HBD

With the aging population and increasing competitive pressures, neurodegenerative diseases of the central nervous system (CNS) have become a serious medical challenge in modern society, including Parkinson's disease, Alzheimer's disease, brain tumors, and multiple sclerosis. The CNS MPO (Multi-Parameter Optimization) score is a widely recognized algorithm in medicinal chemistry. Developed by Pfizer, this method is based on an analysis of approved CNS drugs and their interior CNS drug candidates, establishing the CNS MPO rules. It incorporates six key physicochemical properties (ClogP, ClogD, MW, TPSA, HBD, and pKa) to prospectively optimize CNS drug attributes—such as high blood-brain barrier (BBB) permeability, low P-gp efflux liability, low metabolic clearance, and high safety—thereby improving the clinical success rate of CNS drug candidates. The CNS MPO compound library is a collection of compounds with CNS MPO scores greater than 5, specifically designed for CNS drug discovery.

Unlike highly conserved orthosteric sites, allosteric sites exhibit low conservation, high hydrophobicity, weak polarity, confined geometry, and dynamic cryptic properties. Rather than rigid keyhole-like cavities, they typically appear as flexible grooves, subunit interface clefts, or shallow depressions formed by protein conformational changes.

Based on the dynamic, hydrophobic, and elongated nature of allosteric pockets, MCE has carried out targeted fragment modification and screening under strict physicochemical criteria: MW 120–280 Da, HBD ≤ 2, HBA ≤ 3, PSA 30–80 Ų, rotatable bonds ≤ 2, cLogP 1–3.5. High 3D diversity was further ensured by PMI analysis, yielding fragments with excellent shape complementarity to allosteric pockets.

This library contains 1,800 structurally diverse, drug-like fragments, this library supports allosteric drug development and pocket optimization. It significantly improves screening hit rates and enables efficient, precise early-stage R&D of allosteric drugs.

Small molecule covalent inhibitors, or irreversible inhibitors, are a type of inhibitors that exert their biological functions by irreversibly binding to target through covalent bonds. Compared with non-covalent inhibitors, covalent inhibitors have obvious advantages in bioactivity, such that covalent warheads can target rare residues of a particular target protein, thus leading to the development of highly selective inhibitors and achieving a more complete and continued target occupancy in living systems. In recent years, the distinct strengths of covalent inhibitors in overcoming drug resistance had been recognized. However, toxicity can be a real challenge related to this class of therapeutics due to their potential for off-target reactivity and has led to these drugs being disfavored as a drug class. The drug design and optimization of covalent inhibitors has become a hot spot in drug discovery.

MCE Lead-like Covalent Screening Library offers a valuable resource of 1,049 lead-like compounds with commonly used covalent warheads. These warheads, such as acrylamide, activated terminal alkyne, acyloxymethyl ketone, and boronic acid, are capable of reacting with specific amino acid residues, including cysteine, lysine, serine, and histidine. The inclusion of these reactive warheads in the library allows researchers to explore the potential of covalent inhibition, a powerful approach in drug discovery.

On May 15, 2024, "Dimerization and antidepressant recognition at noradrenaline transporter" was published online by Nature. The research findings were an effort from Shanghai Institute of Materia Medica, Chinese Academy of Sciences. This study unraveled the important neural system target - the noradrenaline transporter (NET), obtaining the binding modes of human NET homodimers with the natural substrate norepinephrine (NE) and six selective antidepressants. It laid an important theoretical foundation for understanding the physiological regulation mechanisms of NET and other monoamine transporters.

The Norepinephrine Transporter (NET) Compound Library is obtained by computer-aided virtual screening based on the HY-L901 compound library . The specific screening process includes molecular docking screening, key pharmacophore screening, and CNS-MPO screening, which can be used for new drug discovery targeting the noradrenaline transporter.

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.

With MCE's 40,662 BBs, covering around 273 reaction types, more than 40 million molecules were generated. Compounds which comply with Ro5 criteria were selected. Inappropriate chemical structures, such as PAINS motifs and synthetically difficult accessible, were removed. Based on Morgan Fingerprint, molecular clustering analysis was carried out, and molecules close to each clustering center were extracted to form this drug-like and synthesizable diversity library. These selected molecules have 805,822 unique Bemis-Murcko Scaffolds (BMS) with diversified chemical space. This library is highly recommended for AI-based lead discovery, ultra-large virtual screening and novel lead discovery.

With MCE's 40,662 BBs, covering around 273 reaction types, more than 40 million molecules were generated. Compounds which comply with Ro5 criteria were selected. Inappropriate chemical structures, such as PAINS motifs and synthetically difficult accessible, were removed. Based on Morgan Fingerprint, molecular clustering analysis was carried out, and molecules close to each clustering center were extracted to form this drug-like and synthesizable diversity library. These selected molecules have 805,822 unique Bemis-Murcko Scaffolds (BMS) with diversified chemical space. This library is highly recommended for AI-based lead discovery, ultra-large virtual screening and novel lead discovery.

Natural products are an attractive source with varied structures that exhibit potent biological activities, and desirable pharmacological profiles. The core scaffold of a natural product can also provide a biologically validated framework upon which to display diverse functional groups. Inspired by bioactive natural products, natural product-like compounds, occupying the same chemical space, are ideally suited to explore and to facilitate understanding of biological pathways.

MCE 10K Natural Product-like Compound Library consists of 10,000 natural product-like compounds. Each compound has scaffold of natural products or Tanimoto coefficient >0.6 with natural products. The natural-likeness scoring of these compounds is >-2. What’s more, compounds in the library are drug-like and readily available for re-supply, making it a powerful tool for new drug research and development. It can be widely applied in high-throughput screening (HTS) and high-content screening (HCS).

Natural products are an attractive source with varied structures that exhibit potent biological activities, and desirable pharmacological profiles. The core scaffold of a natural product can also provide a biologically validated framework upon which to display diverse functional groups. Inspired by bioactive natural products, natural product-like compounds, occupying the same chemical space, are ideally suited to explore and to facilitate understanding of biological pathways.

MCE 5K Natural Product-like Compound Library consists of 4,803 natural product-like compounds. Each compound has scaffold of natural products or Tanimoto coefficient >0.6 with natural products. The natural-likeness scoring of these compounds is >-2. What’s more, compounds in the library are drug-like and readily available for re-supply, making it a powerful tool for new drug research and development. It can be widely applied in high-throughput screening (HTS) and high-content screening (HCS).

MegaUni 50K Virtual Diversity Library consists of 50,000 novel, synthetically accessible, lead-like compounds. With MCE's 40,662 Building Blocks, covering around 273 reaction types, more than 40 million molecules were generated. Based on Morgan Fingerprint and Tanimoto Coefficient, molecular clustering analysis was carried out, and molecules closest to each clustering center were extracted to form a drug-like and synthesizable diversity library. The selected 50,000 drug-like molecules have 46,744 unique Bemis-Murcko Scaffolds (BMS), each containing only 1-3 compounds. This diverse library is highly recommended for virtual screening and novel lead discovery.