Search

The UNAFold software package is an integrated collection of programs that simulate folding, hybridization, and melting pathways for one or two single-stranded nucleic acid sequences. The name is derived from "Unified Nucleic Acid Folding." Folding (secondary structure) prediction for single-stranded RNA or DNA combines free energy minimization, partition function calculations and stochastic sampling. For melting simulations, the package computes entire melting profiles, not just melting temperatures. UV absorbance at 260 nm, heat capacity change (C(p)), and mole fractions of different molecular species are computed as a function of temperature. The package installs and runs on all Unix and Linux platforms that we have looked at, including Mac OS X. Images of secondary structures, hybridizations, and dot plots may be computed using common formats. Similarly, a variety of melting profile plots is created when appropriate. These latter plots include experimental results if they are provided. The package is "command line" driven. Underlying compiled programs may be used individually, or in special combinations through the use of a variety of Perl scripts. Users are encouraged to create their own scripts to supplement what comes with the package. This evolving software is available for download at http://www.bioinfo.rpi.edu/applications/hybrid/download.php .

This article presents a general statistical mechanical approach to describe self-folding together with the hybridization between a pair of finite length DNA or RNA molecules. The model takes into account the entire ensemble of single- and double-stranded species in solution and their mole fractions at different temperatures. The folding and hybridization models deal with matched pairs, mismatches, symmetric and asymmetric interior loops, bulges, and single-base stacking that might exist at duplex ends or at the ends of helices. All possible conformations of the single- and double-stranded species are explored. Only intermolecular basepairs are considered in duplexes at this stage.In particular we focus on the role of stacking between neighboring nucleotide residues of single unfolded strands as an important source of enthalpy change on helix formation which has not been modeled computationally thus far. Changes in the states of the single strands with temperature are shown to lead to a larger heat effect at higher temperature. An important consequence of this is that predictions of enthalpies, which are based on databases of nearest-neighbor energy parameters determined for molecules or duplexes with lower melting temperatures compared with the melting temperatures of the oligos for which they are used as a predictive tool, will be underestimated.

The abbreviated name, 'mfold web server', describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and 'energy dot plots', are available for the folding of single sequences. A variety of 'bulk' servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as 'MFOLDROOT'.

New results for calculating nucleic acid secondary structure by free energy minimization and phylogenetic comparisons have recently been reported. A complete set of DNA energy parameters is now available and the RNA parameters have been improved. Although databases of RNA secondary structures are still derived and expanded using computer-assisted, ad hoc comparative analysis, a number of new computer algorithms combine covariation analysis with energy methods.