Translation

The RNA-targeted bioactive compound library is a high-quality collection of small molecules specifically designed and curated to target RNA structures and functions. It is widely applied in cutting-edge drug discovery and life science research. Unlike traditional strategies that focus on protein targets, RNA-targeted compounds can directly modulate various functional RNA molecules by influencing their splicing, translation, stability, or structural conformation, thereby enabling precise intervention in key biological processes. In the field of drug development, these compounds provide a novel approach to addressing previously “undruggable” targets and have demonstrated significant potential in areas such as oncology, antiviral therapies, and neurodegenerative diseases. For example, by targeting disease-associated RNA structural domains or regulating the aberrant expression of non-coding RNAs, these compounds can effectively inhibit disease progression or restore normal cellular function. In mechanistic studies, RNA-targeted compounds serve as valuable chemical biology tools to elucidate the roles of RNA in gene expression regulation, cellular signaling pathways, and disease development.

The MCE RNA-targeted bioactive compound library contains 858 compounds, sourced from databases such as TargetRX Atlas and R-BIND. The library features excellent structural diversity and biological activity, making it suitable for high-throughput screening (HTS), target validation, phenotypic screening, and lead compound discovery. It represents a valuable resource for RNA-related research and innovative drug development.

Macrocyclic compounds (≥12-atom cyclic small molecules/peptides) have unique physicochemical properties. They form preorganized conformations with high binding affinity/selectivity, target traditional small-molecule-inaccessible proteins, and bridge small-molecule drugs and biological agents. As key protein phosphorylation enzymes, kinases are linked to tumors, COPD, etc., and are critical therapeutic targets. Traditional small-molecule kinase inhibitors lack selectivity, causing off-target toxicity, low bioavailability, and acquired resistance. Macrocycles’ semi-rigid structure restricts conformations, boosts binding selectivity, optimizes pharmacokinetics, and makes macrocyclization a core kinase inhibitor optimization strategy.

Thousands of bioactive macrocycles were curated from ChEMBL. Via Transformer, macrocyclization was converted into a chemical language translation task, enabling end-to-end macrocycle generation from linear precursors with simplified inputs. Macformer achieves efficient, automated linear molecule macrocyclization via deep learning; generated macrocycles have diversity, novelty, biocompatibility, and cover broader chemical space.

MCE collected thousands of marketed/clinical kinase inhibitors, using their fragments for macrocyclization to generate derivatives. After evaluating synthetic accessibility and physicochemical properties, a million-scale virtual macrocyclic library was built for kinase-related virtual and AI-driven screening.

The PI3K/Akt/mTOR pathway controls many cellular processes that are important for the formation and progression of cancer, including apoptosis, transcription, translation, metabolism, angiogenesis, and cell cycle progression. Every major node of this signaling network is activated in a wide range of human tumors. Mechanisms for the pathway activation include activation of receptor tyrosine kinases (RTKs) upstream of PI3K, mutation or amplification of PIK3CA encoding p110α catalytic subunit of PI3K, mutation or loss of PTEN tumor suppressor gene, and mutation or amplification of Akt1. Once the pathway is activated, signaling through Akt can stimulate a series of substrates including mTOR which is involved in protein synthesis. Thus, inhibition of this pathway is an attractive concept for cancer prevention and/or therapy. Currently some mTOR inhibitors are approved for several indications, and there are several novel PI3K/Akt/mTOR inhibitors in clinical trials.

MCE owns a unique collection of 1,149 compounds that can be used for PI3K/Akt/mTOR pathway research. PI3K/Akt/mTOR Compound Library also acts as a useful tool for anti-cancer drug discovery.

RNA is crucial for the regulation of numerous cellular processes and functions. With the in-depth study of disease mechanisms, processes such as RNA expression, splicing, translation, and stability regulation have become new targets for disease intervention. RNA has provided new therapeutic modalities for metabolic diseases, genetic disorders, and cancer patients, resulting in several innovative drugs.

MCE R&D team collected small molecules targeting RNA from the PDB, R-BIND, ROBIN, and internal database as the positive dataset, and non-targeting RNA small molecules from ROBIN as the negative dataset. Based on the GeminiMol pre-trained model, we encoded the molecules and calculated over 1700 molecular descriptors using Mordred as inputs for the model. Subsequently, we employed 13 deep learning models to learn from the data. All of which yielded good training results, with AUROCs greater than 0.75. Ultimately, we selected the Finetune model to screen HY-L901P, which exhibited the best classification performance, achieving an AUROC of 0.82 and a prediction accuracy of 0.76. We then applied filtering based on StaR rules (with at least two of the following properties: cLogP ≥ 1.5, Molar Refractivity ≥ 4, Relative Polar Surface Area ≤ 0.3) to obtain a library containing approximately 5,000 small molecule compounds targeting RNA. This library serves as a valuable tool for screening small molecules that interact with RNA.