Drug-likeness

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.

Fragment-based drug discovery (FBDD) offers a strategic advantage by categorizing fragment hits according to their functional groups. This approach facilitates both the further optimization of these hits and the rational design of larger compounds through fragment combination. The amine functional group plays a vital role in drug development, as evidenced by its presence in many marketed drugs like Galantamine, Tacrine, and Rivastigmine. It is instrumental in enhancing solubility, improving bioavailability, and ensuring shelf-life stability—all critical factors for drug efficacy.

MCE offers a collection of 20,065 amine fragments for drug discovery. All of these compounds adhere to the Rule of Three (RO3) criteria for drug-likeness, which MCE offers a collection of 20,065 amine fragments for drug discovery, all of which stipulates a molecular weight ≤ 300 Da, ≤ 3 hydrogen bond donors, ≤ 3 hydrogen bond acceptors, and a cLogP ≤ 3.

At the forefront of innovative drug discovery, every medicinal chemist faces the challenge of rapidly identifying high-quality hit compounds from vast repositories of chemical resources.

The MCE Natural Product Diversity Scaffold Library is the result of a streamlined optimization process built upon our existing natural product collection. Adhering to the rigorous selection principle of "retaining only one representative compound per BMS scaffold", we have concentrated the diversity of thousands of compounds into a high-value, low-redundancy core set containing 2,256 compounds. All compounds are derived from natural sources, inheriting their inherent advantages of structural complexity and drug-likeness. By eliminating redundancy, the library size is significantly reduced without any compromise to chemical diversity. This approach effectively lowers the cost and time required for primary screening while simplifying downstream data analysis and structure-activity relationship (SAR) studies.

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.

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 122 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.