Drug-like

Natural products are small molecular compounds that occur in nature and come from any organism, including primary and secondary metabolites. Natural products have potential biological activity and can be used as lead compounds for drug discovery. Nature has been a source of medicines for thousands of years, and a large number of drugs have been isolated from nature, many based on their use in traditional medicine. With the development of compound targets, there is an increasing need to screen for compound diversity. Through ongoing research into natural biodiversity, much of which remains to be exploited, natural products will play a key role in meeting this demand. The Lipinski rule of 5 is used to describe the drug-like properties of a molecule, molecules that adhere to the rule of 5 have higher drug potential. Based on MCE natural product library, MCE selects the molecules that obey the rule of 5, which makes the efficiency of drug screening higher.

MCE designs a unique collection of 2,815 RO5 drug-like natural products, which is an important tool for drug discovery.

MCE 18 stands for Medicinal Chemistry Evolution 2018. This metric was established based on structural data of 28,161 patented lead molecules, 1,370 marketed innovative drugs, and nearly 30,000 investigational candidates from preclinical to Phase III stages across 23 major global pharmaceutical companies from 1950 to 2018. After scaffold clustering analysis, a scoring model was constructed by integrating five three dimensional scaffold characteristics, including aromatic rings (AR), non aromatic heterocycles (NAR), chiral centers (CHIRAL), spirocycles (SPIRO), and the sp³ carbon ratio in cyclic and acyclic moieties, enabling quantitative assessment of molecular scaffold novelty and three dimensional complexity.

According to the score distribution of patented molecules, the top 25% of the original patent dataset was defined as the high novelty region. MCE 18 high scoring compounds selected based on this criterion can effectively avoid scaffold patent conflicts and intellectual property risks from the source. Molecules in this range typically feature a high sp³ carbon ratio, abundant chiral centers, spirocycles, and fused heterocycles with prominent three dimensional conformations. Their spatial properties allow precise matching to complex non traditional undruggable target pockets such as PPI interfaces and allosteric sites, making them ideal structural types for early stage screening of First in class drugs.

MCE‑18 Novelty Focused drug‑Like library strictly selects molecules from the aforementioned high scoring range, containing more than 10,000 premium drug like molecules with highly diverse scaffolds and rich 3D diversity. It can be used for high throughput screening of well established targets such as kinases, GPCRs, and proteases, and is especially suitable for hit identification in allosteric modulation, protein–protein interactions, and various undruggable orphan targets, fully supporting early stage drug discovery for cutting edge innovat

MCE-18 stands for Medicinal Chemistry Evolution 2018, which was first published in Journal of Medicinal Chemistry in 2019 for assessing molecular novelty and three-dimensional complexity. Developed based on Clarivate global pharmaceutical patent database, this descriptor was constructed via big-data analysis covering 28,161 patented lead compounds, 1,370 approved drugs and nearly 30,000 preclinical-to-phase III drug candidates from 23 top pharmaceutical companies worldwide between 1950 and 2018, followed by structural clustering and removal of redundant outdated scaffolds for data denoising. Its scoring system integrates five core structural features including aromatic ring (AR), aliphatic heterocycle (NAR), chiral center (CHIRAL), spiro atom (SPIRO), cyclic and acyclic sp³ carbon ratio together with a quadratic topological correction factor. Breaking the limitations of the single Fsp³ parameter, MCE-18 effectively distinguishes conventional flat aromatic scaffolds from modern 3D-enriched novel chemotypes, overcoming typical drawbacks of traditional compound libraries such as scaffold redundancy, low screening hit rates and poor compatibility with allosteric and PPI-related difficult targets.

This library contains over 37,000 structurally diverse compounds with favorable overall drug-likeness, suitable for high-throughput screening against canonical targets including kinases, GPCRs and proteases as well as challenging allosteric and PPI targets. Compounds comply with the developmental trend of modern novel drug discovery, supporting routine primary screening as well as early hit identification of allosteric modulators and PPI inhibitors, serving as an efficient screening resource for early-stage innovative drug discovery.

A diversity compound library contains 1,000,000 compounds with drug fragments. Each compound has at least one drug fragment. These selected molecules have 702,902 Bemis-Murcko Scaffolds (BMS) with drug-like chemical space. This library is highly recommended for AI-based lead discovery, ultra-large virtual screening and novel lead discovery.

UORSY Screening Compounds Library contains about 680,000 compounds. The library has extensively developed a polymerization synthesis method that provides a highly diverse chemical structure. More than 85% of the compounds in the library have drug-like physicochemical properties, and more than 35% of the compounds have lead-like properties.

Diversity-based screening continues to be a vital tool for drug discovery. Efficiency and productivity can be improved by using screening libraries that offer maximum diversity whilst retaining drug-like properties. Chemspace Scaffold derived set composes 10,119 compounds, which including 3,373 scaffolds, 3 compounds per each. This library has exceptional coverage of drug-like chemical space.

Molecular Glue Virtual Library is constructed using generative AI technology, integrating the structural features, activity data of known molecular glues, and interaction information of ternary complexes (target protein-E3-molecular glue). Endowed with structural novelty, drug-likeness, diversity and synthesizability, it is applicable to molecular glue-based AI drug screening and large-scale virtual screening.

MCE builds this library based on high-quality molecular building blocks by virtue of robust computing power, coupled with rigorous reaction rules and optimized compound generation strategies. To ensure library quality, molecules with high synthetic difficulty, poor drug-likeness, PAINS and other undesirable molecules are excluded first. Subsequently, scaffold-based compound analysis is performed to screen drug-like diverse molecules for synthesizability evaluation; those with excessively high synthetic difficulty are removed, ultimately forming a large-scale molecular glue virtual library with structural diversity, synthesizability and drug-likeness.

Compounds in the library can be synthesized in only 1-2 chemical reaction steps. With MCE’s experienced chemical synthesis team, custom synthesis of different scales from milligram to kilogram can be easily achieved to meet diverse customer needs.

With MCE's 40,662 BBs, covering around 273 reaction types, more than 40 million molecules were generated. Compounds which comply with Ro5 criteria were selected. Inappropriate chemical structures, such as PAINS motifs and synthetically difficult accessible, were removed. Based on Morgan Fingerprint, molecular clustering analysis was carried out, and molecules close to each clustering center were extracted to form this drug-like and synthesizable diversity library. These selected molecules have 805,822 unique Bemis-Murcko Scaffolds (BMS) with diversified chemical space. This library is highly recommended for AI-based lead discovery, ultra-large virtual screening and novel lead discovery.

The Chinese National Compound Library (CNCL) composes 1.4 million compounds possessing diversified structures. Coupled with this library will be advanced sample handling, information management and quality control systems. Most compounds in the library are drug-like, conforming to “Lipinski’s Rule of Five”, such as MW < 500, logP < 5, Hydrogen Bond Donors < 5.

Sulfonyl fluoride (-SO₂F) overcomes the poor target selectivity of traditional covalent warheads that rely heavily on cysteine. With high stability and tunable electrophilicity under physiological conditions, it targets multiple nucleophilic residues including Lys, Tyr, Ser and His, offering expanded druggable space, lower off-target risks and prolonged efficacy. It is widely used in covalent inhibitors, molecular glues, PROTACs and chemical probes.

MCE has built a highly diverse sulfonyl fluoride fragment library with 1,162 structurally diverse, drug-like fragments. Designed for balanced reactivity, stability and compatibility, these molecules feature tunable electrophilicity, simple scaffolds and high derivatization potential. Combined with SuFEx click chemistry, the library enables efficient modular modification and rapid structure optimization.

Ideal for targeting non-cysteine residues, this library improves covalent screening and probe development efficiency, serving as a precise tool for early-stage covalent drug discovery and chemical biology research.

Chemspace Lead-Like Compound Library contains 1,367,511 in-Stock lead-like compoundswith favorable physicochemical profiles and high Quantitative Estimation of Drug-likeness.