Comparative visualization of protein secondary structures
Jazyk angličtina Země Anglie, Velká Británie Médium electronic
Typ dokumentu časopisecké články
PubMed
28251875
PubMed Central
PMC5333176
DOI
10.1186/s12859-016-1449-z
PII: 10.1186/s12859-016-1449-z
Knihovny.cz E-zdroje
- Klíčová slova
- Molecular sequence analysis, Molecular structure and function, Molecular visualization,
- MeSH
- algoritmy MeSH
- molekulární modely MeSH
- proteiny chemie MeSH
- sekundární struktura proteinů * MeSH
- sekvence aminokyselin MeSH
- sekvenční seřazení MeSH
- simulace molekulární dynamiky * MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- proteiny MeSH
BACKGROUND: Protein function is determined by many factors, namely by its constitution, spatial arrangement, and dynamic behavior. Studying these factors helps the biochemists and biologists to better understand the protein behavior and to design proteins with modified properties. One of the most common approaches to these studies is to compare the protein structure with other molecules and to reveal similarities and differences in their polypeptide chains. RESULTS: We support the comparison process by proposing a new visualization technique that bridges the gap between traditionally used 1D and 3D representations. By introducing the information about mutual positions of protein chains into the 1D sequential representation the users are able to observe the spatial differences between the proteins without any occlusion commonly present in 3D view. Our representation is designed to serve namely for comparison of multiple proteins or a set of time steps of molecular dynamics simulation. CONCLUSIONS: The novel representation is demonstrated on two usage scenarios. The first scenario aims to compare a set of proteins from the family of cytochromes P450 where the position of the secondary structures has a significant impact on the substrate channeling. The second scenario focuses on the protein flexibility when by comparing a set of time steps our representation helps to reveal the most dynamically changing parts of the protein chain.
Zobrazit více v PubMed
Richardson JS. The anatomy and taxonomy of protein structure. Adv Protein Chem. 1981;34:167–339. doi: 10.1016/S0065-3233(08)60520-3. PubMed DOI
Holm L, Rosenström P. Dali server: conservation mapping in 3D. Nucleic Acids Res. 2010;38(Web Server issue):545–9. doi: 10.1093/nar/gkq366. PubMed DOI PMC
Shindyalov IN, Bourne PE. Protein structure alignment by incremental combinatorial extension (ce) of the optimal path. Protein Eng. 1998;11(9):739–47. doi: 10.1093/protein/11.9.739. PubMed DOI
Orengo CA, Taylor WR. SSAP: sequential structure alignment program for protein structure comparison. Methods Enzymol. 1996;266:617–35. doi: 10.1016/S0076-6879(96)66038-8. PubMed DOI
Zhang Y, Skolnick J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 2005;33(7):2302–309. doi: 10.1093/nar/gki524. PubMed DOI PMC
Pei J, Kim BH, Grishin NV. PROMALS3D: a tool for multiple protein sequence and structure alignments. Nucleic Acids Res. 2008;36(7):2295–300. doi: 10.1093/nar/gkn072. PubMed DOI PMC
Zhou P, Shang Z. 2D molecular graphics: a flattened world of chemistry and biology. Brief Bioinform. 2009;10(3):247–58. doi: 10.1093/bib/bbp013. PubMed DOI
Heinrich J, Burch M, O’Donoghue SI. On the use of 1D, 2D, and 3D visualisation for molecular graphics. In: 3DVis (3DVis), 2014 IEEE VIS International Workshop on 3DVis. IEEE: 2014. p. 55–60.
Stivala A, Wybrow M, Wirth A, Whisstock JC, Stuckey PJ. Automatic generation of protein structure cartoons with pro-origami. Bioinformatics. 2011;27(23):3315–316. doi: 10.1093/bioinformatics/btr575. PubMed DOI
Hutchinson EG, Thornton JM. Hera–a program to draw schematic diagrams of protein secondary structures. Proteins Struct Funct Bioinforma. 1990;8(3):203–12. doi: 10.1002/prot.340080303. PubMed DOI
Westhead DR, Slidel TWF, Flores TPJ, Thornton JM. Protein structural topology: Automated analysis and diagrammatic representation. Protein Sci. 1999;8(4):897–904. doi: 10.1110/ps.8.4.897. PubMed DOI PMC
Michalopoulos I, Torrance GM, Gilbert DR, Westhead DR. Tops: an enhanced database of protein structural topology. Nucleic Acids Res. 2004;32(suppl 1):251–4. doi: 10.1093/nar/gkh060. PubMed DOI PMC
Laskowski RA. Pdbsum new things. Nucleic Acids Res. 2009;37(Database issue):355–9. doi: 10.1093/nar/gkn860. PubMed DOI PMC
Todd AE, Orengo CA, Thornton JM. Domplot: a program to generate schematic diagrams of the structural domain organization within proteins, annotated by ligand contacts. Protein Eng. 1999;12(5):375–9. doi: 10.1093/protein/12.5.375. PubMed DOI
Wallace AC, Laskowski RA, Thornton JM. Ligplot: a program to generate schematic diagrams of protein-ligand interactions. Protein Eng. 1995;8(2):127–34. doi: 10.1093/protein/8.2.127. PubMed DOI
Schäfer T, May P, Koch I. Computation and visualization of protein topology graphs including ligand information. In: Böcker S, Hufsky F, Scheubert K, Schleicher J, Schuster S, editors. German Conference on Bioinformatics 2012. OpenAccess Series in Informatics (OASIcs), vol. 26. Dagstuhl: Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik; 2012.
Zemla A. Lga: a method for finding 3d similarities in protein structures. Nucleic Acids Res. 2003;31(13):3370–374. doi: 10.1093/nar/gkg571. PubMed DOI PMC
Stolte C, Sabir KS, Heinrich J, Hammang CJ, Schafferhans A, O’Donoghue SI. Integrated visual analysis of protein structures, sequences, and feature data. BMC Bioinforma. 2015;16 Suppl 11:7. doi: 10.1186/1471-2105-16-S11-S7. PubMed DOI PMC
O’Donoghue SI, Sabir KS, Kalemanov M, Stolte C, Wellmann B, Ho V, Roos M, Perdigao N, Buske FA, Heinrich J, Rost B, Schafferhans A. Aquaria: simplifying discovery and insight from protein structures. Nat Meth. 2015;12(2):98–9. doi: 10.1038/nmeth.3258. PubMed DOI
Nguyen KT, Ropinski T. Large-scale multiple sequence alignment visualization through gradient vector flow analysis. In: Biological Data Visualization (BioVis), 2013 IEEE Symposium On. IEEE: 2013. p. 9–16.
Touw WG, Baakman C, Black J, te Beek TAH, Krieger E, Joosten RP, Vriend G. A series of PDB-related databanks for everyday needs. Nucleic Acids Res. 2014;43(Database issue):364–8. PubMed PMC
Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, Kiefer F, Cassarino TG, Bertoni M, Bordoli L, Schwede T. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res. 2014;42(Webserver-Issue):252–8. doi: 10.1093/nar/gku340. PubMed DOI PMC
Bostock M, Ogievetsky V, Heer J. D3 data-driven documents. IEEE Trans Vis Comput Graph. 2011;17(12):2301–309. doi: 10.1109/TVCG.2011.185. PubMed DOI
Cojocaru V, Winn PJ, Wade RC. The ins and outs of cytochrome {P450s} Biochimica et Biophysica Acta (BBA) - Gen Subj. 2007;1770(3):390–401. doi: 10.1016/j.bbagen.2006.07.005. PubMed DOI
Hensen U, Meyer T, Haas J, Rex R, Vriend G, Grubmueller H. Exploring protein dynamics space: the dynasome as the missing link between protein structure and function. PLoS ONE. 2012;7(5):33931. doi: 10.1371/journal.pone.0033931. PubMed DOI PMC