Lipophilicity

Membrane receptors, also known cell surface receptors or transmembrane receptors, are transmembrane proteins embedded into the plasma membrane which play an essential role in maintaining communication between the internal processes within the cell and various types of extracellular signals. They act in cell signaling by receiving (binding to) extracellular molecules, which are also called ligands. These extracellular molecules include hormones, cytokines, growth factors, neurotransmitters, lipophilic signaling molecules such as prostaglandins, and cell recognition molecules.

There are three kinds of membrane receptors: ion channel-linked receptors, enzyme-linked receptors and G-protein-linked receptors. They play important roles in keeping human normal physiologic processes. GPCRs and ion channels are important drug targets in drug discovery.

MCE provides a unique collection of 6,857 compounds targeting a variety of membrane receptors. MCE Membrane reeptor-targeted Compound Library can be used for membrane receptor-focused screening and drug discovery.

An emerging drug design method is based on the secondary binding site effect, where small molecule drugs are designed to bind to secondary binding sites on target biomolecules rather than primary orthomorphic sites. Successful potential drugs (known as allosteric modulators) will be able to bind to allosteric sites and remotely alter (or modify) the conformation of the main orthosteric binding sites of biological targets. Allosteric modulators (AMs) are ligands of proteins that act through binding sites different from natural (orthosteric) ligand sites. AMs are relatively small, more lipophilic, and more rigid compounds. The binding efficacy of AMs with their targets is often slightly lower. AMs are divided into positive AMs (PAMs) and negative AMs (NAMs). AMs are ideal drug targets because they can fine-tune receptor activity while preserving the spatial and temporal signal transduction characteristics of endogenous ligands, resulting in fewer targeted side effects, improved subtype selectivity, and better promotion of biased signal transduction than normal ligands.

MCE designs a unique collection of 250 small allosteric modulators. It is a good tool to be used for research on metabolize, cancer and other diseases.

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 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. However, the success rate of CNS drug development remains remarkably low, primarily due to the blood-brain barrier (BBB). The blood-brain barrier (BBB) is a semipermeable barrier structure that surrounds the microvasculature of the CNS. In capillaries, the wedged endothelial cells are tightly packed and wedge-shaped, lining the interior of the vessels to form extensive tight junctions. Along with a range of receptors, transporters, efflux pumps, and other cellular components, this barrier regulates the entry and exit of molecules between the bloodstream and the brain. The intact BBB blocks the passage of most blood-borne substances into the brain, preventing nearly 100% of large-molecule drugs and over 98% of small-molecule drugs from entering. Compared to non-CNS drugs, physicochemical properties such as hydrogen bonds, lipophilicity, and molecular weight significantly influence a compound's ability to cross the BBB. Using artificial intelligence (AI) algorithms to predict BBB permeability, a predicted value greater than 0.75 indicates that the compound has strong potential to cross the BBB, providing a promising starting point for CNS drug discovery.

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 7,113 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.