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110/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects BCB 444/544 Lecture 25 More RNA Structure BCB 544 Projects #25_Oct19 Slide 2 210/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Mon Oct 15 - Lecture 23 Protein Tertiary Structure Prediction Chp 15 - pp 214 - 230 Wed Oct 17 & Thurs Oct 18 - Lecture 24 & Lab 8 (Terribilini) RNA Structure/Function & RNA Structure Prediction Chp 16 - pp 231 - 242 Fri Oct 18 - Lecture 25 (& Mon Oct 22) Gene Prediction Chp 8 - pp 97 - 112 Required Reading (before lecture) Slide 3 310/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Homework Assignment ALL: HomeWork #4 (emailed & posted online Sat AM) Due: Mon Oct 22 by 5 PM (not Fri Oct 19) Read: Ginalski et al.(2005) Practical Lessons from Protein Structure Prediction, Nucleic Acids Res. 33:1874-91. http://nar.oxfordjournals.org/cgi/content/full/33/6/1874 http://nar.oxfordjournals.org/cgi/content/full/33/6/1874 (PDF posted on website) Although somewhat dated, this paper provides a nice overview of protein structure prediction methods and evaluation of predicted structures. Your assignment is to write a summary of this paper - for details see HW#4 posted online & sent by email on Sat Oct 13 Slide 4 410/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects BCB 544 Only: New Homework Assignment 544 Extra#2 (posted online Thurs?) Due: Fri Nov 2 by 5 PM HW#2 is next step in Team Projects Will end lecture a few minutes early today - to allow time to meet & discuss 544 Teams & Projects Slide 5 510/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Seminars this Week BCB List of URLs for Seminars related to Bioinformatics: http://www.bcb.iastate.edu/seminars/index.html Oct 18 Thur - BBMB Seminar 4:10 in 1414 MBB Sachdeve Sidhu (Genentech) Phage peptide and antibody libraries in protein engineering and ligand selection Was great talk! Oct 19 Fri - BCB Faculty Seminar 2:10 in 102 ScI Lyric Bartholomay (Ent, ISU) Computational Biology and vector-borne disease: from the field to the bench Slide 6 610/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Another local example : Combining Structure Prediction, Machine Learning & "Real" (wet-lab) Experiments to Investigate the Lentiviral Rev Protein: A Step Toward New HIV Therapies Susan Carpenter (Washington State Univ) Wendy Sparks Yvonne Wannemuehler Drena Dobbs, GDCB Jae-Hyung Lee Michael Terribilini Kai-Ming Ho, Physics Yungok Ihm Haibo Cao Cai-zhuang Wang Gloria Culver, BBMB Laura Dutca Slide 7 710/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Chp 16 - RNA Structure Prediction SECTION V STRUCTURAL BIOINFORMATICS Xiong: Chp 16 RNA Structure Prediction (Terribilini) RNA Function Types of RNA Structures RNA Secondary Structure Prediction Methods Ab Initio Approach Comparative Approach Performance Evaluation Slide 8 810/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Function Storage/transfer of genetic information Newly discovered regulatory functions miRNA & si RNA pathways, especially Catalytic This slide has been changed Slide 9 910/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA types & functions Types of RNAsPrimary Function(s) mRNA - messengertranslation (protein synthesis) regulatory rRNA - ribosomaltranslation (protein synthesis) tRNA - transfertranslation (protein synthesis) hnRNA - heterogeneous nuclearprecursors & intermediates of mature mRNAs & other RNAs scRNA - small cytoplasmicsignal recognition particle (SRP) tRNA processing snRNA - small nuclear snoRNA - small nucleolar mRNA processing, polyA addition rRNA processing/maturation/methylation regulatory RNAs (siRNA, miRNA, etc.) regulation of transcription and translation, other?? Slide 10 1010/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Structures RNA forms complex 3D structures Mainly "single-stranded" - but: Single RNA strandscan self-hybridize to form Base-paired regions Slide 11 1110/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Levels of RNA Structure Like proteins, RNA has primary, secondary, and tertiary structure (& quaternary structure, too) 1.Primary structure = Ribonucleotide sequence 2.Secondary structure = Helix vs turn (base-paired vs single-stranded) Note: in RNA, helices often involve long-range interactions 3.Tertiary structure = 3D structure (also due to long-range interactions) 4.Quaternary structure = complex of 2 or more RNA strands Rob Knight Univ Colorado This slide has been changed Slide 12 1210/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Common structural motifs in RNA Helices Loops Hairpin Interior Bulge Multibranch Pseudoknots Tetraloops Fig 6.2 Baxevanis & Ouellette 2005 Slide 13 1310/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Fig 6.2 Baxevanis & Ouellette 2005 Covalent & non-covalent bonds in RNA Primary: Covalent bonds Secondary/Tertiary Non-covalent bonds H-bonds (base-pairing) Base stacking This is a new slide Slide 14 1410/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Structure Prediction RNA tertiary structure is very difficult to predict Focus on predicting RNA secondary structure: Given an RNA sequence, predict its secondary structure Almost all methods ignore higher order secondary structures such as pseudoknots & tetraloops Specialized software is available for predicting these This slide has been changed Slide 15 1510/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Pseudoknots & Tetraloops http://academic.brooklyn.cuny.edu/chem/z huang/QD/mckay_hr.gif This is a new slide http://www.lbl.gov/Science-Articles/Research- Review/Annual-Reports/1995/images/rna.gif Often have important regulatory or catalyltic functions PseudoknotTetraloop Slide 16 1610/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Base Pairing in RNA G-C, A-U, G-U ("wobble") & many variants http://www.fli-leibniz.de/ImgLibDoc/nana/IMAGE_NANA.html#basepairs See: IMB Image Library of Biological MoleculesIMB Image Library of Biological Molecules This slide has been changed Slide 17 1710/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Experimental RNA structure determination? X-ray crystallography NMR spectroscopy Enzymatic/chemical mapping Slide 18 1810/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Secondary Structure Prediction Methods Two (three, recently) main types of methods: 1.Ab initio - based on calculating most energetically favorable secondary structure(s) Energy minimization (thermodynamics) 2.Comparative approach - based on comparisons of multiple evolutionarily-related RNA sequences Sequence comparison (co-variation) 3.Combined computational & experimental Use experimental constraints when available This slide has been changed Slide 19 1910/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Secondary structure prediction - 1 1)Energy minimization (thermodynamics) Algorithms: Dynamic programming to find high probability pairs (also, some Genetic algorithms) Software: Mfold - Zuker RNAfold (Vienna Package) -Hofacker RNAstructure - Mathews Sfold - Ding & Lawrence R Knight 2005 This is a new slide Slide 20 2010/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Secondary structure prediction - 2 2) Comparative sequence analysis (co-variation) Algorithms: Mutual information Context-free grammars Software: RNAlifold Foldalign Dynalign This is a new slide Slide 21 2110/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNA Secondary structure prediction - 3 3) Combined experimental & computational Experiments: Map single-stranded vs double- stranded regions in folded RNA How? Enzymes: S1 nuclease, T1 RNase Chemicals: kethoxal, DMS, OH Software: Mfold Sfold RNAStructure RNAFold RNAlifold This is a new slide Kethoxal modification (mild) (strong) DMS modification (mild) (strong) G 200 240 220 DMS Slide 22 2210/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects 1 - Ab Initio Prediction Requires only a single RNA sequence Calculates minimum free energy structure Base-paired regions have lower free energy, so methods "attempt to find secondary structure with maximal base pairing" (Careful!) IMPORTANT: Largest contribution to energy is to nearest neighbor (base-stacking) interactions, not base-pairing! This slide has been changed Slide 23 2310/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Ab Initio Prediction: Clarifications Free energy is calculated based on parameters determined in the wet lab Correction: Use known energy associated with each type of nearest-neighbor pair (base-stacking) (not base-pair) Base-pair formation is not independent: multiple base-pairs adjacent to each other are more favorable than individual base-pairs - cooperative - because of base-stacking interactions Bulges and loops adjacent to base-pairs have a free energy penalty This slide has been changed Slide 24 2410/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Native tertiary structure or "fold" of an RNA molecule is (one of) its "lowest" free energy configuration(s) Gibbs free energy = G in kcal/mol at 37 C = equilibrium stability of structure lower values (negative) are more favorable Is this assumption valid? in vivo? - this may not hold, but we don't really know Ab Initio Prediction: What are the assumptions? This is a new slide Slide 25 2510/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects A U A=U Basepair G = -1.2 kcal/mole A U U A A=U U=A G = -1.6 kcal/mole Basepair What gives here? C Staben 2005 Energy minimization: What are the rules? This is a new slide Slide 26 2610/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Energy minimization calculations: Base-stacking is critical - Tinocco et al. C Staben 2005 This is a new slide Slide 27 2710/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Ab initio RNA Structure Prediction: Uses Nearest-neighbor parameters Most methods for ab initio prediction (free energy minimization) use nearest-neighbor energy parameters (derived from experiment) for predicting stability of an RNA secondary structure (in terms of G at 37 C) & most available software packages use same set of parameters - Mathews, Sabina, Zuker This is a new slide Slide 28 2810/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Ab Initio Energy Calculation Search for all possible base-pairing patterns Calculate total energy of each structure based on all stabilizing and destabilizing forces Fig 6.3 Baxevanis & Ouellette 2005 Total free energy for a specific RNA conformation = Sum of incremental energy terms for: helical stacking (sequence dependent) loop initiation unpaired stacking (favorable "increments" are < 0) This slide has been changed Slide 29 2910/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Dot Matrices Can be used to find all possible base pair patterns Compare input sequence to itself and put a dot where there is a complimentary base R Knight 2005 Slide 30 3010/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Dynamic Programming Finding optimal secondary structure is difficult - lots of possibilities Compare RNA sequence with itself Apply scoring scheme based on energy parameters for base stacking, cooperativity, and penalties for destabilizing forces Find path that represents most energetically favorable secondary structure This slide has been changed Slide 31 3110/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Problem with DP Approach DP returns SINGLE lowest energy structure There may be many structures with similar energies Also, predicted secondary structure is only as good as energy parameters used Solution: return multiple structures with near optimal energies Slide 32 3210/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Popular Ab Initio Prediction Programs Mfold Combines DP with thermodynamic calculations Fairly accurate for short sequences, less accurate as sequence length increases RNAfold Returns multiple structures near predicted optimal structure Computes larger number of potential secondary structures than Mfold, so uses a simplified energy function Slide 33 3310/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects 2 - Comparative Prediction Approaches Use multiple sequence alignment Assume related sequences fold into same secondary structure Slide 34 3410/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Co-variation patterns in MSAs are critical RNA functional motifs are conserved To maintain RNA structure during evolution, a mutation in a base-paired residue must be compensated for by a mutation in residue with which it pairs Comparative methods search for co-variation patterns in MSAs Slide 35 3510/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Consensus Structures Predict secondary structure of each individual sequence in a MSA Compare all structures and try to identify a consensus structure Slide 36 3610/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Popular Comparative Prediction Programs Two main types: 1.Require user to provide MSA RNAalifold 2.No MSA required Foldalign Dynalign Slide 37 3710/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects RNAalifold Requires user to provide MSA Creates a scoring matrix combining minimum free energy and co-variation information DP used to identify minimum free energy structure Slide 38 3810/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Foldalign User provides pair of unaligned RNA sequences Constructs alignment & computes conserved structure Suitable only for relatively short sequences Slide 39 3910/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Dynalign User provides two unaligned input sequences Calculates possible secondary structures using algorithm similar to Mfold Compares multiple structures from both sequences to find a common structure Slide 40 4010/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects 3 - Popular Programs that use Combined Computational Experimental Approaches Mfold Sfold RNAStructure RNAFold RNAlifold Slide 41 4110/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects SL X SL Y SL Z SL Y SL Z SL X SL Y SL Z SL X SL Y SL Z SL X Mfold -54.84 kcal/mol RNAstructure -71.3 kcal/molRNAfold -80.16 kcal/mol Sfold -51.14 kcal/mol Comparison of Predictions for Single RNA using Different Methods JH Lee 2007 Slide 42 4210/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Mfold plus constraints -54.84 kcal/mol Mfold -126.05 kcal/mol Comparison of Mfold Predictions: -/+ Constraints JH Lee 2007 Slide 43 4310/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects Performance Evaluation Ab initio methods? correlation coefficient = 20-60% Comparative approaches? correlation coefficient = 20-80% Programs that require user to supply MSA are more accurate Comparative programs are consistently more accurate than ab initio Base-pairs predicted by comparative sequence analysis for large & small subunit rRNAs are 97% accurate when compared with high resolution crystal structures! - Gutell, Pace BEST APPROACH? Methods that combine computational prediction (ab initio & comparative) with experimental constraints (from chemical/enzymatic modification studies) This slide has been changed Slide 44 4410/19/07BCB 444/544 F07 ISU Dobbs #25 - More RNA Structure & BCB 544 Projects BCB 544 "Team" Projects 544 Extra HW#2 is next step in Team Projects Write ~ 1 page outline Schedule meeting with Michael & Drena to discuss topic Read a few papers Write a more detailed plan You may work alone if you prefer Last week of classes will be devoted to Projects Written reports due: Mon Dec 3 (no class that day) Oral presentations (15-20') will be: Wed-Fri Dec 5,6,7 1 or 2 teams will present during each class period See Guidelines for Projects posted online