Software for predicting the 3D structure of RNA molecules

Computational Modeling of RNA Aptamers: Structure Prediction of the Apo State

RNA aptamers are single-stranded oligonucleotides that bind to specific molecular targets with high affinity and specificity. To design aptamers for new applications, it is critical to understand the ligand binding mechanism in terms of the structure and dynamics of the ligand-bound and apo states. The problem is that most of the NMR or X-ray crystal structures available for RNA aptamers are for ligand-bound states. Available apo state structures, mostly characterized by crystallization under nonphysiological conditions or probed by low resolution techniques, might fail to represent the diverse structural variations of the apo state in solution. Here, we develop an approach to obtain a representative ensemble of apo structures that are based on in silico RNA 3D structure prediction and in vitro experiments that characterize base stacking. Using the neomycin-B aptamer as a case study, an ensemble of structures for the aptamer in the apo (unbound) state are validated and then used to investigate the ligand-binding mechanism for the aptamer in complex with neomycin-B.

Molecular Modeling Applied to Nucleic Acid-Based Molecule Development

Molecular modeling by means of docking and molecular dynamics (MD) has become an integral part of early drug discovery projects, enabling the screening and enrichment of large libraries of small molecules. In the past decades, special emphasis was drawn to nucleic acid (NA)-based molecules in the fields of therapy, diagnosis, and drug delivery. Research has increased dramatically with the advent of the SELEX (systematic evolution of ligands by exponential enrichment) technique, which results in single-stranded DNA or RNA sequences that bind with high affinity and specificity to their targets. Herein, we discuss the role and contribution of docking and MD to the development and optimization of new nucleic acid-based molecules. This review focuses on the different approaches currently available for molecular modeling applied to NA interaction with proteins. We discuss topics ranging from structure prediction to docking and MD, highlighting their main advantages and limitations and the influence of flexibility on their calculations.

Three-dimensional modeling of single stranded DNA hairpins for aptamer-based biosensors

Aptamers consist of short oligonucleotides that bind specific targets. They provide advantages over antibodies, including robustness, low cost, and reusability. Their chemical structure allows the insertion of reporter molecules and surface-binding agents in specific locations, which have been recently exploited for the development of aptamer-based biosensors and direct detection strategies. Mainstream use of these devices, however, still requires significant improvements in optimization for consistency and reproducibility. DNA aptamers are more stable than their RNA counterparts for biomedical applications but have the disadvantage of lacking the wide array of computational tools for RNA structural prediction. Here, we present the first approach to predict from sequence the three-dimensional structures of single stranded (ss) DNA required for aptamer applications, focusing explicitly on ssDNA hairpins. The approach consists of a pipeline that integrates sequentially building ssDNA secondary structure from sequence, constructing equivalent 3D ssRNA models, transforming the 3D ssRNA models into ssDNA 3D structures, and refining the resulting ssDNA 3D structures. Through this pipeline, our approach faithfully predicts the representative structures available in the Nucleic Acid Database and Protein Data Bank databases. Our results, thus, open up a much-needed avenue for integrating DNA in the computational analysis and design of aptamer-based biosensors.