Modeling of ribonucleic acid–ligand interactions

Abstract

Computational methods play a pivotal role in the early stages of small molecule drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the past half century in medicinal chemistry, almost all the attention has been directed to protein-ligand binding and computational tools were created with such targets in mind. However, with growing discoveries of functional RNAs and their possible applications, RNA macromolecules have gained considerable attention as possible drug targets. This flow of discovery was followed by adapting existing computational tools for RNA applications as well as active development of new RNA-tailored methods. However, due to the different nature of RNA, especially its tendency to use morphological plasticity (conformational change in ligand binding) this remains a challenging task. The evolution of 'protein-based' drug discovery and related computational methods offers some clues on possible future directions and developments in modeling RNA interactions with small molecule ligands. The function of many RNAs is modulated by small ligand molecules. These can be naturally occurring molecules as well as fully synthetic compounds. One of the most-studied and well-validated targets for small molecules is ribosomal RNA (rRNA), which forms the active site of the ribosome. This large macromolecular complex consists of RNA and proteins, and is responsible for protein synthesis. Blockage of ribosome function disrupts protein synthesis and leads to cell death. That is why the bacterial ribosome is a good target for many groups of small molecule antibiotics, including macrolides, aminoglycosides, tetracyclines, or oxazolidines, among others.2 Riboswitches represent another class of RNA molecules that can be modulated upon small molecule binding. They typically occur within the protein-noncoding parts of messenger RNA (mRNA) and regulate the translation of the protein-coding parts. Riboswitches can directly form complexes with small molecules and, in this way, regulate gene function without the presence of protein cofactors. Among natural ligands recognized by riboswitches are metabolites, divalent cations, and second messengers. [3][4][5] As riboswitches are common in bacteria and rarely occur in eukaryotes, they are emerging as a potential target for new and selective antibacterial drugs. Viral RNAs can also be † The authors wish it to be known that F.S. and E.I.C. contributed equally and should be regarded as Joint First Authors. 425targets for small molecule inhibitors. Examples include HIV-1 trans-activation response (TAR) RNA, for which small molecules 6-8 and peptidomimetics 9,10 that disrupt its interactions with the Tat protein have been described. Among other druggable viral RNAs are the Hepatitis C virus (HCV) internal ribosome entry site [11][12][13] and the Hepatitis D virus (HDV) ribozyme.14 In recent years, considerable attention has centered on micro RNA (miRNA) as a possible drug target in many diseases including inflamma...

Challenges and current status of computational methods for docking small molecules to nucleic acids

“…However, docking to nucleic acids is comparatively underdeveloped. Generally, protein-ligand docking programs could be adapted to RNA-ligand docking as RNA-ligand and protein-ligand macromolecular complexes follow similar physicochemical binding principles [32,33]. However, many proteins contain a well-defined, generally hydrophobic binding site.…”

Structure-based molecular modeling in SAR analysis and lead optimization

“… [66] Presents an overview of the evolution of structure-based drug discovery techniques in the study of ligand-target recognition phenomenon, going from static molecular docking toward enhanced MD strategies. [67] Summarizes progress in the prediction of RNA–ligand interactions, available methods for calculating the mode of binding for various small RNA molecules, the range of SFs for ligands ranking, accommodating RNA flexibility, and example studies. [68] Provides an overview of the state of the art of experimental and computational approaches for investigating drug metabolism.…”

Structure-Based Discovery of Small Molecules Binding to RNA

“…Therefore, in general the methods developed for proteins can also be applied for RNA [20,27,[48][49][50]. However, there are several challenges which have to be considered when transferring the methods.…”