11/04/05 d dobbs isu - bcb 444/544x: protein structure & function1 11/4/05 protein structure...

11/04/05 D Dobbs ISU - BCB 444/544X: Protein Structure & Function 1

11/4/05

Protein Structure & Function


Announcements

Exam 2 - Has been graded - Will be returned at end of class today

Grade statistics – 444 Average = 81/100 544 Average = 100/118

Questions?


AnnouncementsBCB 544 Projects - Important Dates:

Nov 2 Wed noon - Project proposals due to David/Drena

Nov 4 Fri PM - Approvals/responses & tentative presentation schedule to

students

Dec 2 Fri noon - Written project reports due

Dec 5,7,8,9 class/lab - Oral Presentations (20')

(Dec 15 Thurs = Final Exam)


Bioinformatics Seminars

Nov 4 Fri 12:10 PM BCB Faculty Seminar in E164 Lago How to do sequence alignments on parallel computers Srinivas Aluru, ECprE & Chair, BCB Program http://www.bcb.iastate.edu/courses/BCB691F2005.html

Next week:

Nov 10 Thurs 3:40 PM ComS Seminar in 223 Atanasoff

Computational Epidemiology Armin R. Mikler, Univ. North Texas

http://www.cs.iastate.edu/~colloq/#t3


Bioinformatics Seminars

CORRECTION:

Week after next - Baker Center/BCB Seminars: (seminar abstracts available at above link)

Nov 14 Mon 1:10 PM Doug Brutlag, StanfordDiscovering transcription factor binding

sites

Nov 15 Tues 1:10 PM Ilya Vakser, Univ Kansas Modeling protein-protein interactions both seminars will be in Howe Hall Auditorium


RNA Structure & Function/Prediction

Protein Structure & FunctionMon Review - promoter prediction

RNA structure & function

Wed RNA structure prediction 2' & 3' structure prediction miRNA & target prediction - Lab

10

Fri - a few more words re: Algorithms

Protein structure & function


Reading Assignment (for Fri/Mon)

Mount Bioinformatics• Chp 10 Protein classification & structure prediction

http://www.bioinformaticsonline.org/ch/ch10/index.html

• pp. 409-491 • Ck Errata:

http://www.bioinformaticsonline.org/help/errata2.html

Other? That should be plenty…


Review last lecture:

RNA Structure Prediction


miRNA and RNAi pathways

RISC

Dicerprecursor

miRNA siRNAs

Dicer

“translational repression”and/or mRNA degradation mRNA cleavage, degradation

RNAi pathway

microRNA pathwayMicroRNA primary transcript Exogenous dsRNA, transposon,

etc.

target mRNA

Drosha

RISCRISC

C Burge 2005


miRNA Challenges for Computational Biology

• Find the genes encoding microRNAs

• Predict their regulatory targets

• Integrate miRNAs into gene regulatory pathways & networks

Computational Prediction of MicroRNA Genes & Targets

C Burge 2005

Need to modify traditional paradigm of "transcriptional control" primarily by protein-DNA interactions to include miRNA regulatory mechanisms!


RNA structure prediction strategies

1)Energy minimization (thermodynamics)

2) Comparative sequence analysis (co-variation)

3) Combined experimental & computational

Secondary structure prediction


Secondary structure prediction strategies

1)Energy minimization (thermodynamics)

• Algorithm: Dynamic programming to find high probability pairs(also, some genetic algorithms)

• Software:Mfold - ZukerVienna RNA Package -

Hofacker RNAstructure - MathewsSfold - Ding & Lawrence

R Knight 2005



2) Comparative sequence analysis (co-variation)• Algorithms:

Mutual informationStochastic context-free grammars

• Software: ConStructAlifoldPfoldFOLDALIGNDynalign

R Knight 2005



3) Combined experimental & computational

• Experiment:Map single-stranded vs double-stranded regions in folded RNA

• How?Enzymes: S1 nuclease, T1 RNaseChemicals: kethoxal, DMS

R Knight 2005


Experimental RNA structure determination?

• X-ray crystallography

• NMR spectroscopy

• Enzymatic/chemical mapping

• Molecular genetic analyses


1) Energy minimization method

What are the assumptions?

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 37C

= equilibrium stability of structure lower values (negative) are more favorableIs this assumption valid?

in vivo? - this may not hold, but we don't really know


Free energy minimization

What are the rules?

A UA U

A=UA=U

Basepair

G = -1.2 kcal/mole

A UU A

A=UU=A

G = -1.6 kcal/mole

Basepair

What gives here?

C Staben 2005


Energy minimization calculations:Base-stacking is critical

AAUU

-1.2 CGGC

-3.0

AU or UAUA AU

-1.6 GCCG

-4.3

AG, AC, CA, GAUC, UG, GU, CU

-2.1 GUUG

-0.3

CCGG

-4.8 XG, GXYU, UY

0

- Tinocco et al.

C Staben 2005


Nearest-neighbor parameters

Most methods for free energy minimizationuse nearest-neighbor parameters (derived from experiment) for predicting stability of an RNA secondary structure (in terms of G at 37C)

& most available software packages use the same set of parameters: Mathews, Sabina, Zuker & Turner,

1999


Energy minimization - calculations:

Total free energy of a specific conformation for a specific RNA molecule = sum of incremental energy terms for:

• helical stacking (sequence dependent)• loop initiation• unpaired stacking

(favorable "increments" are < 0)

Fig 6.3Baxevanis & Ouellette 2005


But how many possible conformations for a single RNA molecule?

Huge number:Zuker estimates (1.8)N possible secondary

structures for a sequence of N nucleotides

for 100 nts (small RNA…) = 3 X 1025 structures!

Solution? Not exhaustive enumeration… Dynamic programming

O(N3) in time O(N2) in

space/storage iff pseudoknots

excluded, otherwise:O(N6 ), timeO(N4 ), space


Algorithms based on energy minimization

For outline of algorithm used in Mfold, including description of dynamic programming recursion, please visit Michael Zuker's lecture: http://www.bioinfo.rpi.edu/~zukerm/lectures/RNAfold-html

From this site, you may also download his lecture as either PDF or PS file.

Hmmm, something based on this might make an interesting "Final Exam" question: how could one apply dynamic programming approaches learned in first half of course to RNA structure prediction problem?


2) Comparative sequence analysis (co-variation)

Two basic approaches:

• Algorithms constrained by initial alignment

Much faster, but not as robust as unconstrained

Base-pairing probabilities determined by a partition function

• Algorithms not constrained by initial alignment

Genetic algorithms often used for finding an alignment & set of structures


RNA Secondary structure prediction: Performance?

How evaluate? • Not many experimentally determined structures

currently, ~ 50% are rRNA structures so "Gold Standard" (in absence of tertiary structure):

compare with predicted RNA secondary structure with that determined by

comparative sequence analysis (!!??) using Benchmark Datasets

NOTE: Base-pairs predicted by comparative sequence analysis for large & small subunit rRNAs are 97% accurate when compared with high resolution crystal structures!

- Gutell, Pace


RNA Secondary structure prediction: Performance?

1)Energy minimization (via dynamic programming) 73% avg. prediction accuracy - single

sequence2) Comparative sequence analysis

97% avg. prediction accuracy - multiple sequences (e.g., highly conserved rRNAs)much lower if sequence conservation is lower &/or fewer sequences are available for alignment

3) Combined - recent developments: combine thermodynamics & co-variation

& experimental constraints? IMPROVED RESULTS


RNA structure prediction strategies

Requires "craft" & significant user input & insight

1) Extensive comparative sequence analysis to predict tertiary contacts (co-variation)

e.g., MANIP - Westhof2) Use experimental data to constrain model

building e.g., MC-CYM - Major

3) Homology modeling using sequence alignment & reference tertiary structure (not many of these!)

4) Low resolution molecular mechanics e.g., yammp - Harvey

Tertiary structure prediction


New Today:




Protein structure - primarily determined by sequence

Protein function - primarily determined by structure

• Globular proteins: compact hydrophobic core & hydrophilic surface

• Membrane proteins: special hydrophobic surfaces

• Folded proteins are only marginally stable• Some proteins do not assume a stable "fold"

until they bind to something = Intrinsically disordered

Predicting protein structure and function can be very hard -- & fun!


4 Basic Levels of Protein Structure


Primary & Secondary Structure

Primary • Linear sequence of amino acids• Description of covalent bonds linking aa’s

Secondary • Local spatial arrangement of amino acids• Description of short-range non-covalent

interactions• Periodic structural patterns: -helix, -sheet


Tertiary & Quaternary Structure

Tertiary • Overall 3-D "fold" of a single polypeptide chain• Spatial arrangement of 2’ structural elements;

packing of these into compact "domains"• Description of long-range non-covalent

interactions (plus disulfide bonds)

Quaternary• In proteins with > 1 polypeptide chain, spatial

arrangement of subunits


"Additional" Structural Levels

• Super-secondary elements

• Motifs• Domains• Foldons

11/04/05 d dobbs isu - bcb 444/544x: protein structure & function1 11/4/05 protein structure...

Documents

d dobbs isu bcb

rna structure prediction

proteindna interactions

bcb program http

plenty slide

pm bcb faculty seminar

final exam slide

howe hall auditorium