filters

Different functional groups confer unique chemical properties and reactivity characteristics to compounds. The presence of these functional groups not only affects the physical properties of the compounds, such as solubility and boiling point, but also determines their chemical reactivity and potential applications in chemical synthesis.

Covalent ligands rely on reactive groups (“warheads”), and new warheads are key to expanding the scope of covalent modalities. 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 4,900 multifunctional covalent fragments.

Covalent inhibitors are small molecules that can bind specifically to target proteins through covalent bonds and inhibit their biological functions. Although for a long time, covalent targeting has been playing a subordinate role in drug discovery, with an increasing number of reports on successful clinical applications of such drugs, the potential of these agents is now being acknowledged.

Covalent ligands rely on reactive groups (“warheads”), and new warheads are key to expanding the scope of covalent modalities. 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 8,900 fragment molecules with covalent modification potential, which can target various reactive amino acid residues and can be used for fragment-based covalent drug discovery.

In the research of covalent inhibitors targeting serine and threonine, scientists have found that the nucleophilicity of these hydroxyl groups is significantly enhanced due to the influence of their surrounding environment. This results in higher activity during catalytic reactions. Aspirin, which targets the non-catalytic domain serine (Ser529 in human COX1) of cyclooxygenase, exerts its anti-inflammatory effect through covalent binding. β-lactam antibiotics, which targets the catalytic domain serine of penicillin-binding proteins, interferes with bacterial cell wall synthesis.

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 3,300 fragment molecules which can target serine and threonine residues and can be used for fragment-based covalent drug discovery.

Covalent inhibitors are small molecules that can bind specifically to target proteins through covalent bonds and inhibit their biological functions. Although for a long time, covalent targeting has been playing a subordinate role in drug discovery, with an increasing number of reports on successful clinical applications of such drugs, the potential of these agents is now being acknowledged. Currently, cysteine is the most common covalent amino acid residue in a variety of covalent drugs, and various warheads have been developed that can react with cysteine, providing the key building blocks for covalent drugs to form covalent bonds.

To meet the development needs of covalent inhibitors targeting cysteine, MCE has designed a unique collection of 3,601 fragments with different covalent warheads that target cysteine. The MCE Cysteine Targeted Covalent Fragment Library is designed using the following covalent warheads: Acrylamides, Propiolic acid ester, Dimethylamine functionalized acrylamides, Chloroacetamides, Acrylonitrile, 2-Cyanoacrylamide, Aziridine, Haloacetamide, etc. All fragments are pre-filtered with the Rule of Three restrictions which can be used for fragment-based covalent drug development.

Lysine is the second most common target residue used in the design of TCIs and related covalent ligands. Its appeal lies in its abundance in human proteins, which is approximately three times higher than that of cysteine (5.8% vs. 1.9%). This significantly increases the number of proteins suitable for covalent targeting, especially given that many human proteins lack ligandable cysteine residues. Moreover, it has been suggested that functional lysines have a lower probability of being replaced by mutation, as they often play a crucial role in catalysis by acting as bases or nucleophiles. Additionally, lysines are essential for maintaining the structural integrity of proteins and for regulating post-translational modifications (PTMs). Consequently, targeting lysine has garnered significant interest in recent years.

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 445 fragment molecules which can target lysine residue and can be used for fragment-based covalent drug discovery.

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.

CRBN, namely cereblon, is the substrate recognition subunit of the E3 ubiquitin ligase complex in the ubiquitin-proteasome system. A CRBN ligand library refers to a collection of numerous fragments that can specifically bind to the CRBN protein.

These ligands are mostly designed based on validated CRBN-binding warheads and modified through AI-driven molecular generation optimization systems. They not only include classic lenalidomide-derived structures but also cover novel non-lenalidomide scaffolds. After drug-likeness filtering, these ligands exhibit structural diversity and favorable druggable properties. They can be further optimized and modified to facilitate the development of novel molecular glue degraders, accelerate the discovery of molecular glues that induce interactions between CRBN and new substrate proteins, and enable the exploration of novel CRBN substrates for identifying previously unknown CRBN-binding proteins.

MCE compiles 125 fragments that can specifically bind to the CRBN protein, with molecular weights ranging from 200 to 500. Compounds developed based on the library ligands target multiple disease targets such as cancer and autoimmune diseases, further advancing the development of Molecular Glues and PROTACs therapeutic agents.

RNA is crucial for the regulation of numerous cellular processes and functions. With the in-depth study of disease mechanisms, processes such as RNA expression, splicing, translation, and stability regulation have become new targets for disease intervention. RNA has provided new therapeutic modalities for metabolic diseases, genetic disorders, and cancer patients, resulting in several innovative drugs.

MCE R&D team collected small molecules targeting RNA from the PDB, R-BIND, ROBIN, and internal database as the positive dataset, and non-targeting RNA small molecules from ROBIN as the negative dataset. Based on the GeminiMol pre-trained model, we encoded the molecules and calculated over 1700 molecular descriptors using Mordred as inputs for the model. Subsequently, we employed 13 deep learning models to learn from the data. All of which yielded good training results, with AUROCs greater than 0.75. Ultimately, we selected the Finetune model to screen HY-L901P, which exhibited the best classification performance, achieving an AUROC of 0.82 and a prediction accuracy of 0.76. We then applied filtering based on StaR rules (with at least two of the following properties: cLogP ≥ 1.5, Molar Refractivity ≥ 4, Relative Polar Surface Area ≤ 0.3) to obtain a library containing approximately 5,000 small molecule compounds targeting RNA. This library serves as a valuable tool for screening small molecules that interact with RNA.

Owing to the high conservation of orthosteric sites, conventional orthosteric drugs frequently suffer from poor subtype selectivity, off-target toxicity, and drug resistance, severely restricting their clinical application. In contrast, allosteric sites feature low conservation, high hydrophobicity, weak polarity, confined spatial geometry, and dynamic cryptic properties. These characteristics endow allosteric modulators with distinct advantages including high selectivity, functional tunability, and improved safety, making allosteric therapy a key direction in modern drug discovery.

MCE has curated nearly 1,000 structurally disclosed clinical-stage allosteric modulators. By analyzing allosteric protein–ligand complex structures from the PDB database, we extracted core pharmacophores and privileged scaffolds. Adopting a rational design strategy of “scaffold derivation + allosteric physicochemical filtering”, we performed secondary screening on the derived compounds strictly following the optimal physicochemical principles for allosteric binding based on universal allosteric pocket properties: molecular weight 300–500 Da, HBD ≤ 3, HBA = 3–8, PSA = 70–120 Ų, rotatable bonds ≤ 6, highly rigid scaffolds, cLogP = 1.0–3.8, and no strongly ionizable groups. The selected compounds exhibit high rigidity and shape complementarity, making them well-suited for targeting shallow, dynamic, and hydrophobic-dominated allosteric pockets.

This allosteric modulator library contains 4,315 structurally diverse, lead-like compounds dedicated to allosteric drug development, allosteric site targeting, and allosteric modulator screening. It is suitable for kinases, GPCRs, and other important drug targets. All compounds are analogs of clinical-stage allosteric modulators with a similarity score > 0.6, combining excellent druggability and allosteric binding potential. It provides a highly efficient tool for early-stage allosteric drug discovery.

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.

Covalent inhibitors are small molecules that can bind specifically to target proteins through covalent bonds and inhibit their biological functions. Although for a long time, covalent targeting has been playing a subordinate role in drug discovery, with an increasing number of reports on successful clinical applications of such drugs, the potential of these agents is now being acknowledged. Currently, cysteine is the most common covalent amino acid residue in a variety of covalent drugs, and various warheads have been developed that can react with cysteine, providing the key building blocks for covalent drugs to form covalent bonds.

To meet the development needs of covalent inhibitors targeting cysteine, MCE has designed a unique collection of 5,112 compounds with different covalent warheads that target cysteine. The MCE Cysteine Targeted Covalent Library is designed using the following covalent warheads: Acrylamides, Propiolic acid ester, Dimethylamine functionalized acrylamides, Chloroacetamides, Acrylonitrile, 2-Cyanoacrylamide, Aziridine, Haloacetamide, etc.

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.

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.

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.

MCE 5K Scaffold Library consists of 5,000 lead-like compounds. Each compound represents one unique scaffold. All compounds are compatible with Lipinski’s rule (Rule of 5) with multiple characteristics such as calculated good solubility (-3.2 < logP < 5), oral bioavailability (RotB <= 10), drug transportability (PSA < 120). Compounds contained within the library have been screened to remove any inappropriate chemical structures, avoiding “false hits”. The sufficient diverse of compound structure makes this library a powerful tool for drug screening.

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.

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 5,000 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).

MCE 50K Diversity Library consists of 50,000 lead-like compounds with multiple characteristics such as calculated good solubility (-3.2 < logP < 5), oral bioavailability (RotB <= 10), drug transportability (PSA < 120). These compounds were selected by dissimilarity search with an average Tanimoto Coefficient of 0.52. There are 36,857 unique scaffolds and each scaffold 1 to 7 compounds. What’s more, compounds with the same scaffold have as many functional groups as possible, which make abundant chemical spaces. This exceptionally diverse library is highly recommended for random screening against new as well as popular targets based its novel, diverse scaffolds, abundant chemical spaces and the convenience for subsequent modification.

MEM Non-essential Amino Acid Solution (100×) has been filtered and can be used directly. It adds nutrients and reduces the biosynthetic burden on cell in vitro. The 100 mL is defined as the base specification. All larger sizes correspond to incremental volumes of this base.

MCE Gentamicin, Sterile (10 mg/mL) is a filtered and sterilized antibiotic solution that can be used directly in cell culture. Gentamicin acts by binding to the 30S subunit of the bacterial ribosome leading to inhibition of protein synthesis and death in susceptible bacteria, mainly for gram-negative and gram-positive bacteria.

MCE Blasticidin S, Sterile (10 mg/mL) is a filtered and sterilized antibiotic solution that can be used directly in cell culture. Blasticidin S is a peptidyl nucleoside antibiotic isolated from Streptomyces griseochromogenes. It acts by blocking hydrolysis of peptidyl-tRNA induced by release factors and inhibits peptide bond formation.

MCE Amphotericin B, Sterile (250 μg/mL) is a filtered and sterilized antibiotic solution that can be used directly in cell culture. Amphotericin B is a polyene antifungal antibiotic produced by Streptomyces nodosus. It can bind with sterols to form transmembrane channels, resulting in the leakage of intracellular substances, thus inhibiting fungal and yeast contamination.

MCE Hygromycin B, Sterile (50 mg/mL) is a filtered and sterilized antibiotic solution that can be used directly in cell culture.Hygromycin B is an aminoglycosidic antibiotic purified from Streptomyces hygroscopicus. It acts by binding to the 70S subunit of the bacterial ribosome and inhibiting protein synthesis, leading to the death of bacteria, fungi and mammalian cells.

MCE 0.25% Trypsin-EDTA (1×), Phenol Red-Free, is prepared by dissolving trypsin powder (a mixture of proteases from porcine pancreas, irradiated and sterilized) and EDTA in a calcium- and magnesium-free balanced salt solution. It is filter-sterilized and can be directly used for the dissociation of cultured cells and tissues. The 100 mL is defined as the base specification. All larger sizes correspond to incremental volumes of this base.