Structural insights into the morpholino nucleic acid/RNA duplex using the new XNA builder Ducque in a molecular modeling pipeline.

The field of synthetic nucleic acids with novel backbone structures [xenobiotic nucleic acids (XNAs)] has flourished due to the increased importance of XNA antisense oligonucleotides and aptamers in medicine, as well as the development of XNA processing enzymes and new XNA genetic materials. Molecular modeling on XNA structures can accelerate rational design in the field of XNAs as it contributes in understanding and predicting how changes in the sugar-phosphate backbone impact on the complementation properties of the nucleic acids. To support the development of novel XNA polymers, we present a first-in-class open-source program (Ducque) to build duplexes of nucleic acid analogs with customizable chemistry. A detailed procedure is described to extend the Ducque library with new user-defined XNA fragments using quantum mechanics (QM) and to generate QM-based force field parameters for molecular dynamics simulations within standard packages such as AMBER. The tool was used within a molecular modeling workflow to accurately reproduce a selection of experimental structures for nucleic acid duplexes with ribose-based as well as non-ribose-based nucleosides. Additionally, it was challenged to build duplexes of morpholino nucleic acids bound to complementary RNA sequences.

A superposition free method for protein conformational ensemble analyses and local clustering based on a differential geometry representation of backbone.

Here a differential geometry (DG) representation of protein backbone is explored on the analyses of protein conformational ensembles. The protein backbone is described by curvature, κ, and torsion, τ, values per residue and we propose 1) a new dissimilarity and protein flexibility measurement and 2) a local conformational clustering method. The methods were applied to Ubiquitin and c-Myb-KIX protein conformational ensembles and results show that κ\τ metric space allows to properly judge protein flexibility by avoiding the superposition problem. The dmax measurement presents equally good or superior results when compared to RMSF, especially for the intrinsically unstructured protein. The clustering method is unique as it relates protein global to local dynamics by providing a global clustering solutions per residue. The methods proposed can be especially useful to the analyses of highly flexible proteins. The software written for the analyses presented here is available at https://github.com/AMarinhoSN/FleXgeo for academic usage only.

Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery.

Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding.