cyclic compounds

Cyclic peptide library have advantages such as high affinity, high selectivity, and suitability for targeting protein–protein interactions. Through DEL synthesis technology, the library size can achieve hundreds of millions. DEL cyclic peptide library have advantages like low cost andhigh screeing efficiency, making them valuable for discovering lead compounds against challenging drug targets.

This cyclic peptide library is constructed with unnatural amino acids as building block, synthesized through DNA-compatible chemical reactions. Each cyclic peptide consist of six amino acids and constrained conformations such as side-chain cross-linking, disulfide bonds, and macrocyclization. These cyclic peptides exhibit significantly improved stability and druggability compared with linear peptides, filling the gap between small molecules and macromolecular biologics. Each cyclic peptide is uniquely conjugated to a DNA barcode sequence for molecular identification and sequencing decoding.

MCE’s cyclic peptide library has8 independent sub-libraries, with a total molecular diversity of 1.2 billion. It is constructed via multi-round combinatorial assembly of building blocks and diverse cyclization strategies, facilitating the discovery of cyclic peptide leads for undruggable targets.

Alkaloids are a large and complex group of cyclic compounds that contain N. About 2,000 different alkaloids have been isolated. Important alkaloids include morphine, strychnine, atropine, colchicine, ephedrine, quinine, and nicotine. Alkaloids are useful as diet ingredients, supplements, and pharmaceuticals, in medicine and in other applications in human life. They showed anti-inflammatory, anticancer, analgesics, local anesthetic and pain relief, neuropharmacologic, antimicrobial, antifungal, and many other activities. Alkaloids are also important compounds in organic synthesis for searching new semisynthetic and synthetic compounds with possibly better biological activity than parent compounds.

MCE designs a unique collection of 599 alkaloids that all come from natural products. MCE Alkaloids Library is a useful tool for drug discovery that can be used for high throughput screening (HTS) and high content screening (HCS).

Heterocyclic compounds are cyclic organic compounds which contain at least one hetero atom, the most common heteroatoms are nitrogen, oxygen ,and sulfur. Heterocycles are common in biology, featuring a wide range of structures from enzyme co-factors to amino acids and proteins. On the one hand, heterocycles are common structural units in approved drugs and in medicinal chemistry targets in the drug discovery process. In addition, heterocycles have been found as a key structure in medical chemistry and also they are frequently found in large percent of biomolecules such as vitamins, natural products ,and biologically active compounds including antifungal, anti-inflammatory, antibacterial, antioxidant, antiallergic, anti-HIV, antidiabetic, anticancer activity.

MCE offers a unique collection of 6,484 heterocyclic compounds which can be used for drug discovery for high throughput screening (HTS) and high content screening (HCS). MCE heterocyclic compound library is critical for drug discovery and development.

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.

Macrocyclic compounds (≥12-atom cyclic small molecules/peptides) have unique physicochemical properties. They form preorganized conformations with high binding affinity/selectivity, target traditional small-molecule-inaccessible proteins, and bridge small-molecule drugs and biological agents. As key protein phosphorylation enzymes, kinases are linked to tumors, COPD, etc., and are critical therapeutic targets. Traditional small-molecule kinase inhibitors lack selectivity, causing off-target toxicity, low bioavailability, and acquired resistance. Macrocycles’ semi-rigid structure restricts conformations, boosts binding selectivity, optimizes pharmacokinetics, and makes macrocyclization a core kinase inhibitor optimization strategy.

Thousands of bioactive macrocycles were curated from ChEMBL. Via Transformer, macrocyclization was converted into a chemical language translation task, enabling end-to-end macrocycle generation from linear precursors with simplified inputs. Macformer achieves efficient, automated linear molecule macrocyclization via deep learning; generated macrocycles have diversity, novelty, biocompatibility, and cover broader chemical space.

MCE collected thousands of marketed/clinical kinase inhibitors, using their fragments for macrocyclization to generate derivatives. After evaluating synthetic accessibility and physicochemical properties, a million-scale virtual macrocyclic library was built for kinase-related virtual and AI-driven screening.

Macrocyclic compounds (≥12-atom cyclic small molecules/peptides) have unique physicochemical properties. They form preorganized conformations with high binding affinity/selectivity, target traditional small-molecule-inaccessible proteins, and bridge small-molecule drugs and biological agents. As key protein phosphorylation enzymes, kinases are linked to tumors, COPD, etc., and are critical therapeutic targets. Traditional small-molecule kinase inhibitors lack selectivity, causing off-target toxicity, low bioavailability, and acquired resistance. Macrocycles’ semi-rigid structure restricts conformations, boosts binding selectivity, optimizes pharmacokinetics, and makes macrocyclization a core kinase inhibitor optimization strategy.

Thousands of bioactive macrocycles were curated from ChEMBL. Via Transformer, macrocyclization was converted into a chemical language translation task, enabling end-to-end macrocycle generation from linear precursors with simplified inputs. Macformer achieves efficient, automated linear molecule macrocyclization via deep learning; generated macrocycles have diversity, novelty, biocompatibility, and cover broader chemical space.

MCE collected thousands of marketed/clinical kinase inhibitors, using their fragments for macrocyclization to generate derivatives. After evaluating synthetic accessibility and physicochemical properties, a million-scale virtual macrocyclic library was built for kinase-related virtual and AI-driven screening.