Three-dimensional structures of RNA obtained by means of knowledge-based interaction potentials

One-bead coarse-grained model for RNA dynamics

We present a revised version of a coarse-grained model for RNA dynamics. In such approach, the description of nucleotides is reduced to single points that interact between them through a series of effective pair potentials that were obtained from an improved analysis of RNA structures from the Protein Data Bank. These interaction potentials are the main constituents of a Brownian dynamics simulation algorithm that allows to perform a variety of tasks by taking advantage of the reduced number of variables. Such tasks include the prediction of the three-dimensional configuration of a series of test molecules. Moreover, the model permits the inclusion of effective magnesium ions and the ends of the RNA chains can be pulled with an external force to study the process of unfolding. In spite of the simplicity of the model, we obtain a good agreement with the experimental results.

RNA folding: structure prediction, folding kinetics and ion electrostatics

Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

RNA pseudo-knots simulated with a one-bead coarse-grained model

We present a revised version of a Monte Carlo simulation model for RNA molecules that was introduced in a previous communication [O. Taxilaga-Zetina, P. Pliego-Pastrana, and M. D. Carbajal-Tinoco, Phys. Rev. E 81, 041914 (2010)]. The basic model consists of a series of knowledge-based pair potentials that were obtained from the statistical analysis of large RNAs belonging to the Protein Data Bank. These effective interactions are then used to dress a polymeric chain that reproduces relatively simple secondary structures (e.g., small hairpins). In order to describe more complicated three-dimensional structures such as pseudo-knots, here we include orientational information for the interaction between nucleotides forming hydrogen bonds, as in the case of the Watson-Crick base pairs. As a result, the simulated molecules obtained through the modified model are now consistent with their corresponding experimental configurations.

Modeling nucleic acids

Nucleic acids are an important class of biological macromolecules that carry out a variety of cellular roles. For many functions, naturally occurring DNA and RNA molecules need to fold into precise three-dimensional structures. Due to their self-assembling characteristics, nucleic acids have also been widely studied in the field of nanotechnology, and a diverse range of intricate three-dimensional nanostructures have been designed and synthesized. Different physical terms such as base-pairing and stacking interactions, tertiary contacts, electrostatic interactions and entropy all affect nucleic acid folding and structure. Here we review general computational approaches developed to model nucleic acid systems. We focus on four key areas of nucleic acid modeling: molecular representation, potential energy function, degrees of freedom and sampling algorithm. Appropriate choices in each of these key areas in nucleic acid modeling can effectively combine to aid interpretation of experimental data and facilitate prediction of nucleic acid structure.

Biological physics in México: Review and new challenges

Biological and physical sciences possess a long-standing tradition of cooperativity as separate but related subfields of science. For some time, this cooperativity has been limited by their obvious differences in methods and views. Biological physics has recently experienced a kind of revival (or better a rebirth) due to the growth of molecular research on animate matter. New avenues for research have been opened for both theoretical and experimental physicists. Nevertheless, in order to better travel for such paths, the contemporary biological physicist should be armed with a set of specialized tools and methods but also with a new attitude toward multidisciplinarity. In this review article, we intend to somehow summarize what has been done in the past (in particular, as an example we will take a closer look at the Mexican case), to show some examples of fruitful investigations in the biological physics area and also to set a proposal of new curricula for physics students and professionals interested in applying their science to get a better understanding of the physical basis of biological function.