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1. 28 29 30 32 a Chapman B Chang J Biopython python tools for computational biology ACM SIGBIO Newslett 2000 20 15 19 Knight R Maxwell P Birmingham A Carnes J Caporaso JG Easton BC Eaton M Hamady M Lindsay H Liu Z et al PyCogent a toolkit for making sense from sequence Genome Biol 2007 8 8 R171 Martin J Letellier G Marin A Taly JF de Brevern AG Gibrat JF Protein secondary structure assignment revisited a detailed analysis of different assignment methods BMC Struct Biol 2005 5 17 Yang H Jossinet F Leontis N Chen L Westbrook J Berman H Westhof E Tools for the automatic identification and classification of RNA base pairs Nucleic Acids Res 2003 31 13 3450 3460 Rother M Rother K Puton T Bujnicki JM ModeRNA a tool for comparative modeling of RNA 3D structure Nucleic Acids Res 2011 39 10 4007 4022 de Berg M Cheong O van Kreveld M Overmars M Computational geometry algorithms and applications Third Editionth edition Berlin Heidelberg Springer Verlag 2008 Draper DE A guide to ions and RNA structure RNA 2004 10 3 335 343 Orengo CA Bray JE Hubbard T LoConte L Sillitoe Analysis and assessment of ab initio three dimensional prediction secondary structure and contacts prediction Proteins 1999 Suppl 3 149 170 Grana O Eyrich VA Pazos F Rost B Valencia A EVAcon a protein contact prediction evaluation service Nucleic Acids Res 2005 33 Web Server issue W3472. RNAmap2D can calculate a contact map or a distance map of an RNA structure compare two alternative 3D models of RNA e g predicted structure versus experimen tally solved one Our program can analyze an ensemble of structures e g the content of a PDB file solved by the NMR method with two alternative statistics measures RNAmap2D is also capable of visualizing a contact map of protein RNA complex and a series of such models e g ori ginating from a protein RNA docking experiment RNA map2D can also calculate visualize and export RNA secondary structure in a common dot bracket format Secondary structure can be also imported and displayed as a 2D diagram in this case all contacts visualized by RNAmap2D will correspond to Watson Crick base pairs as other types of contacts are not represented in trad itional secondary structure representations RNAmap2D generates interactive 2D maps with a possi bility to zoom in onto particular fragments Zooming is enabled when a user presses a mouse button over a map and drags a rectangle shaped area The content of this area is shown in a separate window with a sequence ruler range indicator and a possibility of resizing Also when a user hovers a mouse cursor over a specific contact a window appears with information about the residue pair including residue index residue name and binary Y N Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333
3. contact information Additional interaction schemes spe cific to different tasks are available such as color panels fields to input certain value limits etc which are described below in specific sections Output options for 2D maps include a number of image formats BMP GIF JPG PNG TIFF and various text for mats developed initially for storing the results of compara tive analyses of protein sequences and structures CASP 21 EVA 22 PHYLIP 23 and CLANS 24 RNAmap2D can also encode maps in formats such as CSV or MS Excel spreadsheets which can be easily read and analyzed with many third party tools The program is also capable of read ing a map encoded as a text or Excel file e g a file exported from RNAmap2D and edited in a third party program In the section below we highlight some of the tasks of RNAmap2D that we find most typical in our own research on RNA structures All tasks and options are extensively E RNAmap2D v 1 6 2 n 7 Main menu Choose a job single model model ensemble J model vs model contact map from file complex contact map complex docking secondary structure file 1D12 pdb end tag ENDMDL Positioning type residue id based gapped structure based residue id based ungapped Figure 1 RNAmap2D user interface The main menu screen of RNAmap2D which serves as the entry panel for all analyses The user is asked to select the type of analysis a jo
4. 1U6B_B which was transformed by the deletion of 14 nt fragment to match the target sequence without major gaps The picture shows both 3D structures aligned crystal structure cyan and the model red a superpositon of the crystal structure PDB id 3P59 shown in cyan and a model generated by the Bujnicki group shown in red This model has been evaluated as the most accurate prediction for this molecule within the RNA Puzzles challenge 26 The comparison of contact maps with RNAmap2D shows that secondary structures have been modeled correctly and a significant fraction of ter tiary contacts observed in the crystal structure bottom left are also present in the theoretical model top right 20 30 40 50 60 70 80 90 mr EET r r nT a nN hs Ses Oe Le Sete eh See Ce 100 110 120 130 140 150 160 170 180 Page 8 of 11 Comparison of structural ensembles Another ability of RNAmap2D is to analyze results of calculations which typically generate not just one solu tion but entire ensembles Such studies include RNA and RNP structure determination by NMR review 28 and computational structure modeling approaches such as de novo folding e g with FARNA 29 or iFoldRNA 30 or our in house method SimRNA 31 or protein RNA docking e g using low resolution method to gene rate decoys followed by their scoring and ranking 32 For such ensembles comprising sets of complexes from a few to hundreds or even thousands of
5. C4 05 N1 N9 for purines and pyrimidines respectively or multiple atoms all or heavy non hydrogen a maximal distance in A between the specified atoms to form a contact and a minimal resi due separation along the sequence e g to exclude con tacts between consecutive residues that are connected by covalent bonds If multiple atoms are considered it is suf ficient for any pair of atoms from two residues to fall below the distance threshold to have this residues classi fied as in contact RNAmap2D does not generate a map of contacts between individual atoms only maps information about proximal atoms on the respective residues However individual heteroatom records found in PDB files that rep resent ions or ligand atoms are treated as separate resi dues If the PDB file contains several models the user can choose a specific model to be analyzed by the program For oligomeric structures in most analyses it is also pos sible to specify chain identifiers to limit the analysis to cer tain chains of the molecule Auxiliary options are graphic sequence delimiter ruler and grid like lines that separate chains chain borders Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 A pairs S S S H S w H H H W w w canon non canon Wobble Stacking gt gt green lt lt ligh t gre v ra aquama 7 gt lt Other ligands ions other background 110 Page 5 of 1
6. characters plus others if needed are used in the dot bracket string If an RNA secondary struc ture file is uploaded RNAmap2D can display the Watson Crick base pairs as a simplified contact map RNAmap2D can read the Vienna CT and BPSeq secondary structure formats Pseudoknotted base pairs are shown in grey Figure 5 and 6 Contact maps of complexes involving different types of molecules Nucleic acids usually function in complex with proteins and many structures of protein nucleic acid complexes Figure 6 RNA secondary structure Base pairs have been classified by RNAView A A contact map PDB id 1L2X see Figure 5 for a traditional rendering calculated using the threshold of 9 5 A using N1 N9 atoms canonical base pairs are shown in red other base pairs are in blue stacking interactions are shown in yellow and other contacts are in white B The RNA secondary structure Watson Crick base pairs only was saved in the Vienna format and reloaded in the contact map form The grey color indicates residues participating in pseudoknot pairings Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 Figure 7 Protein nucleic acid complex A double stranded RNA binding domain of S cerevisiae RNAse Ill in complex with an AAGU tetraloop hairpin PDB code 2LBS only the first model of the NMR ensemble is shown The protein chain is represented as symbolic secondary structure cartoons helices in red
7. The sequences do not need to be identical Thus it is possible to compare two models of the same RNA even if they don t cover the same range of residues as long as there is some overlap sub structures of different molecules e g homologs with similar structure but different sequence etc In either case two contact maps are shown concur rently with the first structure in the lower left triangle Page 7 of 11 the second in the upper right triangle Contacts common to both structures are shown as white dots while contacts specific to either structure are in grey In Figure 9 and 10 we compared the crystal structure of the Azoarcus group I intron PDB id 1U6B chain B with a 3D model for built on a template from the Twort phage using ModeRNA 25 The reference structure is 198nt long and contains several tertiary contacts that were constructed using a sec ond template from Tetrahymena Twelve residues at the 3 end are not present in the model The all atom RMSD of the model versus crystal structure is 4 3 A The contact map analysis allowed us to identify small differences in contacts between the model and the reference structure mainly in loops and in the tertiary motifs Figure 11 illustrates another example namely the com parison of one of our models constructed in the framework of the RNA puzzles challenge 26 For this modeling exer cise the secondary structure of the RNA square molecule 27 composed o
8. fast contact map calculation mode that bypasses the pairing calculation algorithm and can be used alternatively for large RNA structures in order to obtain a raw contact map very quickly Results and discussion Based on our previous experience with protein 2D map ana lysis and core parts of the PROTmap2D code 13 we devel oped RNAmap2D a standalone tool for calculation visualization and analysis of contact and distance maps of nucleic acid structures and structures of protein nucleic acid complexes PROTmap2D was designed to perform various tasks on proteins only As a consequence it has no generic or specific capabilities that could address tasks specific to nucleic acids or complexes formed by nucleic acids Also PROTmap2D cannot visualize contacts made by macromo lecules with ligands or ions On the other hand the inter action of RNA with ions is essential for the formation and stability of its 3D structure 20 therefore RNA ion contacts shouldn t be neglected in structural analyses RNAmap2D is therefore an independent program with multiple features specific for RNA and not simply an upgrade of PROT map2D Our method can serve to analyze DNA as well as RNA However we expect that because of regularity of DNA structures this type of nucleic acid will not be frequently analyzed on the 2D level hence the programs name includes only RNA as the key input molecule For simplicity in this article we refer mostly to RNA alone
9. RNAs can be seen Page 2 of 11 easily in contact maps even when the 3D structures super impose poorly The development of computational tools for molecular structure visualization must keep up with the growing amount of bioinformatics data and the definition of new data types Structure visualization analysis and annota tion tools play an increasingly important role in research contributing significantly to understanding the biological function of macromolecules There is a number of tools capable of calculating displaying and analyzing protein contact maps including VMD 9 SeqX 10 PConPy 11 or CMView 12 While some of these methods are able to display contacts of the protein component to the nucleic acid ligand they do not produce a 2D map if RNA structure alone is provided as input and they do not discriminate between different types of nucleotide interac tions As more and more RNA structures are determined by experimental methods or predicted by computational techniques it becomes increasingly important to reinforce current state of art 3D RNA modeling tools with 2D vi sualization capabilities Thus we developed a computer program dedicated to structural maps of RNAs and RNA protein or ligand complexes with particular emphasis on visualization of different types of interactions mediated by edges or faces of nucleotide bases i e pairing and stacking Implementation Programming language systems external prog
10. W351 Felsenstein J PHYLIP Phylogeny inference package version 3 2 Cladistics 1989 5 164 166 Frickey T Lupas A CLANS a java application for visualizing protein families based on pairwise similarity Bioinformatics 2004 20 18 3702 3704 Gruber AR Lorenz R Bernhart SH Neubock R Hofacker IL The vienna RNA websuite Nucleic Acids Res 2008 36 Web Server issue W70 W74 Cruz JA Blanchet MF Boniecki M Bujnicki JM Chen SJ Cao S Das R Ding F Dokholyan NV Flores SC et al RNA puzzles a CASP like evaluation of RNA three dimensional structure prediction RNA 2012 14 4 610 625 Dibrov SM McLean J Parsons J Hermann T Self assembling RNA square Proc Natl Acad Sci U S A 2011 108 16 6405 6408 Scott LG Hennig M RNA structure determination by NMR Methods Mol Biol 2008 452 29 61 Das R Baker D Automated de novo prediction of native like RNA tertiary structures Proc Natl Acad Sci U S A 2007 104 37 14664 14669 Sharma S Ding F Dokholyan NV iFoldRNA three dimensional RNA structure prediction and folding Bioinformatics 2008 24 17 1951 1952 Rother K Rother M Boniecki M Puton T Tomala K Lukasz P Bujnicki JM Template based and template free modeling of RNA 3D structure Inspirations from protein structure modeling In RNA 3D structure analysis and prediction Edited by Leontis NB Westhof E Berlin Springer Verlag 2012 Tuszynska Bujnicki JM DARS RNP and QUASI RNP New statistical potentials for pro
11. as sticks 5 and 3 terminal residues are labeled The structure is colored as a rainbow spectrum from 5 red to 3 blue termini Page 6 of 11 map of distances between individual atoms if multiple atoms are considered per residue the shortest distance is taken for each pair of residues One option for visua lization of distance maps is the contact map view This fea ture allows the user to optionally convert a distance map into a series of contact maps calculated at different thres holds New contact maps are calculated and visualized instantly as the user changes the maximal distance param eter defining a contact cutoff by using a mouse roller This enables a user to establish a subjectively optimal dis tance threshold parameter value for the purpose of obtain ing a contact map that highlights certain molecular features e g the minimal spatial proximity of two nucleo tide residues to form a relevant interaction Following the calculation of a distance map the user is given an option to define the absolute distance limits by entering minimal or maximal distance and the minimal sequential sepa ration of nucleotides to be considered The results are visualized instantly as well Figure 4 RNA secondary structure The calculated secondary structure can be written in the popular Vienna 25 format as a dot bracket string RNA map2D recognizes pseudoknots for which special bracket symbols and
12. models a statistical contact map can be calculated to visualize the frequencies of contacts in the ensemble as shades of grey Figure 12 RNAmap2D users can choose between two ways to dis play contacts that vary through the model ensemble file In both cases white fields on the map represent 100 fre quency across a model set and black fields represent no contacts For contacts that appear only in a fraction of models one option of visualization presents a relative fre quency of contacts where and shades of grey correspond to intermediate values the more frequent the contact the lighter the field Another option is to present all partial contacts by one shade of grey In an example analysis we have analyzed the noncano nical base pairs in a part of the 3 UTR from turnip crinkle virus genomic RNA This 102 nt structural element binds to the large ribosomal subunit to promote translation 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 Tr r rA T a M n eRT a RT ee 8 Figure 10 Comparison of a crystal structure and a comparative 3D model in 2D The homology model is compared to the crystal structure Contacts have been calculated using the N1 N9 metrics and 9 5 A threshold 1U6B_B 3D picture shown in Figure 9 A The lower left triangle displays the contacts in the crystal structure the upper right triangle those in the model B The right picture additionally highlights three regions where the contacts differ
13. strands in yellow RNA molecule is represented as bonding sticks and colored according to secondary structure base paired residues are shown in violet and pink Terminal residues are labeled have been determined experimentally In the PDB data base there are 3575 such entries as of April 11th 2012 contributing to 4 4 of the total PDB records RNA map2D is capable of either extracting nucleic acid chains from a complex structure in order to visualize them sepa rately or it can include the coordinates of the protein component and display protein nucleic acid interactions A contact map of a protein nucleic acid complex is visually divided into three distinct parts for intra protein contacts intra nucleic acid contacts and intermolecular contacts between the two entities These three categories can be colored differently for better visual distinction Whenever possible RNAmap2D utilizes protein secondary structure definitions found in a PDB file and displays them red for helices green for strands along the ruler of the contact map alongside the RNA secondary structure bars Figure 7 and 8 Comparison of contact maps RNAmap2D can compare two RNA structures in two modes molecules that have an identical number of resi dues or molecules that contain a common chain with resi dues with corresponding numbers The input can be either a single PDB file with two models or two separate files e g a 3D model and a reference structure
14. 1 120 130 140 150 Figure 3 Coloring capabilities of RNAmap2D A The coloring panel of RNAmap2D with a selection of several types of pairing stacking and other interactions Note that all types of pairings and stacking are identified by the program before the panel is displayed and options corresponding to interactions undetected in the input file are disabled B A contact map of 23S rRNA fragment PDB ID 1HC8_A 3D structure as shown in Figure 2 calculated for N1 N9 atoms using the threshold of 9 5 A and colored according to the code in panel A The top left square represents the RNA chain while the bottom right square shows Mg ions and other heteroatoms classified as either ions or ligands The symmetrically oriented upper right and bottom left sections indicate contacts between nucleotide residues and ions Purple and violet bars along the sequence ruler indicate RNA secondary structure A contact map can be visualized as a black and white picture with no distinction between contacts symbolized as white dots against black background no contact Fol lowing the calculation of the contact map the user can choose independent color schemes in order to highlight and visualize contacts that belong to one of the 12 base pair families three special groups canonical non canonical and Wobble or to one of the four stacking classes 8 The coloring is indicated by invoking an option panel which appears as a separate window RNAmap2D pr
15. 55 and A70 C87 a sugar Hoogsteen pair differ in only one of the models The fourth pair cis Watson Watson U67 C87 is present in four models only It varies a lot between the models and the participating bases can also pair in the cis Watson Hoogsteen mode Residues adjacent to A70 and C87 display some flexibility in the contact map Figure 12 Statistics of contacts in an NMR file A An AAGU tetraloop hairpin from the protein RNA complex PDB code 2LBS_A for the picture of an entire complex see Figure 7 here all NMR models are shown The RNA molecule is colored according to the secondary structure in violet and pink B A statistical contact map of the whole ensemble of RNA chains 16 models in total Shades of grey symbolize the percentage of particular contact occurrence in the whole model set In this case the C4 metrics and 12 A threshold were used to display the variability of contacts in the NMR file analyzed Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 as well This pair is located in an internal loop that is im portant for switching between translation and replication in the virus 33 We conclude that RNAmap2D helps to iden tify regions that undergo conformational changes by high lighting them in the graphical output and enables their quantitative examination in a tabular report Conclusions RNAmap2D is a new tool for calculation and visualization of nucleic acid co
16. Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 BMC Bioinformatics SOFTWARE Open Access RNAmap2D calculation visualization and analysis of contact and distance maps for RNA and protein RNA complex structures Michal J Pietal Natalia Szostak Kristian M Rother and Janusz M Bujnicki Abstract Background The structures of biological macromolecules provide a framework for studying their biological functions Three dimensional structures of proteins nucleic acids or their complexes are difficult to visualize in detail on flat surfaces and algorithms for their spatial superposition and comparison are computationally costly Molecular structures however can be represented as 2D maps of interactions between the individual residues which are easier to visualize and compare and which can be reconverted to 3D structures with reasonable precision There are many visualization tools for maps of protein structures but few for nucleic acids Results We developed RNAmap2D a platform independent software tool for calculation visualization and analysis of contact and distance maps for nucleic acid molecules and their complexes with proteins or ligands The program addresses the problem of paucity of bioinformatics tools dedicated to analyzing RNA 2D maps given the growing number of experimentally solved RNA structures in the Protein Data Bank PDB repository as well as the growing numbe
17. an be recovered from its contact map representation with the reconstructed and original struc tures similar up to the resolution of the contact map re presentation 7 This rationalizes the development of computational tools for analysis and visualization of macro molecular 2D maps as an alternative to dealing directly with 3D structures In fact complex structures of RNA molecules have been traditionally described as 2D dia grams exemplified by the popular cloverleaf representa tion of the tRNA molecule Such diagrams emphasize orthodox pairing of bases with their Watson Crick edges and with the use of additional symbols or colors they can also display other types of pairing using the Hoogsteen and sugar edges 8 However a single nucleotide residue can interact with more than one nucleotide at a time stacking using two faces base pairing using three edges and inter acting with the phosphate group In this situation second ary structure plots become illegible due to crossing of multiple lines indicating long distance contacts On the other hand the same type of information can be repre sented and visualized with a square symmetrical matrix containing data about different types of interactions e g discriminated by the use of different colors With only a lit tle training one can learn to quickly distinguish e g helices and complex tertiary arrangements such as pseudoknots Similarities between distantly related
18. b provide the input filename and indicate whether the program should use residue numbers from the input file or recalculate them Additionally for multi model files e g model ensemble analysis the user is asked to define the tag that separates individual models in the input file Page 4 of 11 Figure 2 A traditional 2D rendering of the 3D structure for the 23S rRNA fragment PDB ID 1HC8 chain C 5 and 3 terminal residues are numbered Nucleotide residues involved in Watson Crick base pairing are shown in pink and violet Mg ions are shown as green balls The limitation of this representation is that a single atom can have only one color and the use of multiple colors to illustrate different types of interactions can become overwhelming documented in the User s Manual which is provided on the program s website The program is also accompanied by a Tutorial which intends to demonstrate all standard features for a user without any prior knowledge A set of PDB structures and other files is also provided so that users do not have to search for appropriate input in order to test and see all the features described in the Tutorial Figure 1 RNA contact map RNAmap2D works on the level of residues rather than in dividual atoms A user can specify the definition of atoms used to calculate the presence of a contact the type of atoms to be included in calculations the options per resi due are single atoms Cl
19. cal functions visualizing and analyzing them is difficult both for humans and computer programs Two dimensional 2D flat images are more readily discernible to the eye and more memorable than complex 3D images As a matter of fact 3D structures of macromolecules including proteins nucleic acids and their complexes can be represented as square symmetrical matrices con taining data about the proximity of residue or atom pairs in the molecule 6 Values stored in the matrix may repre sent e g euclidean distances between particular atoms such matrix is then called a distance map If only binary information about residue residue interactions is included a matrix is called a contact map In a contact map a residue residue interaction may be qualified by an eucli dean distance below a given threshold or by a particular type of contact The representation of macromolecular structure by its 2D map is independent on the coordinate frame i e makes the representation invariant to rotations and translations which makes it useful for both vi sualization and structure comparison Contact maps can be also enriched with additional information e g to dis criminate different types of contacts or to indicate the chi rality in 3D handedness which is otherwise lost upon the conversion to a 2D representation It has been demonstrated that the 3D structure of a pro tein and by analogy any linear polymer that forms a com pact structure c
20. com mended as an optional plugin Please refer to User s Manual and README file for installation instructions to be found on the RNAmap2D project home page Hardware requirements min 512 MB RAM 1GHz CPU or better 2 GB RAM and 2 GHz CPU is recommended License RNAmap2D is distributed under free aca demic license Please refer to the home page for the li cense document Restriction for non academics Users willing to use RNAmap2D for non academic purposes should con tact the corresponding author for details Please note that this license will not affect commercial usage of Page 10 of 11 RNAView Please contact authors of RNAView for a separate license Abbreviations PDB Protein DataBank PIL Python Image Library CASP critical assessment of techniques for protein structure prediction CSV comma separated values CT connectivity table Competing interests Authors declare that they have no competing interests Authors contributions NS participated in majority of the code implementation including most of the features specific for RNA MP co supervised the work of NS contributed the code of PROTmap2D participated in the development of the code developed the final version of the software and drafted the manuscript KR co supervised the work of NS and participated in the development of the code JMB conceived of the study participated in design and coordination and edited the manuscript All authors read and approved
21. esents an option to color contacts made by ligands or 110 120 130 140 150 Ae te he ions which appear as additional residues following the sequence of macromolecules Figures 2 and 3 RNA distance map Distance maps are richer in data than contact maps and essentially preserve all the information required to infer the details of 3D structure with the exception of the han dedness which can be imposed on a higher level of rea soning because we know the stereochemistry of nucleic acid structures e g A RNA helix must be right handed As with contact maps RNAmap2D does not generate a 110 120 130 140 150 Figure 4 Contact vs distance maps A A contact map of 23S rRNA fragment the same structure as in Figure 2 calculated for N1 N9 atoms with a 9 5 A distance threshold All contacts are shown as white squares Purple and violet bars along the sequence ruler indicate RNA secondary structure B A distance map for the same molecule and metric The contact map shows only binary information while the distance map represents the degree of proximity by the shades of grey white color symbolizes a distance equal to zero Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 Figure 5 An example RNA structure with a pseudoknot A projection of a 3D structure of a viral RNA pseudoknot crystal structure PDB id 1L2X in the simplified cartoon format backbone as a ribbon nucleotide residues
22. ety of formats including e g the ones used in CASP or by the PHYLIP package Maps can be also exported and uploaded as Microsoft Office Excel spreadsheets Finally images of maps can be exported as PNG BMP and TIFF files Speed To optimize the speed of RNAmap2D we used C and C libraries that are accessible under Python wxPython for the graphical user interface Numeric and NumPy for most numeric calculations Also the core calculation routine in RNAmap2D is the determination of distances and contacts between atoms and residues We used the KDTree algorithm 19 as implemented in Biopython which has log linear calculation time fastest known to date As an example for a molecule of the size of 100 nu cleotide residues the calculation time reaches 1000 time units typically below a second for obtaining a raw list of contacts from a 3D structure It compares favorably e g with an alternative approach used by the PConPy program for protein contact maps 11 that relies on a naive double loop for calculating a contact map For the molecule of identical size the calculation time would reach 4950 units which is five times slower This is because time complexity of most such algorithms is of the order of O n Please note however that the calculation time for RNA molecules longer than 200 bases can be quite long if no RNAView Page 3 of 11 plugin is installed Bearing this in mind we designed an additional no pairings
23. f eight individual strands as well as three dimensional coordinates of the four strands were provided and the task was to model the structure and contacts made by the four missing strands Figure 11 panel A presents 373 383 393 403 413 423 433 443 453 10 20 P np Figure 8 Contact map of a protein nucleic acid complex A double stranded RNA binding domain of S cerevisiae RNAse Ill in complex with an AAGU tetraloop hairpin PDB code 2LBS only the first model is shown the same as in a traditional rendering in Figure 7 In a contact map picture protein contacts are displayed in yellow RNA contacts are blue and the protein RNA interface contacts are displayed in orange Metrics preset all atoms for RNA and protein molecules 3 5 A contact threshold However the atom type and the distance threshold can be set independently for RNA RNA protein protein and protein RNA contacts In the protein part of the map red and green bars indicate secondary structures alpha helices and beta strands respectively read directly from the PDB file In the RNA part of the map purple and violet bars indicate RNA secondary structure computed using the RNAView program Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 Figure 9 Comparison of a group intron crystal structure and a comparative 3D model built with the ModeRNA program in 3D The homology model is compared to the crystal structure
24. in particular one tertiary interaction site left one loop center and one junction right Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 Page 9 of 11 Figure 11 Self assembling RNA nano square versus homology model A The 3D model red is compared to the crystal structure PDB id 3P59 27 cyan B In the contact map picture the lower left triangle displays the contacts in the crystal structure the upper right triangle those in the model N1 N9 metrics and 9 5 A threshold was used The structure consists of three main helices In the NMR structure PDB ID 2krl 10 models have been deposited RNAmap2D can be used to check e g whether noncano nical base pairs are maintained in all the models We used RNAmap2D to generate a contact map for the ensemble and then colored noncanical pairs in blue We have inspected individual pairs in the map zoomed to a full screen mode and generated a statistics map and exported the contact frequencies to an Excel table In the contact map regions that vary in the ensemble e g due to in creased flexibility are immediately visible as grey areas For instance tertiary interactions between hairpin loop 37 43 and the structure 97 101 fluctuate and base pairing in this region is not stable In total we identified 15 noncanonical base pairs of which four differ in at least one of the 10 models The three noncanonical pairs G9 G12 G29 U
25. m 2009 10 9 10 1415 1419 4 Fulle S Gohlke H Constraint counting on RNA structures linking flexibility and function Methods 2009 49 2 181 188 5 Anfinsen CB Scheraga HA Experimental and theoretical aspects of protein folding Adv Protein Chem 1975 29 205 300 6 Phillips DC The development of crystallographic enzymology Biochem Soc Symp 1970 30 11 28 7 Vendruscolo M Kussell E Domany E Recovery of protein structure from contact maps FoldDes 1997 2 5 295 306 8 Leontis NB Westhof E Geometric nomenclature and classification of RNA base pairs RNA 2001 7 4 499 512 9 Humphrey W Dalke A Schulten K VMD visual molecular dynamics J Mol Graph 1996 14 1 33 38 27 38 10 Biro JC Fordos G SeqX a tool to detect analyze and visualize residue co locations in protein and nucleic acid structures BMC Bioinforma 2005 6 170 11 Ho HK Kuiper MJ Kotagiri R PConPy a python module for generating 2D protein maps Bioinformatics 2008 24 24 2934 2935 12 Vehlow C Stehr H Winkelmann M Duarte JM Petzold L Dinse J Lappe M CMView interactive contact map visualization and analysis Bioinformatics 2011 27 11 1573 1574 13 Pietal MJ Tuszynska Bujnicki JM PROTMAP2D visualization comparison and analysis of 2D maps of protein structure Bioinformatics 2007 23 11 1429 1430 Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 22 23 24 25 26 27
26. ntact and distance maps Our aim was to facilitate analyses of RNA structures that focus on type and location of short range interactions without taking the spatial conformation of the backbone into account RNA map2D is also capable of analyzing protein nucleic acid complexes RNAmap2D is applicable in various scenarios ranging from comparison of RNA 2D and 3D structural pre dictions with each other and with the native structure to analyses of trajectories from MD simulations of nucleic acid structures to studies of RNA DNA protein and RNA DNA ligand interactions and analyses of macromolecular docking experiments PROTmap2D and RNAmap2D both provide researchers with an extensive suite of programs for analyses and visualization of macromolecular structures RNAmap2D runs on any modern operating system is very fast and has an intuitive interface Both programs serve as a complete platform that supplements the existing 3D visualization tools with sophisticated 2D map capabilities Availability and requirements Project name RNAmap2D Project home page http iimcb genesilico pl rnamap2d html Operating systems Windows Linux MacOSX Programming languages Python main C C some parts of external libraries Software packages Windows MacOSX None Software packages Linux Python 2 6 Biopython 1 42 PyCogent 1 4 wxPython 2 8 10 PIL 1 1 6 Numeric 24 2 NumPy 1 1 3 PyExcelerator 0 6 3 Other requirements RNAView program is re
27. r of tools for RNA 2D and 3D structure prediction RNAmap2D allows for calculation and analysis of contacts and distances between various classes of atoms in nucleic acid protein and small ligand molecules It also discriminates between different types of base pairing and stacking Conclusions RNAmap2D is an easy to use method to visualize analyze and compare structures of nucleic acid molecules and their complexes with other molecules such as proteins or ligands and metal ions Its special features make it a very useful tool for analysis of tertiary structures of RNAs RNAmap2D for Windows Linux MacOSx is freely available for academic users at http iimcb genesilico pl rnamap2d htm Keywords Contact maps Distance maps RNA secondary structure RNA base pairing RNA stacking Protein RNA complex Docking Background RNAs and proteins are linear polymers composed of a limited set of building blocks ribonucleotide and amino acid residues respectively that may spontaneously fold into complex three dimensional shapes 1 2 In both RNA and proteins the order of building blocks held to gether by covalent bonds is called the primary structure the local conformation of the chain stabilized mostly by Correspondence iamb genesilico pl Equal contributors Laboratory of Bioinformatics and Protein Engineering International Institute of Molecular and Cell Biology in Warsaw ul Ks Trojdena 4 PL 02 109 Warsaw Poland Laborator
28. rams RNAmap2D was developed based on its predecessor PROTmap2D 13 The core programming language of RNAmap2D is Python The program uses the Biopython 14 and PyCogent 15 libraries to handle PDB structures RNAmap2D is available for Linux Windows and MacOSX To create a Windows executable version of the program we used the py2exe 0 6 9 tool and to build a MacOSX version py2app 0 3 6 respectively Hardware requirements for RNAmap2D are very modest as of 2012 i e 1 GHz processor and 512 MB RAM memory In analogy to a number of programs for determination of protein secondary structure from 3D coordinates 16 that differ from each other in definition of structures and algorithms for their detection there exist various tools for determination of contacts from RNA 3D structures We have adapted RNAmap2D to use RNAView 17 for base pair calculation However RNAView is not available for Windows therefore we added our own procedure for cal culating base nucleotide pairs developed in ModeRNA 18 For every pair of residues considered it superim poses reference frames of all known pairs types as well as predicts the presence of H bonds characteristic for a given pair type based on interatomic distances and angles This makes the latter procedure sensitive to distortions of the relative conformation of the nucleotide According to our tests this procedure agrees with RNAView in assignment Pietal et al BMC Bioinformatics 2012 13 333 h
29. tein RNA docking BMC Bioinforma 2011 12 1 348 Zuo X Wang J Yu P Eyler D Xu H Starich MR Tiede DM Simon AE Kasprzak W Schwieters CD et al Solution structure of the cap independent translational enhancer and ribosome binding element in the 3 UTR of turnip crinkle virus Proc Natl Acad Sci U S A 2010 107 4 1385 1390 doi 10 1186 1471 2105 13 333 Cite this article as Pietal et al RNAmap2D calculation visualization and analysis of contact and distance maps for RNA and protein RNA complex structures BMC Bioinformatics 2012 13 333 Page 11 of 11 Submit your next manuscript to BioMed Central and take full advantage of e Convenient online submission e Thorough peer review e No space constraints or color figure charges e Immediate publication on acceptance e Inclusion in PubMed CAS Scopus and Google Scholar e Research which is freely available for redistribution Submit your manuscript at www biomedcentral com submit C BioMed Central
30. the final manuscript Acknowledgements The authors thank Irina Tuszynska for discussions suggestions and testing RNAmap2D in the context of RNA protein docking and also for critically proofreading the manuscript The authors also thank Anna Philips for help in analyzing structures containing ligands and ions and with nucleotide modifications lists encoded within the RNAmap2D This work was supported mainly by the European Commission initially by the FP6 grant EURASNET LSHG CT 2005 518238 and subsequently by the FP7 grant HEALTH PROT contract number 229676 Integration of various software tools involving protein bioinformatics in the Bujnicki laboratory in IIMCB has been supported by the EU structural funds POIG 02 03 00 00 003 09 M J P was supported by European Social Fund through a Subcarpatian Doctoral Stipend Fund project K R was independently supported by the German Academic Exchange Service grant D 09 42768 J M B was supported by the Foundation for Polish Science FNP grant TEAM 2009 4 2 Received 6 June 2012 Accepted 15 December 2012 Published 21 December 2012 References 1 Dill KA Dominant forces in protein folding Biochemistry 1990 29 31 7133 7155 2 Ferre D Amare AR Doudna JA RNA folds insights from recent crystal structures Annu Rev Biophys Biomol Struct 1999 28 57 73 3 Hazy E Tompa P Limitations of induced folding in molecular recognition by intrinsically disordered proteins Chemphysche
31. ttp www biomedcentral com 1471 2105 13 333 of 95 of canonical base pairs At startup RNAmap2D checks for the presence of the installed RNAView pro gram and uses it by default for base pair interactions clas sification while in its absence our modules are used User skills RNAmap2D requires no programming or scripting skills to make use of all of its features regardless of the platform The Windows and MacOSX versions require no installa tion except for downloading and unpacking the distribu tion file Linux distribution is a set of bytecode Python files that require the installation of all modules cited at the beginning of this section prior to the use of the program Users are provided with a comprehensive manual and a readme file that explains all installation steps All versions provide the same functionalities except for the above mentioned absence of RNAView for the Windows platform Our program has an easy to use graphic user interface that allows for customizing the final contact or distance map and by setting all the important parameters RNA map2D navigation scheme design allows for making a step back from the final map view to the main options panel in order to refine parameters and promptly visualize the desired output The intermediate results of calculations are stored in the computer memory to keep the data pro cessing time at a minimum Distance and contact maps can be saved and uploaded as text files in a vari
32. y of Bioinformatics and Protein Engineering International Institute of Molecular and Cell Biology in Warsaw ul Ks Trojdena 4 Warsaw PL 61 614 Poland C BioMed Central hydrogen bonds is the secondary structure while the path of the chain in three dimensions 3D resulting from va rious long range interactions is the tertiary structure It is known that many proteins and RNAs undergo confor mational transitions Macromolecules and their parts may also exhibit structural disorder i e fluctuations between many different conformations 3 4 The functions of pro teins and RNAs typically involve physical interactions with other molecules in the cell which are dependent on the structure and plasticity of the interacting partners Thus the functions of proteins and RNAs alike depend on the 3D structure and dynamics of these molecules which in turn are encoded in their linear i e unidimensional 1D sequences 5 2012 Pietal et al licensee BioMed Central Ltd This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons org licenses by 2 0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited Pietal et al BMC Bioinformatics 2012 13 333 http www biomedcentral com 1471 2105 13 333 While three dimensional macromolecular structures represent an information rich framework for studying biologi
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