Traditional therapeutic interventions against abnormal gene expression in disease states at the level of expressed proteins are becoming increasingly difficult due to poor selectivity, off-target effects and associated toxicity. Upstream catalytic targeting of specific RNA sequences offers an alternative platform for drug discovery to achieve more potent and selective treatment through antisense interference with disease-relevant RNAs. We report a novel class of catalytic biomaterials, comprising amphipathic RNA-cleaving peptides placed between two RNA recognition motifs, here demonstrated to target the TΨC loop and 3'- acceptor stem of tRNA. These unique peptidyl-oligonucleotide 'dual' conjugates (DCs) were created by phosphoramidate or thiol-maleimide conjugation chemistry of a TΨC-targeting oligonucleotide to the N-terminus of the amphipathic peptide sequence, followed by amide coupling of a 3'-acceptor stem-targeting oligonucleotide to the free C-terminal carboxylic acid functionality of the same peptide. Hybridization of the DCs bearing two spatially-separated recognition motifs with the target tRNA placed the peptide adjacent to a single-stranded RNA region and promoted cleavage within the 'action radius' of the catalytic peptide. Up to 100% cleavage of the target tRNA was achieved by the best candidate (i.e. DC6) within 4 h, when conformational flexibility was introduced into the linker regions between the peptide and oligonucleotide components. This study provides the strong position for future development of highly selective RNA-targeting agents that can potentially be used for disease-selective treatment at the level of messenger, micro, and genomic viral RNA.

Determining the conformations accessible to carbohydrate ligands in aqueous solution is important for understanding their biological action. In this work, we evaluate the conformational free-energy surfaces of Lewis oligosaccharides in explicit aqueous solvent using a multidimensional variant of the swarm-enhanced sampling molecular dynamics (msesMD) method; we compare with multi-microsecond unbiased MD simulations, umbrella sampling, and accelerated MD approaches. For the sialyl Lewis A tetrasaccharide, msesMD simulations in aqueous solution predict conformer landscapes in general agreement with the other biased methods and with triplicate unbiased 10 μs trajectories; these simulations find a predominance of closed conformer and a range of low-occupancy open forms. The msesMD simulations also suggest closed-to-open transitions in the tetrasaccharide are facilitated by changes in ring puckering of its GlcNAc residue away from the C form, in line with previous work. For sialyl Lewis X tetrasaccharide, msesMD simulations predict a minor population of an open form in solution corresponding to a rare lectin-bound pose observed crystallographically. Overall, from comparison with biased MD calculations, we find that triplicate 10 μs unbiased MD simulations may not be enough to fully sample glycan conformations in aqueous solution. However, the computational efficiency and intuitive approach of the msesMD method suggest potential for its application in glycomics as a tool for analysis of oligosaccharide conformation.

The conformational flexibility of the glycosaminoglycans (GAGs) is known to be key in their binding and biological function, for example in regulating coagulation and cell growth. In this work, we employ enhanced sampling molecular dynamics simulations to probe the ring conformations of GAG-related monosaccharides, including a range of acetylated and sulfated GAG residues. We first perform unbiased MD simulations of glucose anomers and the epimers glucuronate and iduronate. These calculations indicate that in some cases, an excess of 15 μs is required for adequate sampling of ring pucker due to the high energy barriers between states. However, by applying our recently developed msesMD simulation method (multidimensional swarm-enhanced sampling molecular dynamics), we were able to quantitatively and rapidly reproduce these ring pucker landscapes. From msesMD simulations, the puckering free energy profiles were then compared for 15 further monosaccharides related to GAGs; this includes to our knowledge the first simulation study of sulfation effects on β-GalNAc ring puckering. For the force field employed, we find that in general the calculated pucker free energy profiles for sulfated sugars were similar to the corresponding unsulfated profiles. This accords with recent experimental studies suggesting that variation in ring pucker of sulfated GAG residues is primarily dictated by interactions with surrounding residues rather than by intrinsic conformational preference. As an exception to this, however, we predict that 4-O-sulfation of β-GalNAc leads to reduced ring rigidity, with a significant lowering in energy of the 1C4 ring conformation; this observation may have implications for understanding the structural basis of the biological function of β-GalNAc-containing glycosaminoglycans such as dermatan sulfate.

Key to the fragment optimisation process within drug design is the need to accurately capture the changes in affinity that are associated with a given set of chemical modifications. Due to the weakly binding nature of fragments, this has proven to be a challenging task, despite recent advancements in leveraging experimental and computational methods. In this work, we evaluate the use of Absolute Binding Free Energy (ABFE) calculations in guiding fragment optimisation decisions, retrospectively calculating binding free energies for 59 ligands across 4 fragment elaboration campaigns. We first demonstrate that ABFEs can be used to accurately rank fragment-sized binders with an overall Spearman’s r of 0.89 and a Kendall τ of 0.67, although often deviating from experiment in absolute free energy values with an RMSE of 2.75 kcal/mol. We then also show that in several cases, retrospective fragment optimisation decisions can be supported by the ABFE calculations. Comparing against cheaper endpoint methods, namely Nwat-MM/GBSA, we find that ABFEs offer better ranking power and correlation metrics. Our results indicate that ABFE calculations can usefully guide fragment elaborations to maximise affinity.