Hydrogen bond acceptor

19F-NMR has proved to be a detection mode in fragment-based drug discovery (FBDD) for studies of protein structure and interactions. 19F shows high sensitivity for NMR detection, and the exquisite sensitivity of 19F chemical shifts and linewidths to ligand binding all make it a valuable approach in FBDD.F (Fluorine) -Fragments can be used for 19F-NMR detection after binding to target proteins, and can be used as an effective 19F-NMR tool for FBDD.

MCE designs a unique collection of 5,123 F-fragments, all of which obey a heuristic rule called the “Rule of Three (RO3)”, in which molecular weight ≤300 Da, the number of hydrogen bond donors (H-donors) ≤3, the number of hydrogen bond acceptors (H-acceptors) is ≤3 and cLogP is ≤3. This F-fragments library is an important source of lead-like drugs.

Fragment-based drug discovery (FBDD) is well suited for discovering both drug leads and chemical probes of protein function; it can cover broad swaths of chemical space and allows the use of creative chemistry. Fragment-based drug discovery is well-established in industry and has resulted in a variety of drugs entering clinical trials, with two, vemurafenib and venetoclax, already approved. FBDD also has key attractions for academia. Notably, it is able to tackle difficult or novel targets for which no chemical matter may be found in existing HTS collections.

MCE designs a unique collection of 23,342 fragment compounds, all of which obey a heuristic rule called the “Rule of Three (RO3) ”, in which molecular weight ≤300 Da, the number of hydrogen bond donors (H-donors) ≤3, the number of hydrogen bond acceptors (H-acceptors) is ≤3 and cLogP is ≤3. This library is an important source of lead-like drugs.

Fragment-based drug discovery (FBDD) offers a strategic advantage by categorizing fragment hits according to their functional groups. This approach facilitates both the further optimization of these hits and the rational design of larger compounds through fragment combination. The amine functional group plays a vital role in drug development, as evidenced by its presence in many marketed drugs like Galantamine, Tacrine, and Rivastigmine. It is instrumental in enhancing solubility, improving bioavailability, and ensuring shelf-life stability—all critical factors for drug efficacy.

MCE offers a collection of 19,532 amine fragments for drug discovery. All of these compounds adhere to the Rule of Three (RO3) criteria for drug-likeness, which MCE offers a collection of 19,532 amine fragments for drug discovery, all of which stipulates a molecular weight ≤ 300 Da, ≤ 3 hydrogen bond donors, ≤ 3 hydrogen bond acceptors, and a cLogP ≤ 3.

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.

In contrast to the high conservation of conventional orthosteric sites, allosteric sites possess structural characteristics of low conservation, high hydrophobicity, weak polarity, confined spatial geometry, and dynamic cryptic properties. There is a significant difference between their core structures and orthosteric pockets — allosteric pockets are mostly dynamic grooves formed by protein conformational changes, subunit interface clefts, or shallow depressions, rather than the rigid "keyhole" structure of orthosteric sites. With looser spatial constraints, allosteric sites have the advantages of high selectivity and low off-target risk, and have become an important direction in new drug discovery.

Based on the dynamic, hydrophobic, and narrow-long spatial characteristics of allosteric pockets, MCE has performed targeted modification and screening of fragments. The screening criteria strictly conform to the requirements of allosteric binding: molecular weight is controlled at 120–280 Da (to meet the core needs of small molecules in fragment libraries and high derivatization), hydrogen bond donors (HBD ≤ 2), hydrogen bond acceptors (HBA ≤ 3), polar surface area (PSA = 30–80 Ų), rotatable bonds (≤ 2), moderate hydrophobicity (cLogP = 1–3.5), no strongly ionizable groups, and both appropriate rigidity and conformational flexibility to adapt to the dynamic changes of the pocket. Meanwhile, combined with the results of principal moment of inertia (PMI) analysis, fragments with high 3D diversity were obtained. Such fragments have good shape complementarity with allosteric pockets, ensuring that the fragments can smoothly enter the allosteric pockets and form stable binding, while providing room for subsequent optimization and derivation.

This library contains 1,800 structurally diverse fragment molecules with excellent drug-like properties, suitable for allosteric drug development and the design and optimization of allosteric sites. It combines the

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.

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).

The MCE 1K Drug Fragment Library consists of 1,366 drug fragments. These drug fragments are derived from 2,946 FDA-approved drug molecules, and fragments from one drug can appear in other drugs, so these fragments are somewhat correlated with good PK/PD properties. Fragment-based screening can reserve enough chemical space for subsequent structural optimization. This compound library is an essential tool for drug screening based on FBDD (Fragment-Based Drug Discovery).

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.