𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐫𝐞𝐭𝐫𝐨-𝐢𝐧𝐯𝐞𝐫𝐬𝐨 𝐩𝐞𝐩𝐭𝐢𝐝𝐞𝐬 𝐚𝐧𝐝 𝐭𝐡𝐞𝐢𝐫 𝐫𝐨𝐥𝐞 𝐢𝐧 𝐝𝐫𝐮𝐠 𝐝𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲? Peptide drugs, though often potent in their biological activities, often face hurdles such as protease degradation that reduces their half life and bioavailability. However, retro-inverso #peptides, a kind of non canonical peptides recently explored in a new article on #drugdiscovery, are a promising solution for drug developers. Retro-inverso peptides are a type of peptidomimetic using D-amino acids (retro isomers) and inverting the primary sequence of the original peptide (inverted). This dual modification creates a stable version of the peptide that is not easily recognized and broken down by biological systems. As retro-inverso peptides are more resistant to proteolytic degradation they can remain active in the body for longer periods increasing their bioavailabiity, while their unique structure can enhance binding affinity and specificity to their targets. This makes them highly interesting in drug discovery. Yet their implementation can be intricate and time-consuming. Fortunately, artificial intelligence can facilitate and expedite the process, revolutionizing peptide development. AI algorithms can analyze vast datasets of peptide sequences and structure-function relationships to design the most effective peptide sequences for specific targets, with enhanced peptide durability and absorption in the body. For example, by leveraging machine learning techniques, researchers can design shorter versions of retro-inverso peptides with optimized biological properties. AI-enabled virtual screening platforms can also expedite the selection of retro-inverso peptidomimetics for experimental validation. By predicting binding affinities and interactions with target receptors, AI algorithms narrow down the pool of candidates, streamlining the selection process and reducing the need for extensive experimental testing. Last but not least, AI algorithms can optimize experimental design and data analysis for phage binding assays, accelerating the identification of retro-inverso peptidomimetics that effectively compete with native peptides for receptor binding. Machine learning models can analyze assay results in real-time, guiding researchers towards promising candidates for further characterization. Integrating AI into the retroinversion pipeline, it is clear, will revolutionize peptidomimetic development and provide unprecedented efficiency and precision, and scalability. Read the full article on peptidomimetic development here >> https://lnkd.in/d9ykxYj8 #AI
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Pepticom designs (and not randomly designs) highly stable peptide drug that can remain active in the body for longer periods, increasing their bioavailability. With AI algorithms and reinforcement learning backed by laboratory synthesis, Pepticom can discover the most effective peptide sequences for specific targets, in expedited process and timeline. We are excited to be part of your journey to revolutionize peptide development with unprecedented efficiency and precision and scalability.
𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐫𝐞𝐭𝐫𝐨-𝐢𝐧𝐯𝐞𝐫𝐬𝐨 𝐩𝐞𝐩𝐭𝐢𝐝𝐞𝐬 𝐚𝐧𝐝 𝐭𝐡𝐞𝐢𝐫 𝐫𝐨𝐥𝐞 𝐢𝐧 𝐝𝐫𝐮𝐠 𝐝𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲? Peptide drugs, though often potent in their biological activities, often face hurdles such as protease degradation that reduces their half life and bioavailability. However, retro-inverso #peptides, a kind of non canonical peptides recently explored in a new article on #drugdiscovery, are a promising solution for drug developers. Retro-inverso peptides are a type of peptidomimetic using D-amino acids (retro isomers) and inverting the primary sequence of the original peptide (inverted). This dual modification creates a stable version of the peptide that is not easily recognized and broken down by biological systems. As retro-inverso peptides are more resistant to proteolytic degradation they can remain active in the body for longer periods increasing their bioavailabiity, while their unique structure can enhance binding affinity and specificity to their targets. This makes them highly interesting in drug discovery. Yet their implementation can be intricate and time-consuming. Fortunately, artificial intelligence can facilitate and expedite the process, revolutionizing peptide development. AI algorithms can analyze vast datasets of peptide sequences and structure-function relationships to design the most effective peptide sequences for specific targets, with enhanced peptide durability and absorption in the body. For example, by leveraging machine learning techniques, researchers can design shorter versions of retro-inverso peptides with optimized biological properties. AI-enabled virtual screening platforms can also expedite the selection of retro-inverso peptidomimetics for experimental validation. By predicting binding affinities and interactions with target receptors, AI algorithms narrow down the pool of candidates, streamlining the selection process and reducing the need for extensive experimental testing. Last but not least, AI algorithms can optimize experimental design and data analysis for phage binding assays, accelerating the identification of retro-inverso peptidomimetics that effectively compete with native peptides for receptor binding. Machine learning models can analyze assay results in real-time, guiding researchers towards promising candidates for further characterization. Integrating AI into the retroinversion pipeline, it is clear, will revolutionize peptidomimetic development and provide unprecedented efficiency and precision, and scalability. Read the full article on peptidomimetic development here >> https://lnkd.in/d9ykxYj8 #AI
Understanding the Structural Requirements of Peptide–Protein Interaction and Applications for Peptidomimetic Development
link.springer.com
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Methods for Identifying Ligand Binding Sites [Open Access] | https://lnkd.in/eqa8jCDn Understanding how a small molecule ligand binds to its target is valuable in drug discovery because it enables more efficient optimization through structure-based design, a better mechanistic understanding of molecular pharmacology, and greater confidence in the therapeutic hypothesis from both safety and efficacy perspectives. In this Drug Hunter Minireview, Daniel Beck and Karson Putt catalog common methods used in industry to determine or predict a ligand’s binding site, while highlighting advantages, disadvantages, and case studies, including: - X-ray analysis - cryo-EM (cryogenic electron microscopy) - competition assays - NMR (nuclear magnetic resonance) - covalent labeling - photoaffinity labeling - mutational analysis and site-directed mutagenesis - HDX (hydrogen/deuterium exchange) and chemical or proteolytic stability profiling - native mass spectrometry - computational approaches Special thanks to reviewers Pablo Martín-Gago and Ravi Kurumbail for their helpful feedback and comments to improve the article! Full article: https://lnkd.in/eqa8jCDn
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What are the top takeaways from Day 2 of the PDA - Parenteral Drug Association #visualinspection Forum? (Bonus points for identifying the happy guys in this photo.)
Day 2 top 3 key takeaways from the PDA - Parenteral Drug Association #VisualInspection Forum: 1️⃣ Automated Visual Inspection: #AI deep learning powered image analysis particle recognition is superior to conventional approaches. AI has the potential to enables a bracketing approach for product independent AVI validation. AVI training test sets and manual visual inspection baseline Knapp threshold studies are required to ensure seamless implementation and validation of AVI. #contact us if you need support Clear Solutions Laboratories. 2️⃣ Innovation in the visual inspection space remains strong, with an interesting presentation of Prof. Bruce Yu about Water Proton Nuclear Magnetic Resonance (wNMR) for Noninvasive Pharmaceutical Analysis, specifically protein particles. 3️⃣ John Shabushnig and Romain Veillon presented an inspiring conference summary and highlights from the Visual Inspection Survey 2023 confirming that visible particles remain a top reason for product recalls and lead to significant challenges during product development and commercialization. The conference was an amazing experience, definitely the place to be for visual inspection people, once again thank you very much to the planning committee, the co-chairs, all the active participants and the whole fantastic PDA crew Falk Klar, PhD, Christopher Haertig, Caroline Lynar, Melanie Decker, and Stefanie Nebelin! Congrats!
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📃Scientific paper: SUMOylation Regulates TDP-43 Splicing Activity and Nucleocytoplasmic Distribution Ref.: Springer, 2021 Abstract: The nuclear RNA-binding protein TDP-43 forms abnormal cytoplasmic aggregates in the brains of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients and several molecular mechanisms promoting TDP-43 cytoplasmic mislocalization and aggregation have been proposed, including defects in nucleocytoplasmic transport, stress granules (SG) disassembly and post-translational modifications (PTM). SUMOylation is a PTM which regulates a variety of cellular processes and, similarly to ubiquitination, targets lysine residues. To investigate the possible regulatory effects of SUMOylation on TDP-43 activity and trafficking, we first assessed that TDP-43 is SUMO-conjugated in the nuclear compartment both covalently and non-covalently in the RRM1 domain at the predicted lysine 136 and SUMO-interacting motif (SIM, 106–110 residues), respectively. By using the SUMO-mutant TDP-43 K136R protein, we demonstrated that SUMOylation modifies TDP-43 splicing activity, specifically exon skipping, and influences its sub-cellular localization and recruitment to SG after oxidative stress. When promoting deSUMOylation by SENP1 enzyme over-expression or by treatment with the cell-permeable SENP1 peptide TS-1, the cytoplasmic localization of TDP-43 increased, depending on its SUMOylation. Moreover, deSUMOylation by TS-1 peptide favoured the formation of small cytoplasmic aggregates of the C-terminal TDP-43 fragment p35, still containing the SUMO lysine target 136, but had no effe... Continued on ES/IODE ➡️ https://etcse.fr/u2CVi ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you. #amyotrophiclateralsclerosis #als #charcot
SUMOylation Regulates TDP-43 Splicing Activity and Nucleocytoplasmic Distribution
ethicseido.com
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📃Scientific paper: SUMOylation Regulates TDP-43 Splicing Activity and Nucleocytoplasmic Distribution Abstract: The nuclear RNA-binding protein TDP-43 forms abnormal cytoplasmic aggregates in the brains of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients and several molecular mechanisms promoting TDP-43 cytoplasmic mislocalization and aggregation have been proposed, including defects in nucleocytoplasmic transport, stress granules (SG) disassembly and post-translational modifications (PTM). SUMOylation is a PTM which regulates a variety of cellular processes and, similarly to ubiquitination, targets lysine residues. To investigate the possible regulatory effects of SUMOylation on TDP-43 activity and trafficking, we first assessed that TDP-43 is SUMO-conjugated in the nuclear compartment both covalently and non-covalently in the RRM1 domain at the predicted lysine 136 and SUMO-interacting motif (SIM, 106–110 residues), respectively. By using the SUMO-mutant TDP-43 K136R protein, we demonstrated that SUMOylation modifies TDP-43 splicing activity, specifically exon skipping, and influences its sub-cellular localization and recruitment to SG after oxidative stress. When promoting deSUMOylation by SENP1 enzyme over-expression or by treatment with the cell-permeable SENP1 peptide TS-1, the cytoplasmic localization of TDP-43 increased, depending on its SUMOylation. Moreover, deSUMOylation by TS-1 peptide favoured the formation of small cytoplasmic aggregates of the C-terminal TDP-43 fragment p35, still containing the SUMO lysine target 136, but had no effe... Continued on ES/IODE ➡️ https://etcse.fr/u2CVi ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you. #amyotrophiclateralsclerosis #als #charcot
SUMOylation Regulates TDP-43 Splicing Activity and Nucleocytoplasmic Distribution
ethicseido.com
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NMR Coupled with Multivariate Data Analysis for Monitoring the Degradation of a Formulated Therapeutic Monoclonal Antibody The function of a protein is directly coupled to its higher-order structure (HOS). Deviations in this critical quality attribute (CQA) may be linked to a decrease in the efficacy and/or safety of the final therapeutic product. High-resolution nuclear magnetic resonance (NMR) spectroscopy has been recently highlighted for protein HOS characterization, thanks to its ability to capture small changes at the molecular and structural levels (primary, secondary, tertiary and quaternary). The present study was carried out to demonstrate the ability of NMR (1D 1H and 2D 1H-13C experiments) coupled with multivariate data analysis (PCA and PLS regression) to monitor the degradation of a formulated mAb-like protein and for the simultaneous quantification of related CQAs, i.e., potency, purity and impurities (aggregates and fragments). The results indicate that this approach could be applied to mitigate product quality risks during development, manufacturing and stability studies of mAb therapeutics. https://lnkd.in/gZhF6uwm #aspenalert #biotech #bioprocess
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Researchers from Karlsruhe Institute of Technology (KIT) and Voxalytic GmbH have developed a new method that allows, for the first time, the elucidation of the chiral structure of molecules—the exact spatial arrangement of the atoms—by nuclear magnetic resonance (NMR) spectroscopy. This important step in the development of new drugs used to be a time-consuming process before now. The new method could now become a standard tool for the chemical and pharmaceutical industries. The research is published in Advanced Materials. The chirality of a molecule refers to its basic structure: Some molecules, so-called enantiomers, occur in pairs and are mirror images of each other. They differ in the way a left and a right glove do. Depending on whether the twisted structure of a molecule is left-handed or right-handed, its influence on biochemical and chemical reactions is different. Despite the mirror-image arrangement, the properties vary or even counteract each other. With drugs, this can have devastating consequences: When children were born with physical deformities in Germany and England in 1960, the active ingredient called Contergan or Thalidomid was the cause. The drug had been administered to pregnant women for the treatment of pregnancy disorders. It was subsequently banned. Since then, it is compulsory for pharmaceutical companies to check whether the active ingredients, which are often chiral, are not converted to their opposite enantiomer in the human body. https://lnkd.in/gPkwBXnV
Direct Chiral Discrimination with NMR
onlinelibrary.wiley.com
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𝐓𝐡𝐞𝐫𝐚𝐧𝐨𝐬𝐭𝐢𝐜𝐬 𝐌𝐚𝐫𝐤𝐞𝐭 𝐆𝐫𝐨𝐰𝐭𝐡 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 - $4.3 𝐁𝐢𝐥𝐥𝐢𝐨𝐧 𝐛𝐲 2028 Download PDF Brochure @ https://lnkd.in/ddsm9Be4 The global 𝐭𝐡𝐞𝐫𝐚𝐧𝐨𝐬𝐭𝐢𝐜𝐬 𝐦𝐚𝐫𝐤𝐞𝐭 𝐢𝐧 𝐭𝐞𝐫𝐦𝐬 𝐨𝐟 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐰𝐚𝐬 𝐞𝐬𝐭𝐢𝐦𝐚𝐭𝐞𝐝 𝐭𝐨 𝐛𝐞 𝐰𝐨𝐫𝐭𝐡 $2.1 𝐁𝐢𝐥𝐥𝐢𝐨𝐧 𝐢𝐧 2023 𝐚𝐧𝐝 𝐢𝐬 𝐩𝐨𝐢𝐬𝐞𝐝 𝐭𝐨 𝐫𝐞𝐚𝐜𝐡 $4.3 𝐁𝐢𝐥𝐥𝐢𝐨𝐧 𝐛𝐲 2028, 𝐠𝐫𝐨𝐰𝐢𝐧𝐠 𝐚𝐭 𝐚 𝐂𝐀𝐆𝐑 𝐨𝐟 15.5% from 2023 to 2028 Key market players are adopting various growth strategies to strengthen their foothold in this region. For instance, in August 2019, Eckert & Ziegler (Germany) initiated a joint venture with Chengdu New Radiomedicine Technology Co., Ltd. (China) to set up a new production facility for radiopharmaceuticals used in the treatment of hepatocellular carcinomas in China. According to an article published in the European Journal of Nuclear Medicine and Molecular Imaging 2022, by 2025, about 50 new centralized radiopharmacies will be built across China, and the availability and accessibility of radiopharmaceuticals will be significantly improved by then. Advanced Accelerator Applications , Bayer | Pharmaceuticals, GE HealthCare 𝐊𝐞𝐲 𝐌𝐚𝐫𝐤𝐞𝐭 𝐏𝐥𝐚𝐲𝐞𝐫𝐬
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Cell Sorting Magnetic Beads Nanometer-sized cell sorting magnetic beads can be used for sorting human cells by conjugating anti-human monoclonal antibodies to the magnetic beads, facilitating the sorting of target cells. These beads incubate with peripheral blood mononuclear cells (PBMCs) or bone marrow samples and undergo magnetic separation to enrich and isolate target cells, thus purifying them. VDO Biotech introduces a new series of sorting magnetic beads, including CD4, CD8, CD138, and SA sorting beads, to meet the diverse needs of customers in various scenarios. CD4/CD8 sorting beads are efficient tools for cell separation, commonly used in scientific research to precisely separate or enrich CD4+/CD8+ T cells. This technology facilitates researchers in studying the functions and mechanisms of T cell subsets in-depth. Inquire us at orders@quantobio.com
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Insilico Medicine internal AI molecular generative platform leads to the discovery of novel, orally bioavailable 3-hydroxymethyl-azetidine derivatives as potent polymerase theta inhibitors Unique structural hit identification strategy employing their Chemistry42 platform and structure-based drug design identified the initial hits(A7, B3), which upon H2L optimization led to metabolically stable deuterated compound C1, exhibiting promising drug-like properties, e.g. solubility, permeability, and metabolic stability. C1 exhibits significant antiproliferative properties in DNA repair-compromised cells and demonstrates favorable pharmacokinetics, showcasing that 3-hydroxymethyl-azetidine is an effective bio-isostere of pyrrolidin-3-ol as in the initial hit. https://lnkd.in/gNh47bXu
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