Agent

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.

Currently,the incidence and mortality rates of clinical fungal infections remain high. Existing antifungal drugs are limited in variety and associated with numerous adverse effects, creating an urgent demand for the development of novel antifungal agents. Antifungal compound libraries can support the screening and development of new antifungal drugs.

The mechanisms of action of antifungal drugs cover key processes such as fungal cell membrane synthesis, cell wall synthesis, and cell division. They exert fungicidal or fungistatic effects by specifically targeting different molecular pathways. This library includes a variety of core analogs of antifungal drugs, making it adaptable to antifungal research in diverse scenarios. It can be used for the high-throughput screening of novel antifungal drug candidates, enabling the rapid identification of compounds with potential antifungal activity and facilitating the elucidation of drug-target interactions and resistance mechanisms. Additionally, it supports the screening of compounds and combinations that reverse drug resistance, thereby uncovering the novel antifungal potential of existing compounds.

The library comprises 8350 compounds with a well-defined screening strategy. The core sources of the compounds include analogs of known antifungal active moleculeswith a similarity score of ≥ 0.6 MCE has collected more than 500 antifungal molecules.All screened compounds conform to lead-like physicochemical properties, exhibiting both structural diversity and drug-like characteristics, and providing valuable support for the research and development of novel antifungal drugs.

The rising prevalence of multidrug-resistant and extensively drug-resistant bacteria, combined with emerging resistance mechanisms and the limitations of existing antibacterial drugs, creates an urgent need for novel antibacterial agents. Antibacterial compound libraries serve as key tools to support antibacterial drug screening and development.

This library features structurally diverse compounds, including small-molecule scaffolds and natural product derivatives, and exhibits diverse antibacterial mechanisms of action. For example, these compounds exert antibacterial effects by disrupting bacterial cell structures, interfering with bacterial metabolic processes, and inhibiting nucleic acid synthesis. The derivation of scaffold structures enhances their activity against drug-resistant bacteria and their selectivity against different types of bacteria. This library can be used for the high-throughput screening of novel antibacterial drug candidates and the identification of potent compounds against drug-resistant and multidrug-resistant bacteria. Additionally, it provides a reference for compound structural modification, enabling further in-depth research on the structure-activity relationships(SARs) of antibacterial drugs. It can also be applied to the exploration of bacterial resistance mechanisms and reversal strategies, as well as the discovery of antibacterial molecules that inhibit efflux pumps and restore drug susceptibility.

The library contains 10855 structurally diverse drug-like compounds. Its core compound sources include analogs of known antifungal active moleculeswith a similarity score of ≥ 0.6. MCE has collected more than 1900 antibacterial molecules. All screened compounds conform to lead-like physicochemical properties, providing valuable support for the research and development of novel antibacterial drugs.

Hepatitis C virus (HCV) is a hepatotropic enveloped positive- strand RNA virus (family Flaviviridae) that infects the parenchymal cells of the liver. HCV infection is a significant public health burden. Globally, an estimated 71 million people have chronic hepatitis C virus infection. A significant number of those who are chronically infected will develop cirrhosis or liver cancer. To date, there is no vaccine against HCV, and combination pegylated alpha interferon (pIFN-) and ribavirin, the main standard-of-care treatment for HCV, is effective in only a subset of patients and is associated with a wide spectrum of toxic side effects and complications. More recently, new therapeutic approaches that target essential components of the HCV life cycle have been developed, including direct-acting antiviral (DAA) that specifically block a viral enzyme or functional protein and host-targeted agents (HTA) that block interactions between host proteins and viral components that are essential to the viral life cycle. However, the genetic diversity of HCV viruses and the stage of liver disease (i.e., cirrhosis) are revealing themselves as obstacles for effective, pan-genotypic treatments. There still exists a need for the discovery and development of new HCV inhibitors. In particular, since the future of HCV therapy will likely consist of a cocktail approach using multiple inhibitors that target different steps of infection, new antivirals targeting all steps of the viral infection cycle.

MCE offers a unique collection of 394 compounds with identified and potential anti-HCV activity. MCE Anti- Hepatitis C Virus Compound Library is a useful tool for discovery new anti-HCV drugs and other anti-infection research.