cLogP

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 5,160 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 41,368 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 19,754 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 19,754 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.

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.

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.

G protein-coupled receptors (GPCRs) are membrane proteins in humans and one of the most important targets in drug discovery. Approximately 35% of launched drugs are targeted GPCRs, making them a crucial class of targets in drug discovery.

The orthosteric site of a GPCR is its endogenous ligand’s (such as neurotransmitters or hormones) binding site. This site plays a central role in signal transduction. Small molecules binding to this site typically contain a protonatable amino group, enabling the formation of salt bridges or hydrogen bonds with acidic residues in the binding pocket. In contrast, the allosteric site does not directly initiate signaling but modulates the signal intensity of the GPCR by altering or stabilizing the conformation of the orthosteric site. Small molecules binding to the allosteric site often contain multiple aromatic rings to occupy hydrophobic pockets and achieve their functional effects.

MCE has collected over 7,114 reported bioactive molecules targeting GPCRs, covering Class A, B, and C GPCRs. These small molecules were subjected to AI representation to extract 2D and 3D features. Subsequently, we do screening by AI score based on similarity to identify molecules in diversity library highly similar to the reported bioactive molecules in both 2D and 3D, with a threshold greater than 0.7. Further screening based on cLogP was applied to select molecules with good lipophilicity, which facilitates the binding of small molecules to GPCRs. This diversity library can be widely applied to the discovery of compounds targeting GPCR proteins.

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.

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 3,657 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.

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 5,182 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.

The MCE 1K Drug Fragment Library consists of 1,383 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).