A study of two enzymes in the brain reveals new insights into how redox reactions regulate the activity of protein kinases.
eLife Sciences Publications, Ltd.’s Post
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In this study, they demonstrated how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments
New High-Throughput, AI-Based, Protein Prediction Method May Advance Drug Discovery
genengnews.com
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Add Proximity Proteomics to your studies! An “off the shelf” solution using bait-specific antibodies of your choice. Purify with streptavidin beads.
Protein A-Turbo - Proximity Biotinylation Enzyme | Sigma-Aldrich
sigmaaldrich.com
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The lab of Daniel P. Mulvihill has described a novel tag known as the vesicular nucleating peptide (VNp) that packages a fusion protein of interest into membrane vesicles for cellular export. VNp was demonstrated to dramatically increase the total yield of multiple proteins. For example, the yield of soluble DARP was increased from 32 to 2194 mg/L upon fusion to VNp6. Oftentimes research groups will just slap new tags onto a single, super-stable protein (e.g., GFP) to show proof of concept and call it a day. Eastwood et al. (2023) stated that the use of their VNp "...resulted in significant increase[s] in yield and solubility for each of the proteins we have tested to date (n > 60)." That is an impressive number of proteins to test a new tag with! Of course, there may be protein-dependent issues for using the VNp. If your protein is toxic, oligomerizes, or contains disulfide bonds then the vesicle may be retained in the cytoplasm. Even so, such proteins were found to still have "improved expression and/or functionality". From a biomanufacturing perspective, the VNp tag stands to greatly simplify and improve protein purification workflows. I can also imagine other fun ways one could hypothetically exploit the VNp. Imagine you designed an RNA aptamer that binds to the VNp. Could you transcribe an mRNA containing the aptamer and selectively package it into the vesicles? Give the paper a read!
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Source: Journal of proteome research A new method using parallel reaction monitoring (PRM) and microflow LC-MS has been developed for high-throughput glycan profiling of human serum IgG subclasses. This method allows for the quantification of Fc glycopeptides and distinguishes between IgG3 and IgG4 without the need for further enrichment. The method has been shown to effectively monitor the relative levels of 13 representative glycoforms with good detection limits for individual IgG subclasses.
High-Throughput Glycan Profiling of Human Serum IgG Subclasses Using Parallel Reaction Monitoring Peptide Bond Fragmentation of Glycopeptides and Microflow LC-MS
pubmed.ncbi.nlm.nih.gov
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Deep Profiling of human plasma proteoform from Prof. Kelleher. 2841 proteoforms from 114 protein, a good example to show the complexcity of proteoform and the importence of TDS
Deep Profiling of Plasma Proteoforms with Engineered Nanoparticles for Top-Down Proteomics
pubs.acs.org
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Contact us to learn why we think ASMS is better than DEL Screening. Learn more about ASMS: https://lnkd.in/eyVezE9i Contact us through this link: https://lnkd.in/e6GFCEvW Why ASMS is better than DEL Screening 1) Compatible with protein/protein and protein/oligonucleotide complexes. Screen helicases, transcription factors, and RNA modifying enzymes with ease. 2) Low protein/RNA usage; typically, less than 1 mg for a 100K screen. 3) Hits are immediately available for confirmation and follow-up. No need to synthesize and purify unlabeled compounds. 4) Solution phase assay without limitations on target size. No need to immobilize the target on a surface or bead. 5) Screen native & unlabeled targets and test compounds. No need for oligo barcodes. 6) ASMS uses rule-of-five compliant drug-like molecules instead of combichem. #massspectrometry #bindingassay #highthroughputscreening #drugdiscovery #ASMS #momentumbiotechnologies #momentum
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At long last, the latest version of AlphaFold - AlphaFold 3 is out. This promises to model protein, nucleic acid, and small molecule complexes. https://lnkd.in/gNPXQYGg As of now, it is Beta. It can only be run on a Deepmind server that has many restrictions, such as runs per day, limits on molecules per day, only a few ligands supported, no commercial entity access. The code is also not public. Still, from my early trials it is promising - I modelled a heterohexamer (3 protein) complex, 3700 total amino acids, plus 120 bp of DNA in only about 15 minutes. Ran a kinase and it modeled ATP well, modeled an enzyme with FAD and NADH co-factors and they were also modeled well. These need experimental validation so time will tell how accurate it is. Have you ran it yet?
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In this 2022 paper "In silico identification of a β2-adrenoceptor allosteric site that selectively augments canonical β2AR-Gs signaling and function", SILCS was used to identify a novel allosteric site on the β2-adrenoceptor. This allows for selective enhancement of β2AR-Gs signaling, offering potential for targeted therapeutic interventions with fewer side effects. This study shows the applicability of SILCS to membrane proteins, as protein flexibility is taken into account during the simulations." #compchem #SILCS #membraneproteins
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Interesting in learning updated research in protein arginine methylation? You still have time to register the FASEB catalyst conference on protein arginine methylation. We have great speakers lined up. https://lnkd.in/gKKYVUFc
Protein Arginine Methylation: Function and Therapeutics
faseb.org
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Studying #protein #oligomerisation. Learn from this new publication how NanoTemper Technologies spectral shift affinity measurement can provide you with binding data on protein-protein interactions (#PPI). In this study, isothermal spectral shift binding data was used to analyse PRMT1 protein self-association identifying a model in which it exists as monomers, dimers, and tetramers.
Oligomerization of protein arginine methyltransferase 1 and its effect on methyltransferase activity and substrate specificity
onlinelibrary.wiley.com
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