A Probabilistic Model of RNA Conformational Space Export

@article{citeulike:4901958, abstract = {<title>Author Summary</title> <p>The importance of RNA in biology and medicine has increased immensely over the last several years, due to the discovery of a wide range of important biological processes that are under the guidance of non-coding RNA. As is the case with proteins, the function of an RNA molecule is encoded in its three-dimensional (3-D) structure, which in turn is determined by the molecule's sequence. Therefore, interest in the computational prediction of the 3-D structure of RNA from sequence is great. One of the main bottlenecks in routine prediction and simulation of RNA structure and dynamics is sampling, the efficient generation of RNA-like conformations, ideally in a mathematically and physically sound way. Current methods require the use of unphysical energy functions to amend the shortcomings of the sampling procedure. We have developed a mathematical model that describes RNA's conformational space in atomic detail, without the shortcomings of other sampling methods. As an illustration of its potential, we describe a simple yet efficient method to sample conformations that are compatible with a given secondary structure. An implementation of the sampling method, called BARNACLE, is freely available.</p>}, author = {Frellsen, Jes and Moltke, Ida and Thiim, Martin and Mardia, Kanti V. and Ferkinghoff-Borg, Jesper and Hamelryck, Thomas}, citeulike-article-id = {4901958}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.1000406}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19543381}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19543381}, day = {19}, doi = {10.1371/journal.pcbi.1000406}, journal = {PLoS Comput Biol}, keywords = {beta-hairpin, cmn, dihedral, free-energy, hexapeptide, short-peptides}, month = {June}, number = {6}, pages = {e1000406+}, posted-at = {2009-06-19 10:09:14}, priority = {5}, publisher = {Public Library of Science}, title = {A Probabilistic Model of RNA Conformational Space}, url = {http://dx.doi.org/10.1371/journal.pcbi.1000406}, volume = {5}, year = {2009} }

TY - JOUR ID - citeulike:4901958 L3 - citeulike-article-id:4901958 N2 - <title>Author Summary</title> <p>The importance of RNA in biology and medicine has increased immensely over the last several years, due to the discovery of a wide range of important biological processes that are under the guidance of non-coding RNA. As is the case with proteins, the function of an RNA molecule is encoded in its three-dimensional (3-D) structure, which in turn is determined by the molecule's sequence. Therefore, interest in the computational prediction of the 3-D structure of RNA from sequence is great. One of the main bottlenecks in routine prediction and simulation of RNA structure and dynamics is sampling, the efficient generation of RNA-like conformations, ideally in a mathematically and physically sound way. Current methods require the use of unphysical energy functions to amend the shortcomings of the sampling procedure. We have developed a mathematical model that describes RNA's conformational space in atomic detail, without the shortcomings of other sampling methods. As an illustration of its potential, we describe a simple yet efficient method to sample conformations that are compatible with a given secondary structure. An implementation of the sampling method, called BARNACLE, is freely available.</p> IS - 6 JF - PLoS Comput Biol TI - A Probabilistic Model of RNA Conformational Space PB - Public Library of Science VL - 5 SP - e1000406 KW - beta-hairpin KW - cmn KW - dihedral KW - free-energy KW - hexapeptide KW - short-peptides AU - Frellsen, Jes AU - Moltke, Ida AU - Thiim, Martin AU - Mardia, Kanti AU - Ferkinghoff-Borg, Jesper AU - Hamelryck, Thomas PY - 2009/06/19/ UR - http://dx.doi.org/10.1371/journal.pcbi.1000406 ER -