hit molecule

Designed to maximize efficiency in hit discovery and optimization, this compound library is built on a foundation of diverse Bemis-Murcko scaffolds, with each scaffold is represented by two specifically derived molecules. This strategy ensures broad chemical space through scaffold diversity while enabling preliminary functional group exploration. This approach provides early structure-activity relationship (SAR) insights for every scaffold, making it a valuable tool for accelerating drug discovery.

A unique set of molecules containing mild electrophilic moieties that covalently interact with amino acid residues in the target protein. The diversity of our compounds for covalent drug discovery ranges from natural product-like scaffolds to macrocycles, creating multiple opportunities in hit generation for a selected target.

Fragment-based drug discovery (FBDD) is well suited for discovering both drug leads and chemical probes of protein function. 3-dimensionality (3D) diversity is pivotal because the molecular shape is one of the most important factors in molecular recognition by a biomolecule. There is a developing appreciation that 3D fragments could offer opportunities that are not provided by 2D fragments.

MCE 3D Diverse Fragment Library consists of 5,400 non-flat fragment-like molecules (average Fsp3 value 0.58). More than 4,700 fragment compounds contain at least one chiral center in the structure. The key concepts that underlie the library design were 3D shape, structural diversity, reactive functionality and fragment-like. This 3D Diverse Fragment Library brings higher fragment hit optimization and increases the likelihood to find innovative hits in FBDD.

PD-1/PD-L1 are key immune checkpoint targets that suppress T-cell-mediated anti-tumor immunity, representing a major focus in cancer immunotherapy. While antibody drugs dominate the clinic, they are limited by administration challenges and immune-related side effects. Small-molecule PD-1/PD-L1 inhibitors, with oral availability, good tissue penetration and low cost, have emerged as a promising next-generation strategy.

A PD-1/PD-L1 lead-like library was built via a five-step virtual screening process. After collecting 8,947 inhibitors from BindingDB and PubChem and filtering by activity and duplicates, AI similarity screening was performed using GeminiMol. Key pharmacophores were extracted from the PPI interface of co-crystal structures, and molecular was screened via a pharmacophore model, effectively enhancing target activity.

Containing 10,000 structurally diverse and drug-like molecules well-matched to the PD-L1 pocket, the library supports virtual docking, high-throughput screening and hit discovery, enabling efficient and rapid development of small-molecule immunotherapies.

Spirocyclic compounds, with rigid 3D structures, high Fsp³ and strong conformational restriction, are highly privileged scaffolds in small-molecule drug screening. They overcome drawbacks of planar aromatic compounds such as poor solubility, high off-target risks and weak druggability. Their orthogonal bicyclic geometry fits well into protein pockets, improving target affinity, subtype selectivity, metabolic stability and membrane permeability, making them ideal for hit identification against kinases, GPCRs, PPIs and other targets.

Spirocyclic scaffolds have been widely applied in oncology, antivirals, hypertension and CNS diseases, leading to many approved drugs and clinical candidates. SAR studies show that spiro-atom chirality, ring size and heteroatom substitution dominate bioactivity and selectivity, with the scaffold mainly serving as a conformational anchor. Azaspirocycles, spirooxindoles and spirosteranes target GPCRs, kinases, MDM2-p53 and PPIs. Approved drugs including irbesartan, spironolactone and rolapitant confirm their druggability, while revumenib and SAR405838 show promise against undruggable targets.

The MCE Spirocyclic Druglike Library contains over 1,000 diverse, stereospecific molecules selected by Lipinski’s rules. It covers privileged cores such as azaspirocycles, oxaspirocycles and spirooxindoles. These molecules bear rich chiral centers and distinct 3D orientations, reducing non-specific binding and enhancing screening efficiency. Featuring novel scaffolds, the library offers a highly innovative starting point for 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

Seven-membered rings are privileged medium-sized scaffolds with distinct twist-chair conformations and greater 3D diversity than five- and six-membered rings. Their flexible conformations allow induced-fit protein binding and precise pharmacophore positioning. They also modulate Fsp³, pKa and logP to enhance solubility and permeability. Azepanes, oxepanes and benzodiazepines serve as bioisosteres for hit discovery against GPCRs, ion channels and kinases.

Widely found in plant and microbial alkaloids, seven-membered heterocycles show excellent biocompatibility and target affinity. They underpin many approved drugs for CNS, cancer and infectious diseases, including diazepam, imipramine and carbamazepine. Clinical candidates further highlight their unique value. However, high transannular strain and synthetic difficulty limit their availability, leaving them rare in standard screening libraries.

MCE 7 Membered Scaffold Library contains 2,792 structurally diverse, lead-like molecules covering azepanes, oxepanes, benzodiazepines and dibenzazepines. With varied substitutions, chiral centers and synthetic accessibility, it fills the shortage of medium-ring scaffolds. Ideal for HTS, virtual screening and SAR studies, these novel, patent-clear compounds offer a distinctive starting point for drug discovery in CNS disorders, oncology, antivirals and challenging targets such as PPIs.

The incidence and significance of central nervous system diseases are increasing at an alarming rate all over the world. Although substantial research efforts have been applied to develop new CNS-active drugs, only a few CNS disorders are addressed satisfactorily, while the remaining ones pose significant clinical challenges. Blood-brain barrier (BBB) permeability is one of the most important limiting factors in the design and development of novel CNS-targeted pharmaceuticals for the treatment of neurological disorders.

Carefully selected from the HTS Compound Collection to meet the parameters optimized for high BBB-permeability, our CNS Focused Screening Library comprising over 30,300 structurally-diverse and potentially CNS-active screening compounds. This original Screening Compound Library is aimed at supporting CNS drug design projects and HTS efforts in search for novel neurotherapeutics.

The discovery of hit molecule is a cornerstone of drug development. Among the diverse tools available, DNA-encoded libraries have emerged a revolutionary platform for high-throughput screening. Compared with traditional HTS, DEL features shorter screening processes, lower costs, simpler assays, and larger library capacities.

DEL Construction utilizes split-and-pool synthesis, a combinatorial chemistry approach that involves iterative splitting, reaction, and pooling. This strategy enables rapid, exponential assembly of fragments in minimal steps without the need for individual compound synthesis andassoicicated isolation or purification steps, thus greatly reducing overall costs. The technology enables simultaneous affinity screeningof massive compound collections to target proteins in a single step. By coupling chemical structures with unique DNA barcodes, each compound is tagged with a distinct DNA sequence for convenient tracking and decoding.DELs readily enable the construction and efficient screening of libraries containing millions to billions of compounds. As a result, DEL screening combines the dual advantages of high efficiency and low cost, making DEL a transformative technology in modern drug discovery.

The DEL kit consists of 50 independent libraries with a total scale of 100 billion compounds. It is constructed through stepwise combinatorial chemistry strategies involving 2-, 3-, and 4-round synthesis. By employing diverse scaffolds and flexible linking strategies, it encompasses various ring systems, linear frameworks, and heterocyclic structures. Screening can be achieved solely through affinity, independent of target-specific activity detection methods. This library is suitable for DEL screening against a wide range of targets.

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.

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.

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).