Ligand Optimization by Improving Shape Complementarity at a Hepatitis C Virus RNA Target

Machine learning-augmented molecular dynamics simulations (MD) reveal insights into the disconnect between affinity and activation of ZTP riboswitch ligands

The challenge of targeting RNA with small molecules necessitates a better understanding of RNA-ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand-induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure-informed design, crystallography, and machine learning-augmented all-atom molecular dynamics simulations (MD) we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the ZTP riboswitch, a ligand-binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on-rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Assessment of Nucleobase Protomeric and Tautomeric States in Nucleic Acid Structures for Interaction Analysis and Structure-Based Ligand Design

With increasing interest in RNA as a therapeutic and a potential target, the role of RNA structures has become more important. Even slight changes in nucleobases, such as modifications or protomeric and tautomeric states, can have a large impact on RNA structure and function, while local environments in turn affect protonation and tautomerization. In this work, the application of empirical tools for pKa and tautomer prediction for RNA modifications was elucidated and compared with ab initio quantum mechanics (QM) methods and expanded toward macromolecular RNA structures, where QM is no longer feasible. In this regard, the Protonate3D functionality within the molecular operating environment (MOE) was expanded for nucleobase protomer and tautomer predictions and applied to reported examples of altered protonation states depending on the local environment. Overall, observations of nonstandard protomers and tautomers were well reproduced, including structural C+G:C(A) and A+GG motifs, several mismatches, and protonation of adenosine or cytidine as the general acid in nucleolytic ribozymes. Special cases, such as cobalt hexamine-soaked complexes or the deprotonation of guanosine as the general base in nucleolytic ribozymes, proved to be challenging. The collected set of examples shall serve as a starting point for the development of further RNA protonation prediction tools, while the presented Protonate3D implementation already delivers reasonable protonation predictions for RNA and DNA macromolecules. For cases where higher accuracy is needed, like following catalytic pathways of ribozymes, incorporation of QM-based methods can build upon the Protonate3D-generated starting structures. Likewise, this protonation prediction can be used for structure-based RNA-ligand design approaches.

Structure-based virtual screening of unbiased and RNA-focused libraries to identify new ligands for the HCV IRES model system

Targeting RNA including viral RNAs with small molecules is an emerging field. The hepatitis C virus internal ribosome entry site (HCV IRES) is a potential target for translation inhibitor development to raise drug resistance mutation preparedness. Using RNA-focused and unbiased molecule libraries, a structure-based virtual screening (VS) by molecular docking and pharmacophore analysis was performed against the HCV IRES subdomain IIa. VS hits were validated by a microscale thermophoresis (MST) binding assay and a Förster resonance energy transfer (FRET) assay elucidating ligand-induced conformational changes. Ten hit molecules were identified with potencies in the high to medium micromolar range proving the suitability of structure-based virtual screenings against RNA-targets. Hit compounds from a 2-guanidino-quinazoline series, like the strongest binder, compound 8b with an EC50 of 61 μM, show low molecular weight, moderate lipophilicity and reduced basicity compared to previously reported IRES ligands. Therefore, it can be considered as a potential starting point for further optimization by chemical derivatization.

RNA drug discovery: Conformational restriction enhances specific modulation of the T-box riboswitch function

Antibacterial drug resistance is a global health concern that requires multiple solution approaches including development of new antibacterial compounds acting at novel targets. Targeting regulatory RNA is an emerging area of drug discovery. The T-box riboswitch is a regulatory RNA mechanism that controls gene expression in Gram-positive bacteria and is an exceptional, novel target for antibacterial drug design. We report the design, synthesis and activity of a series of conformationally restricted oxazolidinone-triazole compounds targeting the highly conserved antiterminator RNA element of the T-box riboswitch. Computational binding energies correlated with experimentally-derived K_d values indicating the predictive capabilities for docking studies within this series of compounds. The conformationally restricted compounds specifically inhibited T-box riboswitch function and not overall transcription. Complex disruption, computational docking and RNA binding specificity data indicate that inhibition may result from ligand binding to an allosteric site. These results highlight the importance of both ligand affinity and RNA conformational outcome for targeted RNA drug design.

Synthesis and characterization of new heterocycles related to aryl[e][1,3]diazepinediones. rearrangement to 2,4-diamino-1,3,5-triazine derivatives

Divergence-oriented synthesis of new heterocycles relevant for medicinal chemistry.

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

Since the development of the first docking program in 1982, the use of docking-based in silico screening for potentially bioactive molecule discovery has become a common strategy in academia and pharmaceutical industry. Up until recently, application of docking programs has largely focused on drugs binding to proteins. However, with the discovery of promising drug targets in nucleic acids, including RNA riboswitches, DNA G-quadruplexes, and extended repeats in RNA, there has been greater interests in developing drugs for nucleic acids. However, due to major biochemical and physical differences in charges, binding pockets, and solvation, existing docking programs, developed for proteins, face difficulties when adopted directly for nucleic acids. In this review, we cover the current field of in silico docking to nucleic acids, available programs, as well as challenges faced in the field.

Discovery of Small Molecule Ligands for MALAT1 by Tuning an RNA-Binding Scaffold

Structural studies of the 3'-end of the oncogenic long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) confirmed a unique triple-helix structure. This structure enables accumulation of the transcript, and high levels of MALAT1 are found in several cancers. Here, we synthesize a small molecule library based on an RNA-binding scaffold, diphenylfuran (DPF), screen it against a variety of nucleic acid constructs, and demonstrate for the first time that the MALAT1 triple helix can be selectively targeted with small molecules. Computational analysis revealed a trend between subunit positioning and composition on DPF shape and intramolecular interactions, which in turn generally correlated with selectivity and binding strengths. This work thus provides design strategies toward chemical probe development for the MALAT1 triple helix and suggests that comprehensive analyses of RNA-focused libraries can generate insights into selective RNA recognition.

Synthesis of Benzo[4,5]imidazo[1,2-c]pyrimidin-1-amines and Their Analogs via Copper-Catalyzed C-N Coupling and Cyclization

2-(2-Bromovinyl)benzimidazoles and 2-(2-bromophenyl)benzimidazoles react with cyanamide by microwave irradiation in dimethylformamide in the presence of a catalytic amount of CuI along with a base to give the corresponding benzo[4,5]imidazo[1,2-c]pyrimidin-1-amines and benzo[4,5]imidazo[1,2-c]quinazolin-6-amines, respectively, in moderate to good yields. 2-(2-Bromophenyl)indoles also react with cyanamide under similar conditions to afford indolo[1,2-c]quinazolin-6-amines. The reaction pathway seems to proceed via a sequence such as intermolecular C-N coupling, C-N formative cyclization, and tautomerization.

A Macrocyclic Peptide Ligand Binds the Oncogenic MicroRNA-21 Precursor and Suppresses Dicer Processing

MicroRNAs (miRNAs) help orchestrate cellular growth and survival through post-transcriptional mechanisms. The dysregulation of miRNA biogenesis can lead to cellular growth defects and chemotherapeutic resistance and plays a direct role in the development of many chronic diseases. Among these RNAs, miR-21 is consistently overexpressed in most human cancers, leading to the down-regulation of key tumor-suppressing and pro-apoptotic factors, suggesting that inhibition of miR-21 biogenesis could reverse these negative effects. However, targeted inhibition of miR-21 using small molecules has had limited success. To overcome difficulties in targeting RNA secondary structure with small molecules, we developed a class of cyclic β-hairpin peptidomimetics which bind to RNA stem-loop structures, such as miRNA precursors, with potent affinity and specificity. We screened an existing cyclic peptide library and discovered a lead structure which binds to pre-miR21 with K_D = 200 nM and prefers it over other pre-miRNAs. The NMR structure of the complex shows that the peptide recognizes the Dicer cleavage site and alters processing of the precursor to the mature miRNA in vitro and in cultured cells. The structure provides a rationale for the peptide binding activity and clear guidance for further improvements in affinity and targeting.

Functional RNA structures throughout the Hepatitis C Virus genome

The single-stranded Hepatitis C Virus (HCV) genome adopts a set of elaborate RNA structures that are involved in every stage of the viral lifecycle. Recent advances in chemical probing, sequencing, and structural biology have facilitated analysis of RNA folding on a genome-wide scale, revealing novel structures and networks of interactions. These studies have underscored the active role played by RNA in every function of HCV and they open the door to new types of RNA-targeted therapeutics.