PPI,

Protein protein interactions (PPI) have pivotal roles in life processes. The studies showed that aberrant PPI are associated with various diseases. However, the design of modulators targeting PPI still faces tremendous challenges, such the difficult PPI interfaces for the drug design, lack of ligands reference, lack of guidance rules for the PPI modulators development and high-resolution PPI proteins structures.

The PPI Library comprises molecules of various sizes, frameworks, and shapes ranging from fragment-like entities to macrocyclic derivatives designed as secondary structure mimetics or as epitope mimetics. The designs cover β-turn / loop mimetics and α-helix mimetics. Since helices present at the interface in 62% of all protein-protein interactions. This library focused on designs including mimics with the substitution geometry of an a-helices, as well as designs that mimic the location of “hot-spot” side chains in helix-mediated PPIs.

Protein protein interactions (PPI) have pivotal roles in life processes. The studies showed that aberrant PPI are associated with various diseases, including cancer, infectious diseases, and neurodegenerative diseases. The classic drug targets are usually enzymes, ion channels, or receptors, the PPI indicate new potential therapeutic targets. Therefore, targeting PPI is a new direction in treating diseases and an essential strategy for the development of new drugs.

However, the design of modulators targeting PPI still faces tremendous challenges, such the difficult PPI interfaces for the drug design, lack of ligands reference, lack of guidance rules for the PPI modulators development and high-resolution PPI proteins structures.

With the development of high-throughput technology, high-throughput screening is also gradually used for the identification of PPI inhibitors, but the compound library used for conventional target screening is not very effective in screening PPI inhibitors. To improve screening efficiency, MCE carefully selected 797 PPI inhibitors and mainly targeting MDM2-p53, Keap1-Nrf2, PD-1/PD-L1, Myc-Max, etc. MCE Protein-protein Interaction Inhibitor Library is a useful tool for PPI drug discovery and related research.

Macrocycles, molecules containing 12-membered or larger rings, are receiving increased attention in small-molecule drug discovery. The reasons are several, including providing access to novel chemical space, challenging new protein targets, showing favorable ADME- and PK-properties. Macrocycles have demonstrated repeated success when addressing targets that have proved to be highly challenging for standard small-molecule drug discovery, especially in modulating macromolecular processes such as protein–protein interactions (PPI). Otherwise, the size and complexity of macrocyclic compounds make possible to ensure numerous and spatially distributed binding interactions, thereby increasing both binding affinity and selectivity.

MCE offers a unique collection of 451 macrocyclic compounds which can be used for drug discovery for high throughput screening (HTS) and high content screening (HCS). MCE Macrocyclic Compound Library is a useful tool for discovering new drugs, especially for “undruggable” targets and protein–protein interactions.

Cyclic peptides are polypeptide chains taking cyclic ring structure, which exhibit diverse biological activities, such as antibacterial activity, immunosuppressive activity and anti-tumor activity. Cyclic peptides, with the features of good binding affinity, target selectivity and low toxicity, show great success as therapeutics. Multiple cyclic peptides are currently in clinical use, for examples, gramicidin and tyrocidine with bactericidal activity, cyclosporin A with immunosuppressive activity, and vancomycin with antibacterial activity. Furthermore, cyclic peptides usually have the sufficient size and a balanced conformational flexibility/rigidity for binding to flat protein-protein interaction (PPI) interfaces, which have potential to develop PPI drugs.

MCE offers a unique collection of 96 cyclic peptides, all of which have good bioactivities. MCE Cyclic Peptide Library is a powerful tool for drug discovery and PPI inhibitor screening.

Recently, significant advancements in tyrosine-targeting electrophiles have primarily occurred in the field of protein-protein interactions (PPIs), where cysteine residues are often underrepresented and novel chemistries are needed to address these interfaces. In this context, tyrosines are frequently more accessible compared to more buried binding sites. Moreover, they are commonly found at "hot spots," which are functional epitopes of PPIs, with 12.3% of the residues consisting of tyrosines. This prevalence is likely due to the hydrophobic nature of tyrosine, its ability to participate in aromatic π-interactions, and its capacity for hydrogen bonding. Beyond PPIs, some progress has also been made in covalent tyrosine targeting in other areas where more commonly addressed side chains are lacking. Even though tyrosine has a slightly lower pKa value compared to the protonated lysine side chain (approximately 10 vs. 10.5 for the unprotected amino acid side chains), significantly less progress has been made in the development of tyrosine-targeted covalent ligands compared to lysine. This is likely due to the reduced flexibility of the tyrosine side chain and the greater steric hindrance of its hydroxy group, which makes it more challenging to adopt suitable reaction geometries.

Through careful selection, we constructed a structural filter containing over 110 electrophilic groups. By analyzing the electrophilic fragments selected by the structural filter, we removed any molecules with trivial or undesirable structural features. Ultimately, we obtained 124 fragment molecules which can target tyrosine residue and can be used for fragment-based covalent drug discovery.

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.

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