Conformational constraint

In PROTAC drug development, linkers are often one of the key variables determining drug-likeness and degradation efficiency. Since PROTAC systems must simultaneously satisfy target protein binding, E3 ligase recruitment, and intracellular spatial conformational matching, their structural design is essentially a multi-parameter optimization problem. Differences in linker rigidity, flexibility, and spatial extension can significantly influence the formation pathway and stability of the ternary complex, leading to substantial variations in degradation activity. Therefore, the development of linker systems with modular tunability and high structural expandability has become an important direction in PROTAC optimization.

The MCE Alkyne PROTAC Linker Library contains 0 linkers based on terminal and internal alkyne scaffolds, forming a highly derivatizable linker module system. These linkers serve as standardized building blocks for rapid assembly and iterative optimization of PROTAC molecules, and support efficient conjugation with azide-containing functional groups via click chemistry. In practical drug development, this type of structure not only facilitates the construction of diverse linker space libraries, accelerating lead compound screening, but also enables systematic tuning of molecular geometry and physicochemical properties, thereby improving ternary complex stability and targeted protein degradation efficiency.

The RNA-targeted bioactive compound library is a high-quality collection of small molecules specifically designed and curated to target RNA structures and functions. It is widely applied in cutting-edge drug discovery and life science research. Unlike traditional strategies that focus on protein targets, RNA-targeted compounds can directly modulate various functional RNA molecules by influencing their splicing, translation, stability, or structural conformation, thereby enabling precise intervention in key biological processes. In the field of drug development, these compounds provide a novel approach to addressing previously “undruggable” targets and have demonstrated significant potential in areas such as oncology, antiviral therapies, and neurodegenerative diseases. For example, by targeting disease-associated RNA structural domains or regulating the aberrant expression of non-coding RNAs, these compounds can effectively inhibit disease progression or restore normal cellular function. In mechanistic studies, RNA-targeted compounds serve as valuable chemical biology tools to elucidate the roles of RNA in gene expression regulation, cellular signaling pathways, and disease development.

The MCE RNA-targeted bioactive compound library contains 858 compounds, sourced from databases such as TargetRX Atlas and R-BIND. The library features excellent structural diversity and biological activity, making it suitable for high-throughput screening (HTS), target validation, phenotypic screening, and lead compound discovery. It represents a valuable resource for RNA-related research and innovative drug development.

Ion channels are key proteins on the cell membrane that regulate the flow of ions across membranes. They participate in nearly all physiological processes, including nerve conduction, muscle contraction, heart rhythm, and pain perception. Abnormalities in their function can lead to various serious diseases such as arrhythmia, epilepsy, hypertension, neuropathic pain, and cancer. Therefore, ion channels are highly valuable drug targets—over 15% of approved drugs target ion channels currently, demonstrating their irreplaceable therapeutic value in cardiovascular, neurological, and analgesic fields.

MCE has collected a library of over 5,000 reported ion channel-related bioactive compounds targeting major sites such as Na+ channels, K+ channels, Ca2+ channels, GABA receptors, iGluRs, and others. Using AI models, these compounds are characterized through both 2D representations (molecular fingerprints, pharmacophores) and 3D representations (3D conformation) to screen for a collection of lead-like compounds highly similar to known active molecules. Additionally, an hERG channel prediction algorithm integrating XGB and ISE mapping strategy is employed to assess and exclude potential cardiotoxicity in the library.. This step significantly reduces safety risks in subsequent screenings, particularly for ion channel drug development related to cardiovascular systems (e.g., Nav1.5, Cav1.2), effectively minimizing failures due to hERG inhibition and serving as a valuable tool for ion channel drug screening.

G protein-coupled receptors (GPCRs) are membrane proteins in humans and one of the most important targets in drug discovery. Approximately 35% of launched drugs are targeted GPCRs, making them a crucial class of targets in drug discovery.

The orthosteric site of a GPCR is its endogenous ligand’s (such as neurotransmitters or hormones) binding site. This site plays a central role in signal transduction. Small molecules binding to this site typically contain a protonatable amino group, enabling the formation of salt bridges or hydrogen bonds with acidic residues in the binding pocket. In contrast, the allosteric site does not directly initiate signaling but modulates the signal intensity of the GPCR by altering or stabilizing the conformation of the orthosteric site. Small molecules binding to the allosteric site often contain multiple aromatic rings to occupy hydrophobic pockets and achieve their functional effects.

MCE has collected over 7,106 reported bioactive molecules targeting GPCRs, covering Class A, B, and C GPCRs. These small molecules were subjected to AI representation to extract 2D and 3D features. Subsequently, we do screening by AI score based on similarity to identify molecules in diversity library highly similar to the reported bioactive molecules in both 2D and 3D, with a threshold greater than 0.7. Further screening based on cLogP was applied to select molecules with good lipophilicity, which facilitates the binding of small molecules to GPCRs. This diversity library can be widely applied to the discovery of compounds targeting GPCR proteins.

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