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It has more functionalities than DSSR basic (the free academic version), including: (i) homology modeling via in silico base mutations, a feature employed by Merck scientists, (ii) easy generation of regular helical models, including circular or super-helical DNA (see figures below), (iii) creation of customized structures with user-specified base sequences and rigid-body parameters, (iv) efficient processing of molecular dynamics (MD) trajectories, (v) detailed characterization of DNA-protein or RNA-protein spatial interactions, and (vi) template-based modeling of DNA-protein complexes (see figures below). DSSR may be licensed from Columbia University. DSSR has also been adopted into numerous other structural bioinformatics resources, including: (i) URS, (ii) RiboSketch, (iii) RNApdbee, (iv) forgi, (v) RNAvista, (vi) VeriNA3d, (vii) RNAMake, (viii) ElTetrado, (ix) DNAproDB, (x) LocalSTAR3D, (xi) IPANEMAP, and (xii) RNANet.Īdvanced features. The DSSR-Jmol and DSSR-PyMOL integrations bring unparalleled search capabilities (e.g., ‘select junctions’ for all multi-branch loops) and innovative visualization styles into 3D nucleic acid structures. To make DSSR as widely accessible as possible, I have initiated collaborations with the principal developers of Jmol and PyMOL. Shaw Research), (iv) “Predicting site-binding modes of ions and water to nucleic acids using molecular solvation theory” ( JACS, 2019), (v) “RIC-seq for global in situ profiling of RNA- RNA spatial interactions” ( Nature, 2020), and (vi) “DNA mismatches reveal conformational penalties in protein- DNA recognition” ( Nature, 2020).īroad integrations. DSSR has been widely cited in scientific literature, including: (i) “Selective small-molecule inhibition of an RNA structural element” ( Nature, 2015 Merck Research Laboratories), (ii) “The structure of the yeast mitochondrial ribosome” ( Science, 2017), (iii) “RNA force field with accuracy comparable to state-of-the-art protein force fields” ( PNAS, 2018 D. It streamlines tasks in RNA/DNA structural bioinformatics, and outperforms its ‘competitors’ by far in terms of functionality, usability, and support.
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DSSR has been made possible by the developer’s extensive user-support experience, detail-oriented software engineering skills, and expert domain knowledge accumulated over two decades. It is built upon the well-known, tested, and trusted 3DNA suite of programs. DSSR (Dissecting the Spatial Structure of RNA) is an integrated software tool for the analysis/annotation, model building, and schematic visualization of 3D nucleic acid structures (see the figures below and the video overview).
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