Targeting peptide

Peptidomimetics are compounds whose essential elements (pharmacophore) mimic a natural peptide or protein in 3D space and which retain the ability to interact with the biological target and produce the same biological effect. Peptidomimetics are designed to circumvent some of the problems associated with a natural peptide: e.g. stability against proteolysis (duration of activity) and poor bioavailability. Certain other properties, such as receptor selectivity or potency, often can be substantially improved. The design and synthesis of peptidomimetics are most important because of the dominant position peptide and protein-protein interactions play in molecular recognition and signaling, especially in living systems. Hence mimics have great potential in drug discovery.

MCE Peptidomimetic Library contains 370 compounds including peptoid, α-helix mimetics, β-turn/sheets mimetics, etc. This library is an indispensable tool of structure-activity relationships in drug discovery.

Cyclic peptide library have advantages such as high affinity, high selectivity, and suitability for targeting protein–protein interactions. Through DEL synthesis technology, the library size can achieve hundreds of millions. DEL cyclic peptide library have advantages like low cost andhigh screeing efficiency, making them valuable for discovering lead compounds against challenging drug targets.

This cyclic peptide library is constructed with unnatural amino acids as building block, synthesized through DNA-compatible chemical reactions. Each cyclic peptide consist of six amino acids and constrained conformations such as side-chain cross-linking, disulfide bonds, and macrocyclization. These cyclic peptides exhibit significantly improved stability and druggability compared with linear peptides, filling the gap between small molecules and macromolecular biologics. Each cyclic peptide is uniquely conjugated to a DNA barcode sequence for molecular identification and sequencing decoding.

MCE’s cyclic peptide library has8 independent sub-libraries, with a total molecular diversity of 1.2 billion. It is constructed via multi-round combinatorial assembly of building blocks and diverse cyclization strategies, facilitating the discovery of cyclic peptide leads for undruggable targets.

Peptides are a group of biologically active substances that are involved in various cellular functions of organisms. Peptides are often used in functional analysis, vaccine research and especially in the field of drug research and development. At present, more than 80 peptide drugs have reached the market for a wide range of diseases, including diabetes, cancer, osteoporosis, multiple sclerosis, HIV infection and chronic pain.

MedChemExpress (MCE) offers a comprehensive collection of 2,520 peptides, including bioactive peptides, amino acid derivatives, and blocking peptides. MCE Peptide Library can be used for peptide library screening, peptide drug discovery, vaccine development, target verification, structural activity research, etc.

Peptides, composed of amino acids, serve as crucial building blocks for proteins and have gained significant attention in drug development over the past decade. The advancements in production, modification, and analytical technologies have led to a surge in the potential applications of peptides in medicine. Peptides offer a number of advantages over small molecule drugs, including: greater target specificity and efficacy, more predictable metabolic profiles, easier delivery to where they are needed in the body, and fewer side effects. Peptides are increasingly appearing in all branches of medicine as components of innovative drugs, imaging agents, diagnostic agents, and other complex drugs such as peptide-drug conjugates. To date, more than 80 peptide drugs have been approved to treat a variety of diseases, including microbial infections, obesity, anti-diabetes, and cancer, as well as to develop cell targeting platforms and improve cell penetration properties.

MCE designs a unique collection of 826 peptide compounds. HY-L105S is a peptide compound library that can be provided with solution form based on HY-L105, and can be applied to peptides-based drug development.

Cyclic peptides are polypeptide chains taking cyclic ring structure, which exhibit diverse biological activities, such as antibacterial activity, immunosuppressive activity and anti-tumor activity. Cyclic peptides, with the features of good binding affinity, target selectivity and low toxicity, show great success as therapeutics. Multiple cyclic peptides are currently in clinical use, for examples, gramicidin and tyrocidine with bactericidal activity, cyclosporin A with immunosuppressive activity, and vancomycin with antibacterial activity. Furthermore, cyclic peptides usually have the sufficient size and a balanced conformational flexibility/rigidity for binding to flat protein-protein interaction (PPI) interfaces, which have potential to develop PPI drugs.

MCE offers a unique collection of 97 cyclic peptides, all of which have good bioactivities. MCE Cyclic Peptide Library is a powerful tool for drug discovery and PPI inhibitor screening.

Dipeptide compounds have attracted extensive attention in drug discovery and life science research due to their simple structures, ease of modification, and favorable biocompatibility. As small peptides composed of two amino acids, dipeptides exhibit diverse biological activities, including anti-inflammatory, antioxidant, antimicrobial, anticancer, and immunomodulatory effects, showing significant application potential in metabolic disorders, neurological diseases, and cancer research. Compared with traditional small molecules, dipeptide compounds possess favorable target-binding properties and high structural plasticity, making them valuable tools for drug screening and mechanism studies.

The MCE Dipeptide Compound Library contains 79 dipeptide compounds and can be applied to peptide drug discovery and development.

Neurotransmitters are chemical messengers that allows a neuron's electrical signal to pass to a postsynaptic neuron or effect target. Neurotransmitters include amino acids, monoamines, and peptides, while other neurotransmitters are composed of metabolites such as nitric oxide and carbon monoxide. The function of neurotransmitters is closely related to the disease of life, helping to regulate the body's heartbeat, blood pressure, breathing, sleep, aging and muscle activity. Therefore, research based on neurotransmitters can help to increase human understanding of diseases.

MCE collects and organizes 58 neurotransmitters and is a tool library for drug screening and mechanism research.

ASINEX has elaborated a library of diverse macrocycles using an effective tool box of synthetic methods. The resulting scaffolds are novel, tremendously diverse, medchem-relevant, macrocyclic frameworks.

Macrocyles tend to be larger than traditional screening molecules which make them perfect discovery tools for targets with shallow or extended binding sites. At the same time, their unique character based on restricted flexibility and ability to form intra-molecular hydrogen bonds allows for design approaches effectively optimizing properties such asaqueous solubility and membrane permeability. Many of these macrocycles have been tested for aqueous and DMSO solubility with cut-offs applied at 10 mM in DMSO and 50 µM in PBS (pH 7.4) followed by PAMPA permeability assay.

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.