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 2,806 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.