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RNAs provide considerable opportunities as therapeutic agent to expand the plethora of classical therapeutic targets, from extracellular and surface proteins to intracellular nucleic acids and its regulators, in a wide range of diseases. RNA versatility can be exploited to recognize cell types, perform cell therapy, and develop new vaccine classes. Therapeutic RNAs (aptamers, antisense nucleotides, siRNA, miRNA, mRNA and CRISPR-Cas9) can modulate or induce protein expression, inhibit molecular interactions, achieve genome editing as well as exon-skipping. A common RNA thread, which makes it very promising for therapeutic applications, is its structure, flexibility, and binding specificity. Moreover, RNA displays peculiar structural plasticity compared to proteins as well as to DNA. Here we summarize the recent advances and applications of therapeutic RNAs, and the experimental and computational methods to analyze their structure, by biophysical techniques (liquid-state NMR, scattering, reactivity, and computational simulations), with a focus on dynamic and flexibility aspects and to binding analysis. This will provide insights on the currently available RNA therapeutic applications and on the best techniques to evaluate its dynamics and reactivity.

The exposure to pathogens triggers the activation of adaptive immune responses through antigens bound to surface receptors of antigen presenting cells (APCs). T cell receptors (TCR) are responsible for initiating the immune response through their physical direct interaction with antigen-bound receptors on the APCs surface. The study of T cell interactions with antigens is considered of crucial importance for the comprehension of the role of immune responses in cancer growth and for the subsequent design of immunomodulating anticancer drugs. RNA sequencing experiments performed on T cells represented a major breakthrough for this branch of experimental molecular biology. Apart from the gene expression levels, the hypervariable CDR3α/β sequences of the TCR loops can now be easily determined and modelled in the three dimensions, being the portions of TCR mainly responsible for the interaction with APC receptors. The most direct experimental method for the investigation of antigens would be based on peptide libraries, but their huge combinatorial nature, size, cost, and the difficulty of experimental fine tuning makes this approach complicated time consuming, and costly. We have implemented in silico methodology with the aim of moving from CDR3α/β sequences to a library of potentially antigenic peptides that can be used in immunologically oriented experiments to study T cells’ reactivity. To reduce the size of the library, we have verified the reproducibility of experimental benchmarks using the permutation of only six residues that can be considered representative of all ensembles of 20 natural amino acids. Such a simplified alphabet is able to correctly find the poses and chemical nature of original antigens within a small subset of ligands of potential interest. The newly generated library would have the advantage of leading to potentially antigenic ligands that would contribute to a better understanding of the chemical nature of TCR-antigen interactions. This step is crucial in the design of immunomodulators targeted towards T-cells response as well as in understanding the first principles of an immune response in several diseases, from cancer to autoimmune disorders.

In recent years, protein science has been revolutionized by the discovery of intrinsically disordered proteins (IDPs). In contrast to the classical paradigm that a given protein sequence corresponds to a defined structure and an associated function, we now know that proteins can be functional in the absence of a stable three-dimensional structure. In many cases, disordered proteins or protein regions become structured, at least locally, upon interacting with their physiological partners. Many, sometimes conflicting, hypotheses have been put forward regarding the interaction mechanisms of IDPs and the potential advantages of disorder for protein-protein interactions. Whether disorder may increase, as proposed e.g. in the fly-casting hypothesis, or decrease binding rates, increase or decrease binding specificity, or what role pre-formed structure might play in interactions involving IDPs (conformational selection vs. induced fit), are subjects of intense debate. Experimentally, these questions remain difficult to address. Here, we review experimental studies of binding mechanisms of IDPs using NMR spectroscopy and transient kinetic techniques, as well as the underlying theoretical concepts and numerical methods that can be applied to describe these interactions at the atomic level. The available literature suggests that the kinetic and thermodynamic parameters characterizing interactions involving IDPs can vary widely and that there may be no single common mechanism that can explain the different binding modes observed experimentally. Rather, disordered proteins appear to make combined use of features such as pre-formed structure and flexibility, depending on the individual system and the functional context.

Mutations in PKD1, the gene encoding for the receptor Polycystin-1 (PC-1), cause autosomal dominant polycystic kidney disease (ADPKD). The cytoplasmic C-terminus of PC-1 contains a coiled-coil domain that mediates an interaction with the PKD2 gene product, Polycystin-2 (PC-2). Here we identify a novel domain in the PC-1 C-terminal tail, a polyproline motif mediating an interaction with Src homology domain 3 (SH3). A screen for interactions using the PC-1 C-terminal tail identified the SH3 domain of nephrocystin-1 (NPHP1) as a potential binding partner of PC-1. NPHP1 is the product of a gene that is mutated in a different form of renal cystic disease, nephronophthisis (NPHP). We show that in vitro pull-down assays and NMR structural studies confirmed the interaction between the PC-1 polyproline motif and the NPHP1 SH3 domain. Furthermore, the two full-length proteins interact through these domains; using a recently generated model system allowing us to track endogenous PC-1, we confirm the interaction between the endogenous proteins. Finally, we show that NPHP1 trafficking to cilia does not require PC-1 and that PC-1 may require NPHP1 to regulate resistance to apoptosis, but not to regulate cell cycle progression. In line with this, we find high levels of apoptosis in renal specimens of NPHP patients. Our data uncover a link between two different ciliopathies, ADPKD and NPHP, supporting the notion that common pathogenetic defects, possibly involving de-regulated apoptosis, underlie renal cyst formation.