Friday, November 12, 2010

Locked nucleic acids (LNA) can be interpreted via rigid blocks too

A new crystal structure (NAR, 2010, 38, 6729) shows a representation of locked nucleic acids using the rigid-body parameter formalism imbeded in 3DNA. It's interesting to see that stretching this type of data in an orderly study one could even get to compute global properties of LNA's ala PNAS 98 paper of Olson, Gorin, et al.
It's also fun to redo their images into a prettier picture accompanied by numbers and compare the numbers to what happens with RNA conformations, and also with DNA conformations. The other way I've seen to modulate helical stretches of nucleic acids is with aptamers like the one of a previous post.

Tuesday, June 1, 2010

RNA Helix Junctions

To understand RNA we need first to split it into two main regions, that is:

1) Single strand.
2) Double-strand helical regions.

This has been known for quite a while now, and so people have done quite a good job at describing double-stranded helical regions where there is canonical Watson-Crick base-pairing, that is, G pairs with C forming 3 hydrogen-bonds, and A pairs to U, forming 2 hydrogen-bonds. Now, the part that is always left a bit out of the picture, or which at least is less commonly looked at is the single stranded part of RNA.
Aalberts and Nandagopal from Williams College in Massachusetts are pointing out this problem, specifically in relation to secondary structure prediction algorithms.
They have refined mfold to take better account of hairpin loops and "multi-branch" loops. By including some type of self-avoiding freely-jointed chain model called FJC2 they give a polymer theory description of loops and claim to decrease the mfold error for multibranches 10 times.

Yet another paper which is also concerned with the interplay between single-stranded and helical regions is another one of the unstoppable paper making machine of the Czechs.

Besseova, Reblova, Leontis and Sponer publish in NAR ahead of print on May 27 a summary of MD simulation performed on three-way junctions picked from the ribosome. They characterize their main normal modes of motion in a fashion similar to what has been carried on by their group for other parts of the ribosome. Strangely they don't cite Christian Laing's latest papers on junctions, nor Dave Lilley's, not even on passing.

Here's a picture of one of their simulation snapshots:

Monday, May 31, 2010

PLASMA AND MAGMA, future keywords to keep in mind

I had the great opportunity to attend a talk by Jack Dongarra in 2001 at a seminar-workshop at Merida, Venezuela, called Second Latin-American School on Parallelism and High Performance Computing. This was the first time I heard about the top 500 list of supercomputers, and also the first time I ever heard about grid computing, which has in a way evolved into cloud computing nowadays.
I remember that Dongarra's talk was one of my favorites because of its strong link to Moore's Law, and the prediction of the computational future as a simple power law. Since then, I've learned that I must change my laptop roughly every 14 months in order not to loose my investment completely, and also to be able to work competitively in my field, that of computational chemistry.
Due to a short news article by the BBC, I remembered, once again, the name of Jack Dongarra. When I googled "top500 dongarra" I stumbled upon a youtube talk at the University of British Columbia, I higly recommend watching it.

From the talk I learned that, if you do any kind of programming, and you do some sort of linear algebra operations in your code, you will inevitably have to move to PLASMA, that is, the new algorithms which take advantage of parallel execution, which is a growing need, according to the frequency limit on computer chips, clearly and neatly explained in Dongarra's talk at U.B.C.
Additional to PLASMA, we will have to learn MAGMA, that is, if we are going to use GPU's efficiently to solve computational chemistry problems, which brings to mind two relevant but naive questions:

1) Does the newly GPU implemented Amber 11 use MAGMA?
2) Would Dongarra be interested in having the generator matrices scheme for polymer modeling adapted to benchmark supercomputers? They already have gromacs and gamess in the fastest supercumputer, JAGUAR, so, why not?

Anyhow, I highly recommend periodically checking Dongarra's talks and ideas if you want a peek into the future.

Tuesday, May 18, 2010

Weekly Review / Monday May 17, 2010

In PDB code 2KR8, one has an example of a K-turn motif. The authors of the study call it specifically a U4-Kt RNA. It seems like there are no specific structural studies of K-turn RNA not bounded to protein. The study which discloses this PDB structure says to be the first to shown an unbound Kt-RNA structure using NMR

The authors are based in Grenoble France and Heidelberg Germany and publish in Nucleic Acids Res. 2010 May 13



Turner Lab. just released a new reparametrization of the amber99 forcefield. They call it amber99chi. So, the name makes it obvious. It has been reparametrized to get the chi torsion angles right in RNA, and also it has been reparametrized to get the sugar puckering conformations of RNA right, or at least better than amber99. They compared the new force field with NMR data and get better agreement than with just amber99.
J Chem Theory Comput. 2010 May 11;6(5):1520-1531

Friday, May 14, 2010

Uracyl-Tetrad Stabilizes Guanine-Quadruplexes

Simply put, the result shown in JACS that I want to blog about is the following:

"Besides G-platforms, there are also U-platforms"

That is, RNA can make a "planar" hydrogen-bonded network with four Uracyl bases.
It has been known for a while that such type of tetrads are possible for Guanine, and when various Guanine tetrads stack in top of each other they are called Guanine-Quadruplexes. It seems like the place where this structures occur is the human telomere. The human telomeres are regions of repeated DNA sequence at the end of chromosomes which protect DNA from degradation, their shortening is linked to the process or cellular aging.

The Tokyo University group of Xu, Ishizuka, Kimura, and Komiyama, shows that the U-tetrad stabilizes a G-Quadruplex structure. The results are obtained using NMR, so I don't know if atomic coordinate files are available to play with, if there are, I will post them here for you and I to play with.

Tuesday, May 4, 2010

Ribosome Controls 2/3 of the Dogma in Bacteria

In BACTERIA:
transcription speed = translation speed
speed of mRNA making = speed of protein making

Messenger RNA is synthesized by RNA polymerase (RNApol).
In the synthesis process two states can occur, either a forward synthesis state, or a backwards (i.e. backtracking) state making an equilibrium of:

Backwards = Forward

Sergey Proshkin, A. Rachid Rahmouni, Alexander Mironov and Evgeny Nudler show in Science. 2010 Apr 23;328(5977):504-8 that the ribosome shifts equilibrium to forward. They measure the rates of transcription and translation and use molecular tricks to enhance translation. Surprisingly the enhancement of translation induces higher transcription rates.

The second part of this discovery is the molecular component, which comes from Björn M. Burmann,Kristian Schweimer, Xiao Luo, Markus C. Wahl, Barbara L. Stitt, Max E. Gottesman, and Paul Rösch in Science. 2010 Apr 23;328(5977):501-4.
They characterize by NMR a transcription factor (a polymerase protein) called NusG, which, it seems, will bind to a ribosomal protein called NusE, therefore binding RNA polymerase and the ribosome.

With this in mind, it is not clear to me how to interpret the polysome micrographs for the coupled process in bacteria.



My guess is that only the "first" ribosome in the polysome couples to RNA polymerase, the other ribosomes which attach to mRNA in the polysome do not control the coupled rates of transcription-translation, and most likely don't care much about transcription fidelity. I wonder, if you were a protein, and then you were synthesized in that first ribosome, would you be different to your twin copy from the second or the third ribosome in the polysome?


I found this movie for the eukaryotic case:

http://www.ncbi.nlm.nih.gov/books/bookres.fcgi/mcb/ch4anim4.mov

NOTE: One reason why this is only possible in bacteria is that prokaryotes don't have a spliceosome, there is no splicing of pre-mRNA into mature-mRNA as far as I know.

Wednesday, April 21, 2010

Love python!

I love python simplicity.

The next code creates a random sequence of RNA of a desired length sooooo easily.


#!/usr/bin/python
import random
import sys

# Print the script usage info if the user
# doesn't supply the correct number of arguments.
if len(sys.argv) != 2:
print 'Usage: rnaseq.py '
sys.exit(1)

# Read the length of the random RNA sequence
# that you want to generate.
arg1 = sys.argv[1]

# Create the random sequence in the output file
outseq = open('rnaseq%s.seq' % arg1, 'w')
rna = ''.join([random.choice('AUGC') for x in range(int (arg1))])
outseq.write(rna)

Friday, April 2, 2010

The time is ripe for RNA

Maybe this is one of many posts which insist in the same point, but this time the indicator I'm using is one dear to all U.S.A. based chemists.
Simply, what I want to say is:
In every issue of Chemical and Engineering news there is at least one review per week of a new discovery or advance in RNA understanding, and this has been going on at least for the whole of the last year. Amazing!

This weeks issue mentions a radical mechanism used by enzymes to methylate adenines in the ribosome, and the previous week they talk about the other role of tRNA, that of being an apoptosis (cell-suicide) regulator, and I could go on.

Finally, Sponer's gang has published another article on quantum mechanical calculations of stacked bases. They previously did a study of stacked uracil's, now they are doing a study of stacked adenines. It's interesting to see that they seem not to know the trend on stacking interactions:
purine-purine > pyrimidine-purine > pyrimidine-pyrimidine
They do kind of; "trying to get it out of the way", mention that they are working in vacuo, that the experimental results in vacuo are not comparable, and at the same time they mention that solvation effects are important, explicitly for the B-DNA case, but they seem just to leave it at that.

Perhaps the reason for doing ApA is that someone told them about the NMR and solubility experiments which show the stacking trend?
Also, why don't they use the standard reference frame? It makes it hard to understand their stacked groups and to compare to say RNA geometrical information coming out of curves or 3dna from analysis of x-ray or NMR structures of RNA.

Friday, March 26, 2010

RNA Secondary Structure Drawing

RNA Secondary Structure drawing can be a very time consuming task, and many times it ends on tediously annotating an existent map using photoshop. Fortunately the people who are involved in developing programs to solve such task are getting better and better, although, for the ribosome, they're not there yet.
To summarize these are the programs and groups which can do the task:

Assemble by Fabrice Jossinet
http://serialized-thoughts.blogspot.com/

VARNA by Kevin Darty, Alain Denise and Yann Ponty
http://varna.lri.fr/index.html

Pseudo-viewer by Y. Byun and K. Han
http://wilab.inha.ac.kr/pseudoviewer

RNAMovies by Uni. Bielefeld group, Robert Giegerich, Dirk J. Evers
http://bibiserv.techfak.uni-bielefeld.de/rnamovies

XRNA by Noller lab.
http://rna.ucsc.edu/rnacenter/xrna/xrna.html

RNAstructure by Mathews/Turner labs.
http://rna.urmc.rochester.edu/RNAstructure.html

Tuesday, March 23, 2010

What is a non-structured RNA?

Westhof reviews an article of Weinberg at Breaker's lab (@ Yale) in Genome Biology, 2010, 11, 108.


I can't help but to wonder what non-structured RNA's are, and where one can find them.
Westhof is surprised about the possible emergence of a "whole new" wealth of structured RNA's, but then this makes me wonder what can a non-structured RNA possibly be?, and where are they at?, which shows my need to have a biologist friend. It also makes me wonder about mRNA structure, and why it remains, unstructured, if such is the case, is it due to temperature? Is it due to environment?, I mean, after what temperature are bases not so fond of base-pairing or stacking or, under which environments, meaning, more or less hydrated, closer or not to proteins, etc.

Song Cao, David P. Giedroc and Shi-Jie Chen in RNA 2010 16 538-552.


They extend Flory-Olson, virtual bond idea for RNA, to a new virtual bond between the C4' atom in the sugar, and the N9(N1) atom in the base, to predict loop–helix tertiary structural contacts in RNA pseudoknots, they have a program called V-fold which instantiates the model.
The picture for the, perhaps new (don't know for sure), virtual bond, follows:



J Comput Chem. 2010 Mar 17. Novel graph distance matrix. Randić M, Pisanski T, Novič M, Plavšić D.


And to wrap up these post on new articles for the week, Randic is at it again. He has published a paper which reviews graph distance matrices and proposes a new one which, he claims, can be used to describe 3D graphs of molecules, not just 2D, and in a different way to the D/D matrix which he has previously proposed. The new distance matrix is called ND (Novel Distance), and it's just the Euclidean Distance matrix of the Adjacency matrix of a molecular graph. YES!, that simple.

Monday, March 1, 2010

Weekly Briefing on RNA

In Zurich they (Erata, Kovacs, Sigel) find that using some type of fancy NMR technique called "(2)J-[(1)H,(15)N]-HSQC (Heteronuclear Single Quantum Coherence) NMR", they can find easier and faster ion bindings to N7 of RNA's Adenine and Guanine, that is, their Hoogsten "face". They use a 27 nucleotide domain 6 of group II Intron to prove their technique.

- J. Am. Chem. Soc., 2010, 132 (11), pp 3668–3669
Jacobs, Resendiz and Greenberg at Johns Hopkins do a direct strand breaking by creating a Uracil radical which then abstracts the C2' hydrogen from the sugar creating a C2' sugar radical which then follows by breakage of the C5' to O5' bond in the backbone. The backbone breakage in aerobic conditions is 1/7 that of the anaerobic case.






Weiss, Zhai, Bhatia and Romaniuk at British Columbia Canada have made an RNA aptamer which binds preferentially to Zinc Fingers (A common protein motif).

Wednesday, February 17, 2010

More RNA Motifs in the Ribosome

RNA (2010), 16:375–381

Matthieu G. Gagnon and Sergey V. Steinberg at the Department of Biochemistry of Montreal University report a "new structural motif" in the ribosome they call it: "A-Wedge Motif".

Every once in a while one can't help but to wonder how an article was accepted to a journal. I am not saying that the research is not unique, or that it's not an important discovery, what I'm saying, in this case, is that the new motif is explained in such an utterly confusing way, that I can't really tell what, or where, or how to find this motif. It almost feels as if one was reading a patent, where the wording is kept ambiguous in order to protect industrial secrets. It also seems unfair when you think about your own work or that of your colleagues which have a hard time being accepted for publication when something like this is published, seemingly, so easily.

Nonetheless my stubbornness has made me produce the following two pictures to try and understand what the A-wedge is.




An additional note to mention a new tool for VMD, it's called VDNA (Bioinformatics, 2009, Vol. 25, Pg. 3187), and it allows you to generate nucleosomal DNA structures automatically, and to produce 3DNA parameter output. Thomas Bishop from Tulane University at New Orleans is the author of this neat tool.

Monday, January 25, 2010

RMSD is not the only metric in the world.

RNA, Vol 15, 1875-1885, 2009
Parisien and Major hit another big methodology "goooool (read it in Spanish)" in the RNA bioinformatics little world.

They propose to use two new quantities, a deformation index, and a deformation profile, to better take into account the local similarity of nucleotides based on the stacking and base-pairing interaction geometry. This in contrast to the more common backbone-centric view, or the all-atom view, which traditionally has stuck to the RMSD metric.

The deformation index is just the ratio of the RMSD to the Mathews Correlation Coefficient. The Deformation Profile is a square matrix whose dimensions are the length of the RNA sequence, and it's values are the average inter-atomic distances between the pyridine ring of bases from a predicted structure with respect to a reference structure.

It has always been interesting to me how Major's group ideas have always felt to me as having a chemical graph theory flavour, which clearly comes from the computer scientist world. For some reason which eludes me, it's still to this day more trendy to approach the RNA bioinfo world from the C.S. side, that the chem. graph theory side. I should try and use this marketing trick myself.