small molecule therapeutic

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.

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.

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.

Kinases is a class of enzymes that adds chemicals called phosphates to other molecules, such as sugars or proteins. Protein phosphorylation serves as a critical regulatory mechanism for numerous cellular processes including cell division, metabolism, and signal transduction, with approximately 50% of cellular functions in humans being regulated by kinase activity. In drug discovery, kinases represent a major category of therapeutic targets, and kinase inhibitors constitute an important class of pharmaceuticals that block the activity of specific disease-associated enzymes, particularly in cancer and inflammatory disorders. Small molecule kinase inhibitors represent one of the fastest-growing drug categories, having received U.S. Food and Drug Administration (FDA) approval for both oncological and non-oncological indications. As of September 2023, over 70 FDA-approved small molecule kinase inhibitors are commercially available.

The MCE Kinase Inhibitor Library Mini contains 271 kinase inhibitors primarily targeting protein kinases (VEGFR, EGFR, BTK, CDK, Akt, etc.), lipid kinases (PI3K, PI4K, SK, etc.), and carbohydrate kinases. This collection includes 1-3 highly specific representative compounds per target, optimized for screening of kinase-related drug targets in pharmaceutical research.

Hematopathy, also known as hematopoietic system diseases, are a class of diseases that hematopoietic system has abnormal changes. Common hematopathy include: aplastic anemia, myeloproliferative diseases, thalassemia, leukemia, lymphoma, myeloma and hemophilia, etc. In recent years, treatments for hematopathy have been developed. In particular, the treatment of malignant hematopathy developed from chemotherapy, radiotherapy, bone marrow development to immunotherapy, induced differentiation therapy, cell therapy, gene therapy and hematopoietic stem cell transplantation. Although these therapies have greatly improved the survival rate of patients, there are still problems such as low cure rate and easy recurrence in the treatment of hematopathy. Therefore, it is of great significance to actively search for new hematopathy therapeutic drugs.

MCE designs a unique collection of 4,357 anti-hematopathy small molecules, which is an effective tool for development and research of anti-hematopathy compounds.

Targeted Protein Degradation (TPD) is a novel and promising approach to drug development. It shows great potential for targeting proteins traditionally considered "undruggable" due to the lack of enzymatic function and absence of binding sites by tagging them for degradation or recruiting natural degradation mechanisms.

Molecular glues are a type of small-molecule degraders that primarily induce novel interactions between E3 ubiquitin ligases and target proteins, forming ternary complexes that lead to protein ubiquitination and subsequent proteasomal degradation. Compared with PROTACs, molecular glues generally have lower molecular weights, higher cell permeability, and better drug-like properties. Additionally, the design of molecular glues is relatively simple, without the requirements for complex linkers and ligand optimization. As a result, molecular glues have gradually emerged as a promising therapeutic approach for various diseases.

Multiple types of molecular glues have been reported previously. Analysis of co-crystal complex structures reveals that CRBN-related molecular glues are more versatile. Therefore, MCE researchers select active molecules related to these targets as probes for artificial intelligence (AI) screening.Subsequently, molecular docking technology was used to verify whether the screened molecules retained the key pharmacophore features. Ultimately, we obtained 317 molecular glue analogs, and these compounds serve as powerful tools for the research of molecular glues.

Gastric Cancer (GC) is one of the most common malignant tumors in the world, ranking fourth in mortality rate globally. Because the early symptoms of stomach neoplasm are usually not obvious, are diagnosed with gastric cancer at terminal stage, and the relative survival rate within 5 years is very low. With the further understanding of the molecular characteristics of stomach neoplasm, many therapeutic targets for gastric cancer have been identified, and molecular targeted therapies such as CTLA-4, HER2 and immune checkpoint inhibitors have made rapid progress. Although survival rates for patients with gastric neoplasm have improved over the past few decades, the prognosis is still worrying. Therefore, there is an urgent need for new drugs to treat gastric cancer.

MCE designs a unique collection of 1,181 small molecules with definite or potential anti-gastric cancer activity, which is an important tool for studying the pathological mechanism of stomach neoplasm and developing drugs for stomach neoplasm.