Name: rna secondary structure prediction using high-throughput shape
Uploaded: 2013-05-31T12:00:00.000+00:00
Duration: 13 min 42 s
Description: Watch this Scientific Journal Video about RNA Secondary Structure Prediction Using High-throughput SHAPE at JoVE.com

S. Lusvarghi, J. Sztuba-Solinska, KJ Purzycka, JW Rausch und SFJ Le Grice werden durch die Interne Research Program des National Cancer Institute, National Institutes of Health, USA unterstützt.

<ol>
	<li>Scott, W. G., Martick, M., Chi, Y. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure+and+function+of+regulatory+RNA+elements:+ribozymes+that+regulate+gene+expression.">Structure and function of regulatory RNA elements: ribozymes that regulate gene expression.</a> Biochim. Biophys. Acta. 1789, 634-641 (2009).</li><li>Moore, P. B., Steitz, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+roles+of+RNA+in+the+synthesis+of+protein.">The roles of RNA in the synthesis of protein.</a> Cold Spring Harb. Perspect. Biol. 3, a003780 (2011).</li><li>Wilkinson, K. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+SHAPE+analysis+reveals+structures+in+HIV-1+genomic+RNA+strongly+conserved+across+distinct+biological+states.">High-throughput SHAPE analysis reveals structures in HIV-1 genomic RNA strongly conserved across distinct biological states.</a> Plos Biol. 6, 883-899 (2008).</li><li>Merino, E. J., Wilkinson, K. A., Coughlan, J. L., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA+structure+analysis+at+single+nucleotide+resolution+by+selective+2+'-hydroxyl+acylation+and+primer+extension+(SHAPE).">RNA structure analysis at single nucleotide resolution by selective 2 '-hydroxyl acylation and primer extension (SHAPE).</a> J. Am. Chem. Soc. 127, 4223-4231 (2005).</li><li>Watts, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Architecture+and+secondary+structure+of+an+entire+HIV-1+RNA+genome.">Architecture and secondary structure of an entire HIV-1 RNA genome.</a> Nature. 460, 711-716 (2009).</li><li>Xu, W., Bolduc, F., Hong, N., Perreault, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+a+combination+of+computer-assisted+structure+prediction+and+SHAPE+probing+to+elucidate+the+secondary+structures+of+five+viroids.">The use of a combination of computer-assisted structure prediction and SHAPE probing to elucidate the secondary structures of five viroids.</a> Mol. Plant Pathol. , (2012).</li><li>Novikova, I. V., Hennelly, S. P., Sanbonmatsu, K. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+architecture+of+the+human+long+non-coding+RNA,+steroid+receptor+RNA+activator.">Structural architecture of the human long non-coding RNA, steroid receptor RNA activator.</a> Nucleic Acids Res. 40, 5034-5051 (2012).</li><li>Leshin, J. A., Heselpoth, R., Belew, A. T., Dinman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+structural+analysis+of+yeast+ribosomes+using+hSHAPE.">High-throughput structural analysis of yeast ribosomes using hSHAPE.</a> RNA Biol. 8, 478-487 (2011).</li><li>Souliere, M. F., Haller, A., Rieder, R., Micura, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+powerful+approach+for+the+selection+of+2-aminopurine+substitution+sites+to+investigate+RNA+folding.">A powerful approach for the selection of 2-aminopurine substitution sites to investigate RNA folding.</a> J. Am. Chem. Soc. 133, 16161-16167 (2011).</li><li>Wilkinson, K. A., Merino, E. J., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+2+'-hydroxyl+acylation+analyzed+by+primer+extension+(SHAPE):+quantitative+RNA+structure+analysis+at+single+nucleotide+resolution.">Selective 2 '-hydroxyl acylation analyzed by primer extension (SHAPE): quantitative RNA structure analysis at single nucleotide resolution.</a> Nat. Protoc. 1, 1610-1616 (2006).</li><li>McGinnis, J. L., Duncan, C. D. S., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-Throughput+Shape+and+Hydroxyl+Radical+Analysis+of+Rna+Structure+and+Ribonucleoprotein+Assembly.">High-Throughput Shape and Hydroxyl Radical Analysis of Rna Structure and Ribonucleoprotein Assembly.</a> Method Enzymol. 468, 67-89 (2009).</li><li>Low, J. T., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SHAPE-directed+RNA+secondary+structure+prediction.">SHAPE-directed RNA secondary structure prediction.</a> Methods. 52, 150-158 (2010).</li><li>Das, R., Laederach, A., Pearlman, S. M., Herschlag, D., Altman, R. B. S. A. F. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Semi-automated+footprinting+analysis+software+for+high-throughput+quantification+of+nucleic+acid+footprinting+experiments.">Semi-automated footprinting analysis software for high-throughput quantification of nucleic acid footprinting experiments.</a> Rna-a Publication of the Rna Society. 11, 344-354 (2005).</li><li>Kertesz, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+measurement+of+RNA+secondary+structure+in+yeast.">Genome-wide measurement of RNA secondary structure in yeast.</a> Nature. 467, 103-107 (2010).</li><li>Underwood, J. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FragSeq:+transcriptome-wide+RNA+structure+probing+using+high-throughput+sequencing.">FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing.</a> Nat. Methods. 7, 995-1001 (2010).</li><li>Mauger, D. M., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Toward+global+RNA+structure+analysis.">Toward global RNA structure analysis.</a> Nat. Biotechnol. 28, 1178-1179 (2010).</li><li>Lucks, J. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+RNA+structure+characterization+with+selective+2'-hydroxyl+acylation+analyzed+by+primer+extension+sequencing+(SHAPE-Seq).">Multiplexed RNA structure characterization with selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq).</a> Proc. Natl. Acad. Sci. USA. 108, 11063-11068 (2011).</li><li>Vasa, S. M., Guex, N., Wilkinson, K. A., Weeks, K. M., Giddings, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ShapeFinder:+a+software+system+for+high-throughput+quantitative+analysis+of+nucleic+acid+reactivity+information+resolved+by+capillary+electrophoresis.">ShapeFinder: a software system for high-throughput quantitative analysis of nucleic acid reactivity information resolved by capillary electrophoresis.</a> RNA. 14, 1979-1990 (2008).</li><li>Reuter, J. S., Mathews, D. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNAstructure:+software+for+RNA+secondary+structure+prediction+and+analysis.">RNAstructure: software for RNA secondary structure prediction and analysis.</a> BMC Bioinformatics. 11, 129 (2010).</li><li>Pang, P. S., Elazar, M., Pham, E. A., Glenn, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simplified+RNA+secondary+structure+mapping+by+automation+of+SHAPE+data+analysis.">Simplified RNA secondary structure mapping by automation of SHAPE data analysis.</a> Nucleic Acids Res. 39, e151 (2011).</li><li>Deigan, K. E., Li, T. W., Mathews, D. H., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+SHAPE-directed+RNA+structure+determination.">Accurate SHAPE-directed RNA structure determination.</a> Proc. Natl. Acad. Sci. USA. 106, 97-102 (2009).</li><li>Darty, K., Denise, A., Ponty, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=VARNA:+Interactive+drawing+and+editing+of+the+RNA+secondary+structure.">VARNA: Interactive drawing and editing of the RNA secondary structure.</a> Bioinformatics. 25, 1974-1975 (2009).</li><li>Byun, Y., Han, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PseudoViewer:+web+application+and+web+service+for+visualizing+RNA+pseudoknots+and+secondary+structures.">PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures.</a> Nucleic Acids Res. 34, 416-422 (2006).</li><li>Brown, T., Brown, D. J. S., Eckstein, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Oligonucleotides and Analogues - A Practical Approach. , 20 (1990).</li><li>Legiewicz, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+RNA+Transport+Element+of+the+Murine+musD+Retrotransposon+Requires+Long-range+Intramolecular+Interactions+for+Function.">The RNA Transport Element of the Murine musD Retrotransposon Requires Long-range Intramolecular Interactions for Function.</a> J. Biol. Chem. 285, 42097-42104 (2010).</li><li>Steen, K., Siegfried, N. A., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Syntheis+of+1-methyl-8-nitroisatoic+anhydride+(1M7).">Syntheis of 1-methyl-8-nitroisatoic anhydride (1M7).</a> Protocol Exchange. , (2011).</li><li>Mortimer, S. A., Weeks, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+fast-acting+reagent+for+accurate+analysis+of+RNA+secondary+and+tertiary+structure+by+SHAPE+chemistry.">A fast-acting reagent for accurate analysis of RNA secondary and tertiary structure by SHAPE chemistry.</a> J. Am. Chem. Soc. 129, 4144-4145 (2007).</li><li>Mitra, S., Shcherbakova, I. V., Altman, R. B., Brenowitz, M., Laederach, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+single-nucleotide+structural+mapping+by+capillary+automated+footprinting+analysis.">High-throughput single-nucleotide structural mapping by capillary automated footprinting analysis.</a> Nucleic Acids Res. 36, e63 (2008).</li><li>Giddings, M. C., Severin, J., Westphall, M., Wu, J., Smith, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+software+system+for+data+analysis+in+automated+DNA+sequencing.">A software system for data analysis in automated DNA sequencing.</a> Genome Res. 8, 644-665 (1998).</li><li>Aviran, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+and+automation+of+sequencing-based+characterization+of+RNA+structure.">Modeling and automation of sequencing-based characterization of RNA structure.</a> Proc. Natl. Acad. Sci. USA. 108, 11069-11074 (2011).</li></ol>

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Wir stellen Ihnen hier eine detaillierte Protokoll für High-Throughput-SHAPE, eine Technik, die sekundäre Struktur Bestimmung erlaubt single-nucleotide Auflösung für RNAs jeder Größe. Außerdem Kopplung experimentellen Daten mit SHAPE Sekundärstruktur Vorhersage-Algorithmen ermöglicht Generation von RNA 2D-Modelle mit einem höheren Grad an Genauigkeit, als es mit beiden Methoden allein. Die Kombination von fluoreszenzmarkierten Primern und automatisierte CE bietet erhebliche Vorteile gegenüber dem herkömmlich...

Um die Funktionen der katalytischen und nicht-kodierende RNAs bei der Regulation der Spleißen, Übersetzung, Virusreplikation und Krebs beteiligt zu verstehen, ist eine genaue Kenntnis der RNA-Struktur 1,2 erforderlich. Leider stellt genaue Vorhersage der RNA-Faltung eine gewaltige Herausforderung. Klassische Sondieren Mittel leiden viele Nachteile, wie Toxizität, unvollständige Nucleotidsequenz Abdeckung und / oder den Durchsatz beschränkt auf 100-150 Nukleotide pro Versuch. Unaided Sekundärstruktur Vorhersage-Algorithmen sind ähnlich nachteilig wegen Ungenauigkeiten aufgrund ihrer Unfähigkeit, effektiv unter energetisch ähnlichen Strukturen zu unterscheiden. Große RNAs insbesondere auch oft feuerfesten Verfahren zur 3D-Struktur Bestimmung wie Röntgenkristallographie und NMR-Spektroskopie (NMR), die aufgrund ihrer konformativen Flexibilität und große Mengen an hochreinem Proben für diese Techniken erforderlich. HIGH-Durchsatz SHAPE löst viele dieser Probleme durch eine effektive, einfache Methode, um die Erforschung der Strukturen von großen RNAs bei single-nucleotide Auflösung. Darüber hinaus sind die Reagenzien für SHAPE verwendet sichere, einfach zu handhaben und im Gegensatz zu den meisten anderen chemischen Reagenzien Sondieren, mit allen vier Ribonukleotiden reagieren. Diese Reagenzien können auch zelluläre Membranen eindringen, was es ermöglicht, RNAs in ihre in vivo-Kontext (e) 3 sondieren. Ursprünglich in den Wochen 4 Labor entwickelt wurde, hat SHAPE verwendet worden, um eine Vielzahl von RNAs, die bemerkenswerteste Beispiel ist die Bestimmung der vollständigen sekundären Struktur des ~ 9 kb HIV-1-RNA-Genom 5 zu analysieren. Andere bemerkenswerte Erfolge mit SHAPE umfassen Aufklärung der Strukturen von infektiösen Viroiden 6, menschlichen langen nicht-kodierenden RNAs 7, Hefe Ribosomen 8 und 9 riboswitches sowie zur Identifizierung von Protein-Bindungsstellen in Virion-assoziierten HIV-1-RNA-3. While das Original und High-Throughput-Variationen des SHAPE-Protokoll wurde bereits an anderer Stelle veröffentlicht 10-12, stellt die vorliegende Arbeit eine detaillierte Beschreibung der RNA Sekundärstruktur Bestimmung durch High-Throughput-SHAPE mit fluoreszierenden Oligonukleotiden, die Beckman Coulter CEQ 8000 Genetic Analyzer, und ShapeFinder und RNAStructure (v5.3)-Software. Bisher unveröffentlichte technischen Details und Hinweise zur Fehlersuche sind ebenfalls enthalten. Variationen von SHAPE Das Wesen Form und seinen Varianten ist die Exposition von RNA in wässriger Lösung einer elektrophilen Anhydride, die selektiv acyliert 2&#39;-Hydroxy-(2&#39;-OH)-Gruppen Ribose, wodurch sperrige Addukte an den Stellen der Modifikation. Diese chemische Reaktion dient als Mittel zum Abfragen lokalen RNA strukturelle Dynamik, als einzelsträngige Nukleotide anfälliger für Konformationen förderlich elektrophilen Angriff durch diese Reagenzien erlassen sind, während basengepaarte oder architektonisch bebauteained Nukleotide sind weniger reaktiv oder 10. Seiten der Adduktbildung werden durch reverse Transkription initiiert von fluoreszent oder radioaktiv markierten Primer hybridisiert an eine spezifische Stelle auf der modifizierten RNA (die &quot;(+)&quot; Primer-Extension-Reaktion) detektiert. Als reverse Transkriptase (RT), um die acylierten Ribonukleotide durchqueren fehlschlägt, wird ein Pool von cDNA-Produkte hergestellt werden, deren Längen übereinstimmen mit Seiten der Modifikation. Ein Steuersystem, &quot;(-)&quot; Primerverlängerungsreaktion Verwendung RNA, die nicht Reagenz ausgesetzt wurde auch durchgeführt, so dass eine vorzeitige Beendigung der DNA-Synthese (dh &quot;Haltestellen&quot;) aufgrund von Struktur, unspezifische RNA-Strang Bruch etc, kann RNA. Pausieren von durch chemische Modifikation hergestellt wurden, unterschieden werden. Schließlich werden zwei Dideoxy-Sequenzierungsreaktionen Einleiten von denselben Primern als Marker verwendet werden, um reaktive Nukleotide mit dem RNA-Primärsequenz nach Elektrophorese korrelieren. In der ursprünglichen Anwendung SHAP(-), Und zwei Sequenzierungsreaktionen E, gleich 32 P-end-markiertem Primer für die (+), verwendet. Produkte dieser Reaktionen in benachbarten Vertiefungen in einer 5-8% igen Polyacrylamid-Slab-Gel geladen und fraktioniert durch denaturierende Polyacrylamid-Gelelektrophorese (PAGE; Abbildung 1). Die quantitative Analyse der Gel-Bilder durch herkömmliche Form hergestellt werden unter Verwendung SAFA, ein halbautomatisches Footprint-Analyse-Software 13 ist. Im Gegensatz dazu verwendet Hochdurchsatz-FORM fluoreszenzmarkierten Primer und automatisierten Kapillarelektrophorese. Genauer gesagt, für jede Region von RNA untersucht, ein Satz von vier DNA Primer eine gemeinsame Sequenz, aber unterschiedliche 5&#39;Fluoreszenzmarkierungen müssen synthetisiert oder gekauft werden. Diese unterschiedlich markierten Oligonukleotide dienen prime zwei SHAPE Reaktionen und zwei Sequenzierungsreaktionen, deren Produkte gebündelt und fraktionierte / erkannt durch automatisierte Kapillarelektrophorese (CE). Whereas die Reaktivität Profil von 100-150 nt von RNA aus einem Satz von vier Reaktionen mit dem ursprünglichen Ansatz erreicht werden kann, ermöglicht Hochdurchsatz-SHAPE Auflösung von 300-600 nt aus einer gepoolten Probe 3. Bis zu 8 Sätze von Reaktionen fraktioniert werden gleichzeitig, jedoch nicht weniger als 96 Proben für die Fraktionierung innerhalb von 12 aufeinander folgenden Läufen CE (2) hergestellt. Darüber hinaus ist die ShapeFinder entwickelte Software zur Verarbeitung und Analyse von Daten, die aus dem CEQ und andere genetische Analysatoren, stärker automatisiert und erfordern viel weniger Benutzereingriff als SAFA 13 oder Gel-Analyse-Pakete. Weiter fortgeschrittene Hochdurchsatz-Methodik wurden kürzlich wie PARS (parallele Analyse von RNA-Struktur) 14 und Frag-Seq (Fragment-Sequenzierung) 15, die Struktur-spezifische Enzyme anstatt Alkylierungsmittel Verwendung in Verbindung mit der nächsten Generation Sequenzierung Techniken zu erhalten entstanden information über RNA-Struktur. Trotz der Attraktivität dieser Techniken, die viele Einschränkungen inhärent Nuklease Sondieren noch 16 bleiben. Diese Probleme können in Form Sequenzierung (Shape-Seq) 17-Protokoll, wobei Sequenzierung der nächsten Generation durch chemische Modifizierung und reverse Transkription der RNA in einer ähnlichen Weise wie in herkömmliche Form durchgeführt vorausgeht umgangen werden. Obwohl diese Methoden die Zukunft der RNA-Struktur Bestimmung darstellen kann, ist es wichtig, sich daran zu erinnern, dass der nächsten Generation Sequenzierung sehr teuer ist und bleibt für viele Labore. SHAPE Data Analysis Die Daten in der Genetic Analyzer erzeugt wird in Form einer Elektropherogramm dargestellt, wobei die Fluoreszenzintensität der Probe (n), der durch die Kapillare Detektor wird gegen einen anderen Zeitpunkt aufgetragen. Dieses Grundstück hat die Form von überlappenden Spuren entsprechend den vier Fluoreszenzkanals verwendet, um die verschiedenen Fluorophoren zu erfassen, und wobei jede Spur aus einzelnen Peaks, die cDNA oder Sequenzierungsprodukte besteht. Elektropherogramm Daten aus dem Genetic Analyzer als Tab-getrennte Textdatei exportiert und importiert in ShapeFinder Transformation und Analyse-Software 18. ShapeFinder zunächst verwendet, um eine Reihe mathematischer Transformationen an den Daten durchführen, um sicherzustellen, dass die Migration Zeiten und Peakvolumina genau die Identität und Menge der Reaktionsprodukte sind. Peaks werden dann ausgerichtet und integriert, und die Ergebnisse zusammen mit dem primären RNA-Sequenz aufgelistet. A &quot;Reaktivitätsprofil&quot; für den betreffenden Abschnitt des RNA wird durch Subtrahieren Steuerwerte aus dem (+) RNA, die mit jedem Nukleotid verbunden ist, und das Normalisieren der Daten, wie unten beschrieben erhalten. Dieses Profil wird in RNAstructure importiert (v5.3)-Software 19,20, die den normierten Reaktivität val wandeltUES in Pseudo-Energie Einschränkungen, die in der RNA-Sekundärstruktur Faltungsalgorithmus eingebaut sind. Das Kombinieren der chemischen Sondieren und Falten Algorithmen auf diese Weise erheblich verbessert die Genauigkeit der Vorhersage Struktur im Vergleich zu beiden Verfahren allein 12,21. Der Ausgang des RNAstructure (v5.3) enthält Bilder von der niedrigsten Energie RNA Sekundärstrukturen mit der Form Reaktivitätsprofil (en), sowie den gleichen Strukturen in textueller dot-Klammern zu farbcodiert. Letzteres kann anschließend auf Software spezialisiert auf die grafische Darstellung der RNA Sekundärstruktur wie Varna 22 und 23 PseudoViewer exportiert werden. <img alt="Abbildung 1" fo:content-width="4.8in" fo:src="/files/ftp_upload/50243/50243fig1highres.jpg" src="/files/ftp_upload/50243/50243fig1.jpg" /> Abbildung 1. Flussdiagramm der RNA-Struktur Bestimmung über SHAPE 4,10. (A) RNA may aus biologischen Proben oder durch in vitro-Transkription erhalten werden. (B) Je nach Quelle wird RNA gefaltet oder anderweitig verarbeitet und modifiziert mit SHAPE Reagenz. (C) reverse Transkription fluoreszierend oder radioaktiv markierte Primer verwenden. (D) cDNA-Produkte sind fraktionierten entweder über Kapillare oder Slab-Gel-basierten Elektrophorese. (E) Fragment-Analyse. (F) RNA-Struktur-Vorhersage. <a href="http://www.jove.com/files/ftp_upload/50243/50243fig1large.jpg" target="_blank">Klicken Sie hier für eine größere Abbildung zu sehen.</a> <img alt="Abbildung 2" fo:content-width="6in" fo:src="/files/ftp_upload/50243/50243fig2highres.jpg" src="/files/ftp_upload/50243/50243fig2.jpg" /> Abbildung 2. Die Hochdurchsatz-Charakter der CE-Form ermöglicht eine schnelle Analyse mehrerer RNAs, und / oder mehrere Segmente der gleichen RNA. (A) </stRong&gt; Gibt an, wie ein RNA in 300-600 nt Abschnitte (Farbe in grün, blau und rot kodiert) (B) Sektionen der RNA unabhängig sondiert mit verschiedenen Sätzen von fluoreszierenden Primer (schwarze Pfeile) (C) Sets unterteilt werden kann Reaktionen werden vereinigt und in die Vertiefungen A1, B1, C1, etc., die jeweils geladen, wodurch eine vollständige Abdeckung des ~ 3 kb RNA1. Reaktionsprodukte von RNAs 2, 3, 4, usw. können in ähnlicher Weise für die Fraktionierung in aufeinanderfolgenden Läufen Elektrophorese vorbereitet werden. <a href="http://www.jove.com/files/ftp_upload/50243/50243fig2large.jpg" target="_blank">Klicken Sie hier, um eine größere Abbildung anzuzeigen.</a>

<table><tbody><tr><td colspan="4">&lt;strong&gt;REAGENTS&lt;/strong&gt;</td></tr><tr><td>N-methylisatoic anhydride (NMIA)</td><td>Life technologies</td><td>M25</td><td>Dissolve in anhydrous DMSO</td></tr><tr><td>1-methyl-t-nitroisatoic anhydride (1M7)</td><td>see ref. 22</td><td></td><td></td></tr><tr><td>Superscript III Reverse Transcriptase</td><td>Life technologies</td><td>18080044</td><td>10,000 units</td></tr><tr><td>Thermo sequenase cycle sequencing kit</td><td>Affymetrix</td><td>78500</td><td></td></tr><tr><td colspan="4">&lt;strong&gt;Materials provided by the user&lt;/strong&gt;</td></tr><tr><td>RNA of interest</td><td></td><td></td><td>6 pmol per reaction (the limit of detection will be determined by the instrument)</td></tr><tr><td>Sets of four 5&#039; labeled primers (Cy5, Cy5.5, WellRed D2 and WellRed D1/Licor IR800)</td><td></td><td></td><td>Primers are complementary to the RNA and are used in reverse transcription and sequencing reactions. The listed fluorophores are optimal for the Beckman Coulter 8000 CEQ. Primers may be purchased or synthesized in house.</td></tr><tr><td>DNA template</td><td></td><td></td><td>DNA is used for sequencing reactions, and must contain the sequence of the RNA being studied - including any 3&#039;terminal extension, if present. Where applicable, it is often convenient to use the RNA transcription template.</td></tr><tr><td colspan="4">&lt;strong&gt;Buffers&lt;/strong&gt;</td></tr><tr><td>10x RNA renaturation buffer</td><td></td><td></td><td>100 mM Tris-HCl pH 8.0, 1 M KCl, 1 mM EDTA</td></tr><tr><td>5X RNA folding buffer</td><td></td><td></td><td>200 mM Tris-HCl pH 8.0, 25 mM MgCl&lt;sub&gt;2&lt;/sub&gt;, 2.5 mM EDTA, 650 mM KCl. (This buffer might be changed depending on the case (&lt;em&gt;e.g.&lt;/em&gt; pH, EDTA, Mg, RNase inhibitor)</td></tr><tr><td>2.5X RT mix</td><td></td><td></td><td>4 &amp;mu;l 5X buffer, 1 &amp;mu;l 100 mM DTT, 1.5 &amp;mu;l water,1 &amp;mu;l 10 mM dNTPs, 0.5 &amp;mu;l SuperScript III. Note that the 5X buffer and 100 mM DTT are provided with purchase of SuperScript III (Invitrogen).</td></tr><tr><td>GenomeLab Sample Loading Solution (Beckman Coulter)</td><td></td><td></td><td>&lt;strong&gt;Attention:&lt;/strong&gt; Avoid multiple freeze-thaw cycles</td></tr><tr><td colspan="4">&lt;strong&gt;EQUIPMENT&lt;/strong&gt;</td></tr><tr><td>Capillary electrophoresis</td><td>Beckman</td><td>CEQ8000</td><td></td></tr><tr><td>Thermocycler</td><td>varies</td><td></td><td></td></tr></tbody></table>

rna secondary structure prediction using high-throughput shape

Das Verständnis der Funktion der RNA in biologischen Prozessen beteiligt erfordert eine gründliche Kenntnis der RNA-Struktur. Zu diesem Zweck wird die Methodik genannt &quot;High-Throughput-selektive 2-Hydroxyl Acylierung durch Primer-Extension analysiert&quot;, oder SHAPE ermöglicht Vorhersage von RNA Sekundärstruktur mit Einzel-Nukleotid-Auflösung. Dieser Ansatz nutzt chemische Sondierung Mittel, die Acylierung bevorzugt einzelsträngig oder flexiblen Bereiche der RNA in wässriger Lösung. Seiten der chemischen Modifizierung durch reverse Transkription der RNA modifiziert detektiert und die Produkte dieser Reaktion sind fraktioniert automatisierten Kapillarelektrophorese (CE). Seit Reverse Transkriptase Pausen an diesen RNA Nukleotide durch die Form Reagenzien modifiziert, die resultierende cDNA-Bibliothek indirekt abbildet diese Ribonukleotiden die einzigen im Rahmen der gefalteten RNA gestrandet sind. Mit ShapeFinder Software werden die Elektropherogrammen durch automatisierte CE produziert verarbeitet und in nugonucleotid Reaktivität Tabellen, die sich in Pseudo-Energie-Einschränkungen in der RNAStructure (v5.3) Vorhersage-Algorithmus verwendet wird, umgewandelt. Die zweidimensionalen RNA-Strukturen durch die Kombination FORM Sondieren mit in silico RNA Sekundärstrukturvorhersage erhalten haben, wurde festgestellt, dass viel genauer als Strukturen erhalten mit beiden Methoden allein.

RNA, die die HIV-1-rev-Response-Element (RRE) und eine 3&#39;-terminale Struktur Kassette 4 aus einem linearisierten Plasmid durch in vitro Transkription hergestellt, wonach es durch Erhitzen, Kühlen, und die Inkubation wurde bei 37 ° gefaltet C in Gegenwart MgCl 2. RNA wurde NMIA belichtet und dann von einem 5&#39;-Ende markierten DNA-Primer hybridisiert das 3&#39;-terminale Struktur Kassette revers transkribiert. Die resultierende Form cDNA-Bibliothek, zusammen mit Steuerungs-und Seque...

Watch this Scientific Journal Video about RNA Secondary Structure Prediction Using High-throughput SHAPE at JoVE.com

RNA Secondary Structure Prediction Using High-throughput SHAPE

Hochdurchsatz-selektiven 2-Hydroxyl-Acylierung durch Primer-Extension (FORM) analysiert verwendet einen neuartigen chemischen Tastertechnologie, reverse Transkription, Kapillarelektrophorese und Sekundärstrukturvorhersage Software, um die Strukturen der RNAs, die von mehreren hundert bis zu mehreren tausend bestimmen Nukleotide an Einzel-Nukleotid-Auflösung.

RNA Secondary Structure Prediction Mit High-Throughput-SHAPE

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed ...

rna-secondary-structure-prediction-using-high-throughput-shape

Research

Education

JoVE Journal

JoVE Core

Molecular Biology

Biology

Unit 1

Transcription: DNA to RNA

SCIENTISTS IN ACTION

31.3K Aufrufe.  Frederick National Laboratory for Cancer Research. Hochdurchsatz-selektiven 2-Hydroxyl-Acylierung durch Primer-Extension (FORM) analysiert verwendet einen neuartigen chemischen Tastertechnologie, reverse Transkription, Kapillarelektrophorese und Sekundärstrukturvorhersage Software, um die Strukturen der RNAs, die von mehreren hundert bis zu mehreren tausend bestimmen Nukleotide an Einzel-Nukleotid-Auflösung.

Serie: RNA Secondary Structure Prediction Using High-throughput SHAPE

Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding

The antigenic diversity of HIV-1 has long been an obstacle to vaccine design, and this variability is especially pronounced in the V3 loop of the virus' surface envelope glycoprotein. We previously proposed that the crown of the V3 loop, although dynamic and sequence variable, is constrained throughout the population of HIV-1 viruses to an immunologically relevant &beta;-hairpin tertiary structure. Importantly, there are thousands of different V3 loop crown sequences in circulating HIV-1 viruses, making 3D structural characterization of trends across the diversity of viruses difficult or impossible by crystallography or NMR. Our previous successful studies with folding of the V3 crown1, 2 used the ab initio algorithm 3 accessible in the ICM-Pro molecular modeling software package (Molsoft LLC, La Jolla, CA) and suggested that the crown of the V3 loop, specifically from positions 10 to 22, benefits sufficiently from the flexibility and length of its flanking stems to behave to a large degree as if it were an unconstrained peptide freely folding in solution. As such, rapid ab initio folding of just this portion of the V3 loop of any individual strain of the 60,000+ circulating HIV-1 strains can be informative. Here, we folded the V3 loop of the R2 strain to gain insight into the structural basis of its unique properties. R2 bears a rare V3 loop sequence thought to be responsible for the exquisite sensitivity of this strain to neutralization by patient sera and monoclonal antibodies4, 5. The strain mediates CD4-independent infection and appears to elicit broadly neutralizing antibodies. We demonstrate how evaluation of the results of the folding can be informative for associating observed structures in the folding with the immunological activities observed for R2.

Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding

The crown region of different V3 loop sequences of the surface envelope glycoprotein (gp120) of HIV-1 can be structurally characterized in many cases by in silico folding of positions 10 to 22 of the loop using a state-of-the-art ab initio folding algorithm. Here we demonstrate the folding and evaluation of this region of the V3 loop from the R2 strain of HIV-1, a uniquely neutralization sensitive strain with puzzling functional properties.

Bewertung von immunologisch relevanten dynamischen tertiären strukturellen Merkmale der HIV-1 V3-Loop Crown R2 Sequence durch Ab initio Folding

The antigenic diversity of HIV-1 has long been an obstacle to vaccine design, and this variability is especially pronounced in the V3 loop of the virus' ...

Forschung

Immunologie und Infektion

Combining Wet and Dry Lab Techniques to Guide the Crystallization of Large Coiled-coil Containing Proteins

Obtaining crystals for structure determination can be a difficult and time consuming proposition for any protein. Coiled-coil proteins and domains are found throughout nature, however, because of their physical properties and tendency to aggregate, they are traditionally viewed as being especially difficult to crystallize. Here, we utilize a variety of quick and simple techniques designed to identify a series of possible domain boundaries for a given coiled-coil protein, and then quickly characterize the behavior of these proteins in solution. With the addition of a strongly fluorescent tag (mRuby2), protein characterization is simple and straightforward. The target protein can be readily visualized under normal lighting and can be quantified with the use of an appropriate imager. The goal is to quickly identify candidates that can be removed from the crystallization pipeline because they are unlikely to succeed, affording more time for the best candidates and fewer funds expended on proteins that do not produce crystals. This process can be iterated to incorporate information gained from initial screening efforts, can be adapted for high-throughput expression and purification procedures, and is augmented by robotic screening for crystallization.

We describe a framework incorporating straightforward biochemical and computational analysis to guide the characterization and crystallization of large coiled-coil domains. This framework can be adapted for globular proteins or extended to incorporate a variety of high-throughput techniques.

Nass- und Trockenlabortechniken Die Kombination der Kristallisation von Large Coiled-Coil-Proteine ​​enthalten, zu Führer

Obtaining crystals for structure determination can be a difficult and time consuming proposition for any protein. Coiled-coil proteins and domains are ...

Biochemie

Self-assembly of Complex Two-dimensional Shapes from Single-stranded DNA Tiles

Current methods in DNA nano-architecture have successfully engineered a variety of 2D and 3D structures using principles of self-assembly. In this article, we describe detailed protocols on how to fabricate sophisticated 2D shapes through the self-assembly of uniquely addressable single-stranded DNA tiles which act as molecular pixels on a molecular canvas. Each single-stranded tile (SST) is a 42-nucleotide DNA strand composed of four concatenated modular domains which bind to four neighbors during self-assembly. The molecular canvas is a rectangle structure self-assembled from SSTs. A prescribed complex 2D shape is formed by selecting the constituent molecular pixels (SSTs) from a 310-pixel molecular canvas and then subjecting the corresponding strands to one-pot annealing. Due to the modular nature of the SST approach we demonstrate the scalability, versatility and robustness of this method. Compared with alternative methods, the SST method enables a wider selection of information polymers and sequences through the use of de novo designed and synthesized short DNA strands.

DNA tiling is an effective approach to make programmable nanostructures. We describe the protocols to construct complex two-dimensional shapes by the self-assembly of single-stranded DNA tiles.

Die Selbstorganisation von Complex zweidimensionale Formen von Einzelstrang-DNA-Fliesen

Current methods in DNA nano-architecture have successfully engineered a variety of 2D and 3D structures using principles of self-assembly. In this ...

Chemie

Atomic Scale Structural Studies of Macromolecular Assemblies by Solid-state Nuclear Magnetic Resonance Spectroscopy

Supramolecular protein assemblies play fundamental roles in biological processes ranging from host-pathogen interaction, viral infection to the propagation of neurodegenerative disorders. Such assemblies consist in multiple protein subunits organized in a non-covalent way to form large macromolecular objects that can execute a variety of cellular functions or cause detrimental consequences. Atomic insights into the assembly mechanisms and the functioning of those macromolecular assemblies remain often scarce since their inherent insolubility and non-crystallinity often drastically reduces the quality of the data obtained from most techniques used in structural biology, such as X-ray crystallography and solution Nuclear Magnetic Resonance (NMR). We here present magic-angle spinning solid-state NMR spectroscopy (SSNMR) as a powerful method to investigate structures of macromolecular assemblies at atomic resolution. SSNMR can reveal atomic details on the assembled complex without size and solubility limitations. The protocol presented here describes the essential steps from the production of 13C/15N isotope-labeled macromolecular protein assemblies to the acquisition of standard SSNMR spectra and their analysis and interpretation. As an example, we show the pipeline of a SSNMR structural analysis of a filamentous protein assembly.

Structures of supramolecular protein assemblies at atomic resolution are of high relevance because of their crucial roles in a variety of biological phenomena. Herein, we present a protocol to perform high-resolution structural studies on insoluble and non-crystalline macromolecular protein assemblies by magic-angle spinning solid-state nuclear magnetic resonance spectroscopy (MAS SSNMR).

Atomarer Skala strukturelle Studien der makromolekularen Versammlungen von Festkörper-NMR-Spektroskopie

Supramolecular protein assemblies play fundamental roles in biological processes ranging from host-pathogen interaction, viral infection to the ...

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences is desired. We herein provide a detailed in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) protocol to study the RNA structural change in the presence of an experimental drug for spinal muscular atrophy (SMA), survival of motor neuron (SMN)-C2, and in exon 7 of the pre-mRNA of the SMN2 gene. In in vitro SHAPE, an RNA sequence of 140 nucleotides containing SMN2 exon 7 is transcribed by T7 RNA polymerase, folded in the presence of SMN-C2, and subsequently modified by a mild 2&#39;-OH acylation reagent, 2-methylnicotinic acid imidazolide (NAI). This 2&#39;-OH-NAI adduct is further probed by a 32P-labeled primer extension and resolved by polyacrylamide gel electrophoresis (PAGE). Conversely, 2&#39;-OH acylation in in-cell SHAPE takes place in situ with SMN-C2 bound cellular RNA in living cells. The pre-mRNA sequence of exon 7 in the SMN2 gene, along with SHAPE-induced mutations in the primer extension, was then amplified by PCR and subject to next-generation sequencing. Comparing the two methodologies, in vitro SHAPE is a more cost-effective method and does not require computational power to visualize results. However, the in vitro SHAPE-derived RNA model sometimes deviates from the secondary structure in a cellular context, likely due to the loss of all interactions with RNA-binding proteins. In-cell SHAPE does not need a radioactive material workplace and yields a more accurate RNA secondary structure in the cellular context. Furthermore, in-cell SHAPE is usually applicable for a larger range of RNA sequences (~1,000 nucleotides) by utilizing next-generation sequencing, compared to in vitro SHAPE (~200 nucleotides) that usually relies on PAGE analysis. In case of exon 7 in SMN2 pre-mRNA, the in vitro and in-cell SHAPE derived RNA models are similar to each other.

Detailed protocols for both in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) experiments to determine the secondary structure of pre-mRNA sequences of interest in the presence of an RNA-targeting small molecule are presented in this article.

Mit In-vitro- und In der Zelle Form zu untersuchen, kleines Molekül induzierte Pre-mRNA Strukturveränderungen

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences ...

Genetik

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

The role of RNA structure in virtually any biological process has become increasingly evident, especially in the past decade. However, classical approaches to solving RNA structure, such as RNA crystallography or cryo-EM, have failed to keep up with the rapidly evolving field and the need for high-throughput solutions. Mutational profiling with sequencing using dimethyl sulfate (DMS) MaPseq is a sequencing-based approach to infer the RNA structure from a base&#39;s reactivity with DMS. DMS methylates the N1 nitrogen in adenosines and the N3 in cytosines at their Watson-Crick face when the base is unpaired. Reverse-transcribing the modified RNA with the thermostable group II intron reverse transcriptase (TGIRT-III) leads to the methylated bases being incorporated as mutations into the cDNA. When sequencing the resulting cDNA and mapping it back to a reference transcript, the relative mutation rates for each base are indicative of the base&#39;s &#34;status&#34; as paired or unpaired. Even though DMS reactivities have a high signal-to-noise ratio both in vitro and in cells, this method is sensitive to bias in the handling procedures. To reduce this bias, this paper provides a protocol for RNA treatment with DMS in cells and with in vitro transcribed RNA.

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

The protocol provides instruction for modifying RNA with dimethyl sulfate for mutational profiling experiments. It includes in vitro and in vivo probing with two alternative library preparation methods.

Untersuchung der RNA-Struktur mit Dimethylsulfat-Mutationsprofilierung mit Sequenzierung in vitro und in Zellen

The role of RNA structure in virtually any biological process has become increasingly evident, especially in the past decade. However, classical ...

A Protocol for Computer-Based Protein Structure and Function Prediction

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently &gt;20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.

Guidelines for computer based structural and functional characterization of protein using the I-TASSER pipeline is described. Starting from query protein sequence, 3D models are generated using multiple threading alignments and iterative structural assembly simulations. Functional inferences are thereafter drawn based on matches to proteins with known structure and functions.

Ein Protokoll für die Computer-Based Protein Structure and Function Prediction

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the ...

Biologie

The ITS2 Database

The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8.
The ITS2 Database9 presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11 accurately reannotated10. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12 (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.
The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14 search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16 and ProfDistS17 for multiple sequence-structure alignment calculation and Neighbor Joining18 tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.
In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.

The ITS2 Database is a workbench for phylogenetic inference simultaneously considering sequence and secondary structure of the internal transcribed spacer 2. This includes data collection with accurate annotation, structure prediction, multiple sequence-structure alignment and fast tree calculation. In a nutshell, this workbench simplifies first phylogenetic analyses to a few clicks.

Die ITS2 Database

The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades.  As ITS2 research mainly focused on the very ...

Analyzing and Building Nucleic Acid Structures with 3DNA

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic acid structures. This article presents detailed protocols for a subset of new and popular features available in 3DNA, applicable to both individual structures and ensembles of related structures. Protocol 1 lists the set of instructions needed to download and install the software. This is followed, in Protocol 2, by the analysis of a nucleic acid structure, including the assignment of base pairs and the determination of rigid-body parameters that describe the structure and, in Protocol 3, by a description of the reconstruction of an atomic model of a structure from its rigid-body parameters. The most recent version of 3DNA, version 2.1, has new features for the analysis and manipulation of ensembles of structures, such as those deduced from nuclear magnetic resonance (NMR) measurements and molecular dynamic (MD) simulations; these features are presented in Protocols 4 and 5. In addition to the 3DNA stand-alone software package, the w3DNA web server, located at <a href="http://w3dna.rutgers.edu" target="_blank">http://w3dna.rutgers.edu</a>, provides a user-friendly interface to selected features of the software. Protocol 6 demonstrates a novel feature of the site for building models of long DNA molecules decorated with bound proteins at user-specified locations.

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic acid structures. This article presents detailed protocols for a subset of new and popular features available in 3DNA, applicable to both individual structures and ensembles of related structures.

Analysieren und Bauen Nukleinsäurestrukturen mit 3DNA

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic ...

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (<a href="http://www.proteinwisdom.org" target="_blank">http://www.proteinwisdom.org</a>), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

We developed computational de novo protein design methods capable of tackling several important areas of protein design. To disseminate these methods we present Protein WISDOM, an online tool for protein design (<a href="http://www.proteinwisdom.org" target="_blank">http://www.proteinwisdom.org</a>). Starting from a structural template, design of monomeric proteins for increased stability and complexes for increased binding affinity can be performed.

Protein WISDOM: A Workbench für<em&gt; In silico</em&gt;<em&gt; De novo</em&gt; Aufbau von Biomolekülen

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific ...

RNA Secondary Structure Prediction Mit High-Throughput-SHAPE

Zusammenfassung

Weitere Videos entdecken

Kapitel in diesem Video

Bewertung von immunologisch relevanten dynamischen tertiären strukturellen Merkmale der HIV-1 V3-Loop Crown R2 Sequence durch Ab initio Folding

Nass- und Trockenlabortechniken Die Kombination der Kristallisation von Large Coiled-Coil-Proteine enthalten, zu Führer

Die Selbstorganisation von Complex zweidimensionale Formen von Einzelstrang-DNA-Fliesen

Atomarer Skala strukturelle Studien der makromolekularen Versammlungen von Festkörper-NMR-Spektroskopie

Mit In-vitro- und In der Zelle Form zu untersuchen, kleines Molekül induzierte Pre-mRNA Strukturveränderungen

Untersuchung der RNA-Struktur mit Dimethylsulfat-Mutationsprofilierung mit Sequenzierung in vitro und in Zellen

Ein Protokoll für die Computer-Based Protein Structure and Function Prediction

Die ITS2 Database

Analysieren und Bauen Nukleinsäurestrukturen mit 3DNA

Protein WISDOM: A Workbench für

RNA Secondary Structure Prediction Mit High-Throughput-SHAPE

Zusammenfassung

Weitere Videos entdecken

Kapitel in diesem Video

Bewertung von immunologisch relevanten dynamischen tertiären strukturellen Merkmale der HIV-1 V3-Loop Crown R2 Sequence durch Ab initio Folding

Nass- und Trockenlabortechniken Die Kombination der Kristallisation von Large Coiled-Coil-Proteine ​​enthalten, zu Führer

Die Selbstorganisation von Complex zweidimensionale Formen von Einzelstrang-DNA-Fliesen

Atomarer Skala strukturelle Studien der makromolekularen Versammlungen von Festkörper-NMR-Spektroskopie

Mit In-vitro- und In der Zelle Form zu untersuchen, kleines Molekül induzierte Pre-mRNA Strukturveränderungen

Untersuchung der RNA-Struktur mit Dimethylsulfat-Mutationsprofilierung mit Sequenzierung in vitro und in Zellen

Ein Protokoll für die Computer-Based Protein Structure and Function Prediction

Die ITS2 Database

Analysieren und Bauen Nukleinsäurestrukturen mit 3DNA

Protein WISDOM: A Workbench für

Nass- und Trockenlabortechniken Die Kombination der Kristallisation von Large Coiled-Coil-Proteine enthalten, zu Führer