DNA bending plays an important role in many biological processes, but its molecular and energetic details as a function of base sequence remain to be fully understood. Using a recently developed restraint, we have studied the controlled bending of four different B-DNA oligomers using molecular dynamics simulations. Umbrella sampling with the AMBER program and the recent parmbsc0 force field yield free energy curves for bending. Bending 15-base pair oligomers by 90° requires roughly 5 kcal mol−1, while reaching 150° requires of the order of 12 kcal mol−1. Moderate bending occurs mainly through coupled base pair step rolls. Strong bending generally leads to local kinks. The kinks we observe all involve two consecutive base pair steps, with disruption of the central base pair (termed Type II kinks in earlier work). A detailed analysis of each oligomer shows that the free energy of bending only varies quadratically with the bending angle for moderate bending. Beyond this point, in agreement with recent experiments, the variation becomes linear. An harmonic analysis of each base step yields force constants that not only vary with sequence, but also with the degree of bending. Both these observations suggest that DNA is mechanically more complex than simple elastic rod models would imply.

A current challenge in RNA structure prediction is the description of global helical arrangements compatible with a given secondary structure. Here we address this problem by developing a hierarchical graph sampling/data mining approach to reduce conformational space and accelerate global sampling of candidate topologies. Starting from a 2D structure, we construct an initial graph from size measures deduced from solved RNAs and junction topologies predicted by our data-mining algorithm RNAJAG trained on known RNAs. We sample these graphs in 3D space guided by knowledge-based statistical potentials derived from bending and torsion measures of internal loops as well as radii of gyration for known RNAs. Graph sampling results for 30 representative RNAs are analyzed and compared with reference graphs from both solved structures and predicted structures by available programs. This comparison indicates promise for our graph-based sampling approach for characterizing global helical arrangements in large RNAs: graph rmsds range from 2.52 to 28.24 Å for RNAs of size 25-158 nucleotides, and more than half of our graph predictions improve upon other programs. The efficiency in graph sampling, however, implies an additional step of translating candidate graphs into atomic models. Such models can be built with the same idea of graph partitioning and build-up procedures we used for RNA design.RNA 3D graph | Monte Carlo simulated annealing | RNA 3D prediction T he heightened interest in RNA biology with demonstrated successful applications to medicine and technology has presented new challenges to computational scientists in RNA structure prediction. Though general automated prediction of RNA tertiary (3D) structure from the primary sequence remains elusive, many effective approaches exist for analyzing and describing 3D RNA structures as well as predicting reasonably 3D aspects of small RNAs, ranging from coarse-grained modeling (1) to various structure assembly (2), energy minimization (3), molecular dynamics (4), and other conformational sampling approaches (5, 6).Interest in RNA structure prediction and its modular architecture has also led to many analyses of RNA local structure (7-12). In particular, several studies have focused on the helical arrangements formed by internal loops, important points of flexibility that can affect the overall 3D shape of RNAs. Indeed, the bending and torsion of helical arms connected by internal loops define unique helical conformations, as analyzed by AlHashimi and coworkers (7), Tang and Draper (8), Hagerman and coworkers (9), and Olson and coworkers (10). Recently, Pyle and coworkers (11) reported a pseudotorsional angle database from local RNA backbone geometry, and Sim and Levitt (12) cataloged preferred helical arrangements among nucleotide fragment assemblies given a secondary (2D) conformation. However, extensive topological and geometrical analyses over a large diverse set of RNAs do not exist.To such endeavors, mathematical and computational tools have been applied, including gra...

DNA-bending flexibility is central for its many biological functions. A new bending restraining method for use in molecular mechanics calculations and molecular dynamics simulations was developed. It is based on an average screw rotation axis definition for DNA segments and allows inducing continuous and smooth bending deformations of a DNA oligonucleotide. In addition to controlling the magnitude of induced bending it is also possible to control the bending direction so that the calculation of a complete (2-dimensional) directional DNA-bending map is now possible. The method was applied to several DNA oligonucleotides including A(adenine)-tract containing sequences known to form stable bent structures and to DNA containing mismatches or an abasic site. In case of G:A and C:C mismatches a greater variety of conformations bent in various directions compared to regular B-DNA was found. For comparison, a molecular dynamics implementation of the approach was also applied to calculate the free energy change associated with bending of A-tract containing DNA, including deformations significantly beyond the optimal curvature. Good agreement with available experimental data was obtained offering an atomic level explanation for stable bending of A-tract containing DNA molecules. The DNA-bending persistence length estimated from the explicit solvent simulations is also in good agreement with experiment whereas the adiabatic mapping calculations with a GB solvent model predict a bending rigidity roughly two times larger.