Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites; ii) the training and test datasets; iii) the algorithmic methods for the prediction strategies; iv) the performance measures and v) the distribution and availability of the prediction programs. Here we report a large-scale assessment of 19 web servers and 3 stand-alone programs on 41 datasets including more than 5000 proteins derived from 3D structures of protein-nucleic acid complexes. Well-defined binary assessment criteria (specificity, sensitivity, precision, accuracy…) are applied. We found that i) the tools have been greatly improved over the years; ii) some of the approaches suffer from theoretical defects and there is still room for sorting out the essential mechanisms of binding; iii) RNA binding and DNA binding appear to follow similar driving forces and iv) dataset bias may exist in some methods.

SUMMARY: Assemble is an intuitive graphical interface to analyze, manipulate and build complex 3D RNA architectures. It provides several advanced and unique features within the framework of a semi-automated modeling process that can be performed by homology and ab initio with or without electron density maps. Those include the interactive editing of a secondary structure and a searchable, embedded library of annotated tertiary structures. Assemble helps users with performing recurrent and otherwise tedious tasks in structural RNA research. AVAILABILITY AND IMPLEMENTATION: Assemble is released under an open-source license (MIT license) and is freely available at http://bioinformatics.org/assemble. It is implemented in the Java language and runs on MacOSX, Linux and Windows operating systems.

SUMMARY: Efficient RNA sequence manipulations (such as multiple alignments) need to be constrained by rules of RNA structure folding. The structural knowledge has increased dramatically in the last years with the accumulation of several large RNA structures similar to those of the bacterial ribosome subunits. However, no tool in the RNA community provides an easy way to link and integrate progress made at the sequence level using the available three-dimensional information. Sequence to Structure (S2S) proposes a framework in which an user can easily display, manipulate and interconnect heterogeneous RNA data, such as multiple sequence alignments, secondary and tertiary structures. S2S has been implemented using the Java language and has been developed and tested under UNIX systems, such as Linux and MacOSX. AVAILABILITY: S2S is available at http://bioinformatics.org/S2S/.