Developing an Updated Strategy for Estimating the Free-Energy Parameters in RNA Duplexes

Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery

INTRODUCTION

Targeting RNAs with small molecules offers an alternative to the conventional protein-targeted drug discovery and can potentially address unmet and emerging medical needs. The recent rise of interest in the strategy has already resulted in large amounts of data on disease associated RNAs, as well as on small molecules that bind to such RNAs. Artificial intelligence (AI) approaches, including machine learning and deep learning, present an opportunity to speed up the discovery of RNA-targeted small molecules by improving decision-making efficiency and quality.

AREAS COVERED

The topics described in this review include the recent applications of AI in the identification of RNA targets, RNA structure determination, screening of chemical compound libraries, and hit-to-lead optimization. The impact and limitations of the recent AI applications are discussed, along with an outlook on the possible applications of next-generation AI tools for the discovery of novel RNA-targeted small molecule drugs.

EXPERT OPINION

Key areas for improvement include developing AI tools for understanding RNA dynamics and RNA - small molecule interactions. High-quality and comprehensive data still need to be generated especially on the biological activity of small molecules that target RNAs.

Nearest-neighbour parametrization of DNA single, double and triple mismatches at low sodium concentration

DNA mismatches, that is, base pairs different from the canonical AT and CG, are involved in numerous biological processes and can be a problem for technological applications such as PCR amplification. The nearest-neighbour (NN) model is the standard approach for predicting melting temperatures and is used in methods of secondary structure predictions and modelling of hybridization kinetics. However, despite its biological and technological importance, existing NN parameters that include DNA mismatches are incomplete, and those available were obtained from a limited set of melting temperature at high sodium concentration. To our knowledge, there is currently no NN set of parameters for up to three mismatches covering all configurations at low sodium concentrations. Here, we are applying the NN model to a large set of 4096 published melting temperatures, covering all combinations of single, double and triple mismatches. Dealing with such a large set of temperature is challenging in several ways, bringing new methodological problems. Here, optimizing a large number of 252 independent parameters has required the development of a new method where we readjust the seed parameters using the definition of the Gibbs free energy. The new parameters predict the training set within 1.1 °C and the validation set to 2.7 °C.

Discovery of RNA-targeted small molecules through the merging of experimental and computational technologies

INTRODUCTION

The field of RNA-targeted small molecules is rapidly evolving, owing to the advances in experimental and computational technologies. With the identification of several bioactive small molecules that target RNA, including the FDA-approved risdiplam, the biopharmaceutical industry is gaining confidence in the field. This review, based on the literature obtained from PubMed, aims to disseminate information about the various technologies developed for targeting RNA with small molecules and propose areas for improvement to develop drugs more efficiently, particularly those linked to diseases with unmet medical needs.

AREAS COVERED

The technologies for the identification of RNA targets, screening of chemical libraries against RNA, assessing the bioactivity and target engagement of the hit compounds, structure determination, and hit-to-lead optimization are reviewed. Along with the description of the technologies, their strengths, limitations, and examples of how they can impact drug discovery are provided.

EXPERT OPINION

Many existing technologies employed for protein targets have been repurposed for use in the discovery of RNA-targeted small molecules. In addition, technologies tailored for RNA targets have been developed. Nevertheless, more improvements are necessary, such as artificial intelligence to dissect important RNA structures and RNA-small-molecule interactions and more powerful chemical probing and structure prediction techniques.