Anima’s mRNA Lightning platform has generated many novel chemical entities that modulate mRNA translation, further contributing to the expanse of the RNA-targeting small molecule field. Anima's phenotypic screening approach systematically evaluates the impact of small molecules on mRNA translation into proteins. Combined with AI-driven MOA elucidation, Anima has identified and validated compounds that are binding to proteins which regulate mRNA translation, offering an opportunity for both tissue-selective and target-specific modulation. Anima’s lead programs in fibrosis and oncology have demonstrated efficacy in animal and patient-derived models and are advancing toward preclinical development.

Utilizing small molecules to modulate splicing has emerged as a successful therapeutic approach to regulating protein expression. Here, three diseases where small molecule splicing modulators can be utilized are described: spinal muscular atrophy, familial dysautonomia, and Huntington’s disease. For each of these indications, I will discuss the correlation between pharmaceutical properties and pharmacokinetics, pharmacokinetics and pharmacodynamics, and the correlation between pharmacodynamics and efficacy.

We describe the lead optimization of a series of HTT splicing modulators that are structurally distinct from those currently in the clinic and highlight the in vitro and in vivo PK/PD profiles of a lead compound.

Antisense oligonucleotides (ASOs) have demonstrated the ability to functionally reduce the expression of cognate RNAs in cells. However, the therapeutic utility of these molecules has been limited by their tissue distribution and mode of administration. Small molecules present a superior modality that can broadly target tissues and cross the blood brain barrier by oral administration. In this presentation, we will discuss our efforts to selectively target undruggable RNAs with small molecules that induce RNA degradation at meaningful therapeutic concentrations. This presentation will explore the molecular basis for these interactions and examine the functional consequences of target suppression in cellular models of disease. 

RNA offers a broad array of folded, three-dimensional structures that mediate their functional roles. Our drug discovery platform at Arrakis Therapeutics is directed at the intervention of those functions to therapeutic benefit using drug-like small molecules that bind folded RNA structures. This presentation will touch on some of the unique challenges in building a broad and robust RNA-targeted small molecule platform and provide early data on specific RNA targets.

RNA-binding proteins (RBPs) are paramount effectors of gene expression, and their malfunction underlies the origin of many diseases. However, therapeutically targeting RBPs with small molecules has proven challenging due to highly polar orthosteric ribonucleic interactions and a lack of lipophilic cavities indicative of druggability. We present an integrated screening campaign integrating fragment-based differentiable design with molecular dynamics to discover a cryptic site enabling the discovery of a novel non-functional RBP binder. We demonstrate the physics-driven optimization of this hit molecule to induce the proximity of an E3 ligase, facilitating the proteosome-specific degradation of an RBP and restoring a tumor-suppressive miRNA.

High-throughput screening of RNA-targeting small molecules remains a challenge due to the lack of RNA-focused small molecule libraries. We applied AI-assisted technology to select a suitable small molecule library and carried out compound screening using ALIS. The increased hit rate was significantly higher compared to our previous campaigns, which demonstrates that AI-driven compound selection strategies can accelerate RNA-targeted small molecule drug discovery.

Atomic AI has developed PARSE, the Platform for AI-driven RNA Structure Exploration, which can locate 3D structures at unprecedented speed and accuracy in disease-relevant RNA targets. PARSE builds on our work featured on the cover of Science, and involves a tight integration of high-throughput wet-lab experiments and cutting-edge artificial intelligence capabilities. Through this data-driven approach, Atomic AI is enabling and pursuing drug discovery against undruggable targets.

We present an approach that utilizes clickable probes to directly quantify protein-RNA interactions on proteins. Our method facilitated global detection of RNA-interaction sites on RBPs that mediate recognition of coding and noncoding RNA. We performed functional profiling of known RNA-binding domains and discovery of RNA binding activity on proteins without prior RBP annotation. In summary, we present a chemoproteomic method for global quantification of protein-RNA binding activity in living cells.

We have discovered compounds that covalently engage the RNA-binding protein NONO. These NONO ligands suppress mRNA of several cancer-relevant genes and impair cancer cell proliferation. Surprisingly, these effects were not observed in cells genetically disrupted for NONO, which were instead resistant to NONO ligands. The ligands promote NONO accumulation in nuclear foci and stabilize NONO-RNA interactions, supporting a trapping mechanism that prevents compensatory action of paralog proteins PSPC1 and SFPQ.  

An estimated 85% of the ~3 billion base pairs in the human genome is transcribed into RNA, but only ~1.5% of these code for proteins. While the chemical properties of protein binders are increasingly understood and interrogated, the field of RNA-targeted drugs is relatively new and the properties of small molecules that drive specific and selective targeting of RNA, and associated assays, are yet to be developed. At Serna Bio [previously Ladder Therapeutics] we are using an AI enabled, data-first approach to write the rules that define RNA-small molecule interactions.

Targeting of RNA by small molecule drugs requires modification of RNA target function or stability induced by ligand binding. Surrogate approaches that assess target performance upon structure modification in the context of biological function, and screening assays that couple ligand binding and structure modification are powerful tools to assess feasibility of small molecule targeting for structured RNA domains. I will discuss examples from targeting structured domains in human mRNA and viruses including HCV, Zika virus, and SARS CoV-2. 

RNA structures play essential roles in directing RNA function and are key therapeutic targets. I will discuss our ongoing efforts to develop single-molecule chemical probing technologies to measure complex RNA and RNA-protein structures at high-resolution in living cells. I will further describe new RNA structural mechanisms revealed by these technologies, and our preliminary efforts to target RNA structures to control gene expression.