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Title: Prsentation PowerPoint


1
The RNA World Lecture 7 RNA/ligand RNA
/protein interactions RNA energetics
2
Induce fit of RNA structures
  • RNA unstructured, protein structured
  • RNA structured, protein unstructured
  • RNA unstructured, protein unstructured

Structure induce fit of RNA by the protein
Structure induce fit for the RNA and the protein
3
Large conformational change upon binding
4
The ATP aptamer NMR structure a GNRA like motif
ATP
ATP
ATP
Dieckman et al. (1996) RNA 2, 628 Jiang et al.
(1996) Nature 382, 183
5
Comparison of the GUAA tetraloop structure (in
blue) and the ATP binding motif (ATP is in red)
Dieckman et al. (1996)
6
Classes of Antibiotics that target rRNA
decoding 16S
Aminoglycosides Macrolides Ribotoxins Lincosamides
Chloramphenicol Puromycin Thiostrepton Tetracycli
ne
PTC 23S (tunnel)
PTC 23S
PTC 23S
decoding 16S
7
16S ribosomal RNA
Spectinomycin Streptomycin Paromomycin Tetracyc
line
Elongation step is inhibited by tetracyclines
(inhibit the binding of aa-tRNA to the A site in
bacteria 16S)
RR0016 Carter, et al. 2000
http//www.rna.icmb.utexas.edu
8
Antibiotics that bind to the 16S rRNA
Phosphate groups and protein side chain
Bases groups
Phosphate and bases groups
Magnesium ions
Vincens Westhof (2003) ChemBioChem 4, 1018-1023
9
An example of structured bulge in presence of
Argininamide
A bulge that folds into a define 3D structure
once it binds the TAT peptide or
argininamide RNA structures can be induced by
peptides, proteins or ligands (see Chap 16 and 17)
10
BIV Tat/TAR complex
HIV Rev/RRE complex
Arginine (R) rich peptides
Phage lambda N/ boxB RNA complex
Phage P22 N/ box B RNA complex
11
Discrimination between bases in the major groove
of DNA and RNA more easy than in the minor groove
In RNA, edges of base pairs are inaccessible in
the deep groove of A-form RNA but most
recognition can occur in short duplex regions
interrupted by bulges and loops. Protein can
recognize RNA 3D shapes. Interaction with the
more accessible minor groove.
12
Amino acids most often hydrogen-bonded to DNA and
RNA are Asn, Gln, Glu, Lys and Arg residues
Discrimination between T-A (or U-A) and C-G
Arg (R)
Hydrophobic recognition (in DNA)
Asn (N)
Recognition of 2OH in RNA!
Bases can be recognized in multiple ways -gt no
simple amino-acid-to-base code
13
Asn
Strong distorsion of the AC tRNA loop
14
Water molecule can be specifically oriented by
interactions with the protein (surrogate side
chain).
Network of H-bonding involving water molecules
15
Interaction between single-stranded RNA and the
bacteriophage MS2 coat protein
Interaction with Ser (S) and Thr (T)
16
Elements of RNA energetics
17
Free energy estimates Where are they coming from?
(1) London - van der Waals interactions
Bij Aij rij12 rij6
?-? electrons Interactions in base stacking
E
-
Dispersion-repulsion forces
(2) Hydrogen bond interactions
18
The concentration of nucleotides can be easily
determined by measuring the absorbance at 260nm
conc ODlmax/(?260 x d)
19
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20
In the nearest-neighbor model, the measured
thermodynamics of double-strand formation can be
approximately divided into an initiation step of
forming the first base pair followed by
successive propagation steps of adding base
pairs. What will matter for the stability of
base pairs is their directly adjacent neighbors.
21
Thermodynamic tables for Watson-Crick pairs and
others
Nearest neighbor model for estimating the free
energy change of 2D structure formation
If the sequence is palindromic, there is a
symmetry correction parameter that should be
added. Otherwise, this parameter is omitted.
22
Calculation of the predicted free energy at 37C
for the RNA duplex
Energies for base pair propagation
-
23
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24
Coaxial stacks the stacking of two adjacent
helices contribute significantly to RNA stability
RNA World (chap. 10)
25
In RNA structure, stacking is optimized and very
few bases are left unstacked! See also the
structure of the tRNA (lecture 5)
26
Prediction of RNA secondary structures based on
thermodynamic stability calculation
73 accurate
Starting with a sequence, find RNA 2D structures
with the lowest free energy as well as suboptimal
2D structures mfold or RNA structure
programs (Michael Zuker) http//www.bioinfo.rpi.ed
u/zukerm/ RNA Vienna package http//www.tbi.univ
ie.ac.at/ivo/RNA/
Very good starting point for getting an idea of
the 2D structure if only one RNA sequence is
available! The accuracy of the prediction can be
improved to 86 if chemical probing data are
available.
Matrix representation
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