivian, D.; Kim, D.E.; Malmström, L.; Bradley, P.; Robertson, T.; Murphy, P.; Strauss, C.E.; Bonneau, R.; Rohl, C.A.; Baker, D. Automated prediction of CASP-5 structures using the Robetta server. Proteins, 2003, 53(Suppl. 6), 524-533.
[http://dx.doi.org/10.1002/prot.10529] [PMID: 14579342]
[6]
Källberg, M.; Margaryan, G.; Wang, S.; Ma, J.; Xu, J. RaptorX server: A resource for template-based protein structure modeling. Methods Mol. Biol., 2014, 1137, 17-27.
[http://dx.doi.org/10.1007/978-1-4939-0366-5_2] [PMID: 24573471]
[7]
Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc., 2015, 10(6), 845-858.
[http://dx.doi.org/10.1038/nprot.2015.053] [PMID: 25950237]
[8]
Wu, S.; Zhang, Y. MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information. Proteins, 2008, 72(2), 547-556.
[http://dx.doi.org/10.1002/prot.21945] [PMID: 18247410]
[9]
Zheng, W.; Zhang, C.; Bell, E.W.; Zhang, Y. I-TASSER gateway: A protein structure and function prediction server powered by XSEDE. Future Gener. Comput. Syst., 2019, 99, 73-85.
[http://dx.doi.org/10.1016/j.future.2019.04.011] [PMID: 31427836]
[10]
Zhang, W.; Yang, J.; He, B.; Walker, S.E.; Zhang, H.; Govindarajoo, B.; Virtanen, J.; Xue, Z.; Shen, H.B.; Zhang, Y. Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11. Proteins, 2016, 84(Suppl. 1), 76-86.
[http://dx.doi.org/10.1002/prot.24930] [PMID: 26370505]
[11]
Jayaram, B.; Dhingra, P.; Mishra, A.; Kaushik, R.; Mukherjee, G.; Singh, A.; Shekhar, S. Bhageerath-H: A homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins. BMC Bioinformatics, 2014, 15(Suppl. 16), S7.
[http://dx.doi.org/10.1186/1471-2105-15-S16-S7] [PMID: 25521245]
[12]
Ito, A.; Mukaiyama, A.; Itoh, Y.; Nagase, H.; Thogersen, I.B.; Enghild, J.J.; Sasaguri, Y.; Mori, Y. Degradation of interleukin 1β by matrix metalloproteinases. J. Biol. Chem., 1996, 271(25), 14657-14660.
[http://dx.doi.org/10.1074/jbc.271.25.14657] [PMID: 8663297]
[13]
Cock, P.J.; Antao, T.; Chang, J.T.; Chapman, B.A.; Cox, C.J.; Dalke, A.; Friedberg, I.; Hamelryck, T.; Kauff, F.; Wilczynski, B.; de Hoon, M.J. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics, 2009, 25(11), 1422-1423.
[http://dx.doi.org/10.1093/bioinformatics/btp163] [PMID: 19304878]
[14]
Wilkins, M.R.; Gasteiger, E.; Bairoch, A.; Sanchez, J.C.; Williams, K.L.; Appel, R.D.; Hochstrasser, D.F. Protein identification and analysis tools in the ExPASy serve Methods Mol. Biol., 1999, 112, 531-552.
[PMID: 10027275]
[15]
Gamage, D.G.; Gunaratne, A.; Periyannan, G.R.; Russell, T.G. Applicability of instability index for in vitro protein stability prediction. Protein Pept. Lett., 2019, 26(5), 339-347.
[http://dx.doi.org/10.2174/0929866526666190228144219] [PMID: 30816075]
[16]
Tabb, D.L. An algorithm for isoelectric point estimation. Available from: http://fields. scripps. edu/DTASelect/20010710-pI-Algorithm. pdf(Accessed July 01, 2011)..
[17]
Sievers, F.; Higgins, D.G. Clustal Omega for making accurate alignments of many protein sequences. Protein Sci., 2018, 27(1), 135-145.
[http://dx.doi.org/10.1002/pro.3290] [PMID: 28884485]
[18]
Blackshields, G.; Sievers, F.; Shi, W.; Wilm, A.; Higgins, D.G. Sequence embedding for fast construction of guide trees for multiple sequence alignment. Algorithms Mol. Biol., 2010, 5, 21.
[http://dx.doi.org/10.1186/1748-7188-5-21] [PMID: 20470396]
[19]
Johnson, M. NCBI BLAST: A better web interface., Nucleic Acids Res, 2008, 36(Web Server issue), W5-W9..
[http://dx.doi.org/10.1093/nar/gkn201]
[20]
Xu, D.; Xu, Y.; Uberbacher, E.C. Computational tools for protein modeling. Curr. Protein Pept. Sci., 2000, 1(1), 1-21.
[http://dx.doi.org/10.2174/1389203003381469] [PMID: 12369918]
[21]
Breda, A. Protein structure, modelling and applications. Bioinformatics in tropical disease research: A practical and case-study approach; National Center for Biotechnology Information: US, 2007.
[22]
Khan, F.I.; Wei, D.Q.; Gu, K.R.; Hassan, M.I.; Tabrez, S. Current updates on computer aided protein modeling and designing. Int. J. Biol. Macromol., 2016, 85, 48-62.
[http://dx.doi.org/10.1016/j.ijbiomac.2015.12.072] [PMID: 26730484]
[23]
Kolaskar, A.S.; Sawant, S. Prediction of conformational states of amino acids using a Ramachandran plot. Int. J. Pept. Protein Res., 1996, 47(1-2), 110-116.
[http://dx.doi.org/10.1111/j.1399-3011.1996.tb00817.x] [PMID: 8907507]
[24]
Durham, E.; Dorr, B.; Woetzel, N.; Staritzbichler, R.; Meiler, J. Solvent accessible surface area approximations for rapid and accurate protein structure prediction. J. Mol. Model., 2009, 15(9), 1093-1108.
[http://dx.doi.org/10.1007/s00894-009-0454-9] [PMID: 19234730]
[25]
Lobanov, M.Iu.; Bogatyreva, N.S.; Galzitskaia, O.V. Radius of gyration is indicator of compactness of protein structure Mol. Biol. (Mosk.), 2008, 42(4), 701-706. [Radius of gyration is indicator of compactness of protein structure.
[PMID: 18856071]
[26]
O’Boyle, N.M.; Banck, M.; James, C.A.; Morley, C.; Vandermeersch, T.; Hutchison, G.R. Open Babel: An open chemical toolbox. J. Cheminform., 2011, 3, 33.
[http://dx.doi.org/10.1186/1758-2946-3-33] [PMID: 21982300]
[27]
Gasteiger, E. Protein identification and analysis tools on the ExPASy server., The proteomics protocols handbook; , 2005, pp. 571-607..
[http://dx.doi.org/10.1385/1-59259-890-0:571]

Rights & Permissions Print Cite
Article Metrics
23
1
© 2024 Bentham Science Publishers | Privacy Policy