driven

A collection of over 2 million screening compounds from manufacturers such as VitasM, Specs, Otava and more, available at competitive prices, suitable for virtual screening and AI-driven screening applications.

A collection of over 10 million screening compounds from 18+ manufacturers. The data has been cleaned, suitable for virtual screening and AI screening.

Owing to the high conservation of orthosteric sites, conventional orthosteric drugs frequently suffer from poor subtype selectivity, off-target toxicity, and drug resistance, severely restricting their clinical application. In contrast, allosteric sites feature low conservation, high hydrophobicity, weak polarity, confined spatial geometry, and dynamic cryptic properties. These characteristics endow allosteric modulators with distinct advantages including high selectivity, functional tunability, and improved safety, making allosteric therapy a key direction in modern drug discovery.

MCE has curated nearly 1,000 structurally disclosed clinical-stage allosteric modulators. By analyzing allosteric protein–ligand complex structures from the PDB database, we extracted core pharmacophores and privileged scaffolds. Adopting a rational design strategy of “scaffold derivation + allosteric physicochemical filtering”, we performed secondary screening on the derived compounds strictly following the optimal physicochemical principles for allosteric binding based on universal allosteric pocket properties: molecular weight 300–500 Da, HBD ≤ 3, HBA = 3–8, PSA = 70–120 Ų, rotatable bonds ≤ 6, highly rigid scaffolds, cLogP = 1.0–3.8, and no strongly ionizable groups. The selected compounds exhibit high rigidity and shape complementarity, making them well-suited for targeting shallow, dynamic, and hydrophobic-dominated allosteric pockets.

This allosteric modulator library contains 4,315 structurally diverse, lead-like compounds dedicated to allosteric drug development, allosteric site targeting, and allosteric modulator screening. It is suitable for kinases, GPCRs, and other important drug targets. All compounds are analogs of clinical-stage allosteric modulators with a similarity score > 0.6, combining excellent druggability and allosteric binding potential. It provides a highly efficient tool for early-stage allosteric drug discovery.

In contrast to the high conservation of conventional orthosteric sites, allosteric sites possess structural characteristics of low conservation, high hydrophobicity, weak polarity, confined spatial geometry, and dynamic cryptic properties. There is a significant difference between their core structures and orthosteric pockets — allosteric pockets are mostly dynamic grooves formed by protein conformational changes, subunit interface clefts, or shallow depressions, rather than the rigid "keyhole" structure of orthosteric sites. With looser spatial constraints, allosteric sites have the advantages of high selectivity and low off-target risk, and have become an important direction in new drug discovery.

Based on the dynamic, hydrophobic, and narrow-long spatial characteristics of allosteric pockets, MCE has performed targeted modification and screening of fragments. The screening criteria strictly conform to the requirements of allosteric binding: molecular weight is controlled at 120–280 Da (to meet the core needs of small molecules in fragment libraries and high derivatization), hydrogen bond donors (HBD ≤ 2), hydrogen bond acceptors (HBA ≤ 3), polar surface area (PSA = 30–80 Ų), rotatable bonds (≤ 2), moderate hydrophobicity (cLogP = 1–3.5), no strongly ionizable groups, and both appropriate rigidity and conformational flexibility to adapt to the dynamic changes of the pocket. Meanwhile, combined with the results of principal moment of inertia (PMI) analysis, fragments with high 3D diversity were obtained. Such fragments have good shape complementarity with allosteric pockets, ensuring that the fragments can smoothly enter the allosteric pockets and form stable binding, while providing room for subsequent optimization and derivation.

This library contains 1,800 structurally diverse fragment molecules with excellent drug-like properties, suitable for allosteric drug development and the design and optimization of allosteric sites. It combines the

Owing to the widespread transmission and frequent mutation of viral diseases, as well as the continuous emergence of new viruses and drug-resistant strains, antiviral drug development is facing increasingly stringent requirements. Antiviral compound libraries serve as important tools for drug screening, mechanism research and development, enabling the discovery and investigation of various antiviral drugs.

These compounds act through diverse antiviral mechanisms, targeting key steps in viral replication, assembly and invasion. They exert antiviral effects by inhibiting viral nucleic acid synthesis, blocking viral protein processing, and preventing viral binding to host cells. This library covers various types of antiviral compounds, including nucleosides, non-nucleosides, protease inhibitors and integrase inhibitors. It supports research on influenza virus, herpes virus, hepatitis virus, emerging respiratory viruses and other pathogens, and enables high-throughput screening of novel antiviral candidates to rapidly identify potential active compounds against diverse viruses. It also facilitates mechanistic studies to elucidate drug-target interactions and viral resistance mechanisms, and supports the screening of effective compounds against mutant strains for research on viral variation and drug resistance.

This antiviral library consists of 6,804 compounds with lead-like physicochemical properties. The core sources of the compounds include analogs of known antiviral molecues with a similarity score ≥ 0.6. MCE has collected more than 1450 antiviral molecules. As a small-molecule collection with both activity potential and structural modifiability, it provides strong support for antiviral drug research and development.

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.

Cysteine proteases (CPs), a key enzyme family regulating physiological metabolism and mediating pathological processes (such as abnormal bone resorption, tumour invasion, and pathogen infection), represent a core therapeutic target for developing specific inhibitors in disease intervention. Currently reported CP inhibitors primarily achieve their inhibitory function by precisely binding to CP active pockets (e.g., S1-S4 non-primed regions or S1'-S2' primed regions) and forming covalent/non-covalent interactions with the active site cysteine residues, providing clear structural references for the development of novel inhibitors.

This compound library, designed based on the core strategy of "similarity-based known active structures", contains over 200 cysteine protease inhibitors. Leveraging AI-driven molecular screening technology, it retains the critical pharmacological and shape features of reported CP inhibitors, serving as a specialized tool for efficiently discovering novel cysteine protease inhibitors.

Sulfonyl fluoride (-SO₂F) overcomes the bottleneck of target selectivity in traditional covalent warheads through its unique chemical and biological properties, which rely heavily on cysteine (Cys) residues. Featuring high stability and tunable electrophilicity under physiological conditions, it can target a wide range of nucleophilic residues including lysine (Lys), tyrosine (Tyr), serine (Ser), and histidine (His). It offers the advantages of a broader druggable space, lower off-target risks, and long-lasting efficacy, with numerous reported cases in the research of covalent inhibitors, Molecular glue, PROTACs, and chemical biology probe development.

MCE constructs a highly diverse sulfonyl fluoride fragment library based on the reactivity, stability and physiological compatibility of sulfonyl fluoride. The library contains 1000 efficiently synthesized and stable sulfonyl fluoride fragments, which ensure precise reactivity of the warhead and retain sufficient derivatization space for subsequent optimization. Combined with the modular strategy of SuFEx click chemistry, it enables versatile modification of compounds and functionalization of complex molecules, improves the efficiency of structural optimization and rapidly expands druggability, making it suitable for high-throughput probe and custom covalent library construction. It provides an efficient research tool for the development of broad-spectrum covalent inhibitors targeting Lys/Tyr/Ser/His, covalent PROTACs for E3 ligases and chemical biology probe development, meeting the requirements of modern drug research for high throughput, high success rate and high derivatization potential.

This library contains 1,162 sulfonyl fluoride fragments with high structural diversity, favorable drug-like properties and tunable electrophilicity. It is well suited for precise targeting of non-Cys residues and meets the criteria of simple structure and high derivatization potential. It effectively improves

CRBN, namely cereblon, is the substrate recognition subunit of the E3 ubiquitin ligase complex in the ubiquitin-proteasome system. A CRBN ligand library refers to a collection of numerous fragments that can specifically bind to the CRBN protein.

These ligands are mostly designed based on validated CRBN-binding warheads and modified through AI-driven molecular generation optimization systems. They not only include classic lenalidomide-derived structures but also cover novel non-lenalidomide scaffolds. After drug-likeness filtering, these ligands exhibit structural diversity and favorable druggable properties. They can be further optimized and modified to facilitate the development of novel molecular glue degraders, accelerate the discovery of molecular glues that induce interactions between CRBN and new substrate proteins, and enable the exploration of novel CRBN substrates for identifying previously unknown CRBN-binding proteins.

MCE compiles 125 fragments that can specifically bind to the CRBN protein, with molecular weights ranging from 200 to 500. Compounds developed based on the library ligands target multiple disease targets such as cancer and autoimmune diseases, further advancing the development of Molecular Glues and PROTACs therapeutic agents.

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.