Abstract
Bioinformatic analysis of functionally diverse superfamilies can help to study the structure-function relationship in proteins, but represents a methodological challenge. The Mustguseal web-server can build large structure-guided sequence alignments of thousands of homologs that cover all currently available sequence variants within a common structural fold. The input to the method is a PDB code of the query protein, which represents the protein superfamily of interest. The collection and subsequent alignment of protein sequences and structures is fully automated and driven by the particular choice of parameters. Four integrated sister web-methods—the Zebra, pocketZebra, visualCMAT, and Yosshi—are available to further analyze the resulting superimposition and identify conserved, subfamily-specific, and co-evolving residues, as well as to classify and study disulfide bonds in protein superfamilies. The integration of these web-based bioinformatic tools provides an out-of-the-box easy-to-use solution, first of its kind, to study protein function and regulation and design improved enzyme variants for practical applications and selective ligands to modulate their functional properties. In this chapter, we provide a step-by-step protocol for a comprehensive bioinformatic analysis of a protein superfamily using a web-browser as the main tool and notes on selecting the appropriate values for the key algorithm parameters depending on your research objective. The web-servers are freely available to all users at https://biokinet.belozersky.msu.ru/m-platform with no login requirement.
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References
Suplatov D, Kirilin E, Švedas V (2016) Bioinformatic analysis of protein families to select function-related variable positions. In: Svendsen A (ed) Understanding enzymes. Pan Stanford Publishing, Singapore
Rozewicki J, Li S, Amada KM, Standley DM, Katoh K (2019) MAFFT-DASH: integrated protein sequence and structural alignment. Nucleic Acids Res 47(W1):W5–W10
Suplatov DA, Kopylov KE, Popova NN, Voevodin VV, Švedas VK (2018) Mustguseal: a server for multiple structure-guided sequence alignment of protein families. Bioinformatics 34(9):1583–1585
Shegay MV, Suplatov DA, Popova NN, Švedas VK, Voevodin VV (2019) parMATT: parallel multiple alignment of protein 3D-structures with translations and twists for distributed-memory systems. Bioinformatics 35(21):4456–4458
Krissinel E, Henrick K (2004) Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. Acta Crystallogr D Biol Crystallogr 60(12):2256–2268
Menke M, Berger B, Cowen L (2008) Matt: local flexibility aids protein multiple structure alignment. PLoS Comput Biol 4(1):e10
Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30(4):772–780
Suplatov D, Sharapova Y, Geraseva E, Švedas V (2020) Zebra2: advanced and easy-to-use web-server for bioinformatic analysis of subfamily-specific and conserved positions in diverse protein superfamilies. Nucleic Acids Res 48(W1):W65–W71
Suplatov D, Shalaeva D, Kirilin E, Arzhanik V, Švedas V (2014) Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity. J Biomol Struct Dyn 32(1):75–87
Suplatov D, Voevodin V, Švedas V (2015) Robust enzyme design: bioinformatic tools for improved protein stability. Biotechnol J 10(3):344–355
Suplatov D, Kirilin E, Arbatsky M, Takhaveev V, Švedas V (2014) pocketZebra: a web-server for automated selection and classification of subfamily-specific binding sites by bioinformatic analysis of diverse protein families. Nucleic Acids Res 42(W1):W344–W349
Suplatov D, Sharapova Y, Timonina D, Kopylov K, Švedas V (2018) The visualCMAT: a web-server to select and interpret correlated mutations/co-evolving residues in protein families. J Bioinform Comput Biol 16(02):1840005
Suplatov DA, Timonina DS, Sharapova YA, Švedas VK (2019) Yosshi: a web-server for disulfide engineering by bioinformatic analysis of diverse protein families. Nucleic Acids Res 47(W1):W308–W314
Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ (2009) Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25(9):1189–1191
Fesko K, Suplatov D, Švedas V (2018) Bioinformatic analysis of the fold type I PLP-dependent enzymes reveals determinants of reaction specificity in l-threonine aldolase from Aeromonas jandaei. FEBS Open Bio 8(6):1013–1028
Dong R, Peng Z, Zhang Y, Yang J (2018) mTM-align: an algorithm for fast and accurate multiple protein structure alignment. Bioinformatics 34(10):1719–1725
Pei J, Kim BH, Grishin NV (2008) PROMALS3D: a tool for multiple protein sequence and structure alignments. Nucleic Acids Res 36(7):2295–2300
Sharapova Y, Suplatov D, Švedas V (2018) Neuraminidase A from streptococcus pneumoniae has a modular organization of catalytic and lectin domains separated by a flexible linker. FEBS J 285(13):2428–2445
Hanson RM, Prilusky J, Renjian Z, Nakane T, Sussman JL (2013) JSmol and the next-generation web-based representation of 3D molecular structure as applied to proteopedia. Isr J Chem 53(3–4):207–216
Suplatov D, Sharapova Y, Shegay M, Popova N, Fesko K, Voevodin V, Švedas V (2019) High-performance hybrid computing for bioinformatic analysis of protein superfamilies. In: Voevodin V, Sobolev S (eds) Communications in computer and information science, vol 1129. Springer Nature, Switzerland AG, Basel
Gille C, Fähling M, Weyand B, Wieland T, Gille A (2014) Alignment-Annotator web server: rendering and annotating sequence alignments. Nucleic Acids Res 42(W1):W3–W6
Steffen-Munsberg F, Vickers C, Kohls H, Land H, Mallin H, Nobili A, Skalden L, van den Bergh T, Joosten HJ, Berglund P, Höhne M, Bornscheuer UT (2015) Bioinformatic analysis of a PLP-dependent enzyme superfamily suitable for biocatalytic applications. Biotechnol Adv 33(5):566–604
Webb B, Sali A (2017) Protein structure modeling with modeller. In: Kaufmann M, Klinger C, Savelsbergh A (eds) Functional genomics. Methods in molecular biology, vol 1654. Humana Press, New York
Suplatov D, Panin N, Kirilin E, Shcherbakova T, Kudryavtsev P, Švedas V (2014) Computational design of a pH stable enzyme: understanding molecular mechanism of penicillin acylase's adaptation to alkaline conditions. PLoS One 9(6):e100643
Söding J, Biegert A, Lupas AN (2005) The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res 33(Suppl. 2):W244–W248
Fischer JD, Mayer CE, Söding J (2008) Prediction of protein functional residues from sequence by probability density estimation. Bioinformatics 24(5):613–620
Craig DB, Dombkowski AA (2013) Disulfide by Design 2.0: a web-based tool for disulfide engineering in proteins. BMC Bioinformatics 14(1):346
Dani VS, Ramakrishnan C, Varadarajan R (2003) MODIP revisited: re-evaluation and refinement of an automated procedure for modeling of disulfide bonds in proteins. Protein Eng 16(3):187–193
Sadovnichy V, Tikhonravov A, Voevodin V, Opanasenko V (2017) “Lomonosov”: supercomputing at Moscow State University. In: Vetter JS (ed) Contemporary high performance computing. Chapman and Hall/CRC, New York
Acknowledgments
This work was supported by the Russian Foundation for Basic Research grant #18-29-13060 and carried out using the equipment of the shared research facilities of HPC computing resources at Lomonosov Moscow State University supported by the project RFMEFI62117X0011 [29].
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Suplatov, D., Sharapova, Y., Švedas, V. (2021). Mustguseal and Sister Web-Methods: A Practical Guide to Bioinformatic Analysis of Protein Superfamilies. In: Katoh, K. (eds) Multiple Sequence Alignment. Methods in Molecular Biology, vol 2231. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1036-7_12
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DOI: https://doi.org/10.1007/978-1-0716-1036-7_12
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