Recent Innovations in Biochemical Research

Quite a nice (and updated) review -RNA therapeutics and LNPs for extrahepatic delivery LNPs have become a cornerstone in delivering RNA therapeutics, successfully used in mRNA vaccines and gene therapies. Despite their success, LNPs' tendency to preferentially accumulate in the liver remains a critical limitation. This liver tropism hinders their effectiveness in treating diseases in other organs, such as the lungs, brain, and pancreas. 🔬 Recent research has made significant strides in re-engineering LNPs to deliver RNA to organs beyond the liver. One approach is to adjust the composition of LNP formulations, either by adding a cationic lipid (like DOTAP) or replacing the ionizable lipid's ester linkers with amide linkers. These modifications change the physicochemical properties of LNPs, influencing the biomolecular corona that forms post-administration, which ultimately determines organ-specific targeting. For instance, lung-targeted LNPs can transfect up to 65% of endothelial cells and 40% of epithelial cells in the lungs, demonstrating a potential breakthrough for treating pulmonary diseases like cystic fibrosis and pulmonary fibrosis. Spleen-specific delivery has been achieved by incorporating anionic lipids, enabling the targeting of immune cells like macrophages and T cells, essential for in vivo immunotherapy applications. Meanwhile, LNPs designed for bone marrow delivery are showing promise in treating hematopoietic disorders like sickle cell disease. 🧠 Still, delivering RNA to the brain remains a considerable challenge (you know, the usual BBB). However, promising strategies, like adding neurotransmitter-derived lipids to LNP formulations, are showing early success in crossing this barrier, paving the way for treating neurological diseases. 🎯 As we look to the future, designing LNPs that can target specific cell types and improve safety profiles is paramount. Advances in overcoming physiological barriers, such as the BBB and tissue-specific targeting, will revolutionize how we approach gene therapies for previously untreatable conditions. From organ-selective LNPs to fine-tuned biomolecular coronas, the future of RNA delivery is more promising than ever. Learn more here: https://lnkd.in/ecQjkNaq #Nanomedicine #LipidNanoparticles #GeneTherapy #RNA #BiotechInnovation #TargetedDelivery #DrugDelivery

Excited to report that we have discovered a new, endogenous molecular clock in unmodified human cells and tissues. It is ticking away right now in almost every cell in your body. Paper here: https://lnkd.in/gNDdeghA Specifically, in a new paper on BioRxiv, we show that RNA editing by the near-ubiquitous ADAR1 in unmodified human cells is sufficient to allow us to infer the ages of thousands of species of RNA. This provides a new way to infer past transcriptional dynamics, without any metabolic labeling or genetic engineering, in anything from cultured cells to patient biopsies. Work by Ali Ghareeb, James Bayne, Aaron Wagen, and others, and funded by Lada Nuzhna's Impetus Grants, along with generous support from Eric and Wendy Schmidt!

In the past month, new tools have improved protein design, benchmarking, and refinement, showing both progress and areas for improvement. ▪️ Proteína by NVIDIA is a flow-based generative model for de novo protein backbone design, trained on 21 million AlphaFold structures. Its 400M-parameter transformer supports C.A.T.H. conditioning, classifier-free guidance, and autoguidance for precise structure control. Proteína generates proteins up to 800 residues, outperforming RFdiffusion and Genie2 in scale and accuracy. ▪️ MotifBench is a comprehensive benchmark for evaluating motif-scaffolding methods in protein design. Featuring 30 challenging test cases from the Protein Data Bank, it provides a standardized evaluation pipeline and identifies key limitations in methods like RFdiffusion, highlighting the need for more advanced approaches. ▪️ ROCKET enhances AlphaFold2’s protein structure predictions by integrating experimental data from X-ray, cryo-EM, and cryo-ET without requiring retraining. It refines large structural changes, improves accuracy at low resolution, and allows automated, experiment-guided model building. At RECEPTOR.AI, we're closely following these innovations while recognizing their dependence on high-quality data. Rather than relying solely on model adjustments, we emphasize integrating experimental insights and physics-informed approaches with AI. This combined strategy helps overcome current limitations and accelerates meaningful advances in protein design and drug discovery. GIF credit: Ian Haydon / Institute for Protein Design (via MIT News) #ai #ml #artificialintelligence #biotech #drugdiscovery

This week, I’m excited to highlight two recent breakthroughs in CRISPR research that caught my attention: 🩺 BEAM Therapeutics' Phase 1 clinical data for BEAM-302: This novel base-editing therapy uses a Cas9-deaminase fusion to precisely target and correct the PiZ mutation responsible for alpha-1 antitrypsin deficiency (AATD). Patients received escalating doses (15, 30, and 60 mg) to evaluate in vivo editing efficiency. Remarkably, at the highest dose (60 mg), BEAM-302 increased total AAT levels from 4.4 µM to 12.4 µM, clearly surpassing the therapeutic threshold of 11 µM. Importantly, the treatment was well-tolerated, highlighting its potential as an effective genetic correction strategy for patients. While base editors can introduce unintended edits, these initial results are highly promising. I’ll be watching closely as PRIME Medicine also enters this space with RT-based editors, potentially offering enhanced precision. See these results here: https://lnkd.in/gQXZ-5JS 🧬 Innovative research from the labs of Dave Savage and Jennifer Doudna (co-founders of Scribe Therapeutics) Their recent preprint, “Latent activity in TnpB revealed by mutational scanning,” provides an outstanding example of engineering CRISPR enzymes from modest baseline activity to high efficiency. TnpB, a compact RNA-guided nuclease and evolutionary ancestor of Cas12, was systematically improved using deep mutational scanning and yeast-based potency assays. The researchers identified specific mutations dramatically enhancing TnpB’s nuclease activity. By combining several beneficial mutations, they created an optimized “enhanced TnpB” variant, achieving up to 50-fold increased activity in plant systems —a reasonably respectable 🤯 leap in enzyme efficiency. This research is a fantastic showcase of how systematic mutational scanning and combinatorial engineering can substantially enhance CRISPR enzyme performance—an approach we regularly utilize at Scribe Therapeutics to rapidly building powerful new genome-editing tools with improved therapeutic characteristics. Check it out: https://lnkd.in/gnbdhjGq. Why I like this work: beyond showcasing TnpB as an exciting new small CRISPR enzyme, this study provides a clear playbook for modern molecular engineering. Comparing this work with others in the field, it is clear that comprehensive mapping of protein & RNA variants can surpass the effectiveness of both targeted mutagenesis and assay-naïve AI strategies. Plus it's just more fun! Check out these results here: https://lnkd.in/gnrabq_8 Together, these studies reflect the ongoing, vibrant evolution of CRISPR technology, driven by thoughtful scientific and engineering approaches.

Technological Innovations in Glycosylation Technological innovations in glycosylation research have greatly advanced our understanding and manipulation of glycan structures, opening new possibilities for both basic science and therapeutic applications. One of the most transformative innovations is glycoengineering, in which tools such as CRISPR/Cas9 are used to precisely edit genes involved in glycosylation pathways. This allows for targeted modifications of glycosylation patterns in proteins, enabling the creation of optimized therapeutic proteins with enhanced efficacy and reduced immunogenicity. Another key innovation has been the development of high-throughput glycan profiling platforms. These technologies, including glycan microarrays and advanced mass spectrometry methods, enable rapid and comprehensive analysis of glycan structures. These tools have accelerated research by allowing large-scale screening of glycan-protein interactions, leading to the discovery of new glycan biomarkers and therapeutic targets. Advances in synthetic biology have also contributed to the field, particularly through the development of microbial systems designed to produce human-like glycosylation patterns. These systems provide a more consistent and scalable approach to producing glycosylated biopharmaceuticals, thereby reducing costs and increasing the availability of glycoengineered therapeutics. Additionally, computational approaches, including machine learning and artificial intelligence (AI), are being integrated into glycoscience to predict glycosylation patterns and their biological effects. These techniques pave the way for the design of more effective sugar-based drugs and personalized medicine. Overall, these technological innovations are driving significant advances in glycosylation research, enabling more precise control of sugar structures and expanding the potential for therapeutic development. Reference [1] Mengyuan He et al., Signal Transduction and Targeted Therapy 2024 (https://lnkd.in/e_smSGsu) [2] Haining L et al., Biotechnology Advances 2022 (https://lnkd.in/epGg7hFJ) [3] Leva Bagdonaite et al., Nature Reviews Methods Primers 2022 (https://lnkd.in/eZmDTHHy) #Glycosylation #GlycoEngineering #CRISPR #Glycomics #Glycoproteomics #Biotechnology #AI #MachineLearning #Bioprocessing #Biotherapeutics #BiomedicalInnovation