Cradle’s Post

Last week, Cradle announced their $73M Series B to further expand their AI-enabled protein engineering platform. So far, they’ve partnered with 21 customers and achieved cost reductions of up to 90% on R&D projects. On this week’s Vital Signs, I sat down with Cradle’s Co-Founder & CEO, Stef van Grieken. We discuss how Cradle plans to use the new funding, what’s been happening in AI x bio, the technical underpinnings of Cradle’s platform, and more. Some highlights: 🧪 The current state & future of AI x bio Stef says that we’re still in the early stages of AI x bio. He highlights three areas where AI can play an important role: 1) hit identification for easy targets via novel binders 2) structural de novo models where researchers have some understanding of the target but want to generate some variance 3) multi-property optimization to learn from experimental results and reduce the number of experimental cycles needed. Stef advocates for more experimental context in models and better benchmarks that are relevant to bio. He also talks about how the valuable datasets in bio are kept private, meaning the public datasets are inherently less valuable, which might bias models towards irrelevant directions.  🧪 How Cradle designs their models Stef shares how their foundation model has two major components: 1) A predictor component which has some knowledge of properties (e.g., stability, expression), works decently well in zero-shot, and sees all of the assay data. 2) A generator to search the local search space and is conditioned to understand the relevant domain (e.g., providing evolutionary information, providing some labeled data without leaking too much). Stef mentions that it’s easy to go out of domain in biology given the sparsity of data, so Cradle has invested significantly in model confidence around generated sequences.  🧪 What’s next for Cradle Stef explains Cradle’s three goals: 1) Most protein models to date are assuming a fixed vocabulary with natural amino acids, but Cradle wants to also represent non-natural ones. 2) Models are currently effective at optimizing a protein construct once a user has properly formatted it. Stef hopes to have models reformat from large libraries – e.g., generating a bispecific antibody instead of configuring from the individual components. 3) Cradle plans to do more zero-shot learning on their panel of assays in areas like immunogenicity. An insightful discussion on all things AI x bio! Listen to the full episode below: Spotify: https://bit.ly/3D0Cy20 Apple: https://bit.ly/3ZiSyDZ

🎯 Protein Production Tips – Part 18: 𝐏𝐫𝐨𝐭𝐞𝐢𝐧 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐢𝐧 𝐌𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐂𝐞𝐥𝐥𝐬 – 𝐅𝐚𝐬𝐭? 𝐀 𝐖𝐞𝐞𝐤? I know many of us rely on 𝐄. 𝐜𝐨𝐥𝐢 as the go-to expression system—and when it works, I’m fully on board. After all, with E. coli, you can go from plasmid to protein in just 3 days. But let’s face it: many challenging proteins—especially those requiring post-translational modifications (PTMs)—simply demand a eukaryotic system. And for me, mammalian expression, particularly in HEK cells, is the way to go. ✨ 𝐌𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧: 𝐅𝐚𝐬𝐭𝐞𝐫 𝐓𝐡𝐚𝐧 𝐘𝐨𝐮 𝐓𝐡𝐢𝐧𝐤 Let’s focus on secreted proteins first. It might sound ambitious, but with good planning and attention to detail, you can go from gene to purified protein in 1 week. Here’s how: 1️⃣ Day 1: Clone your gene of interest. 2️⃣ Day 2: Perform a midiprep. 3️⃣ Day 3: Start the transient transfection. 4️⃣ Express for 3–4 days, and voila—protein ready for purification. Sounds fast, right? It’s totally achievable if you plan well and execute carefully. 💡 𝐖𝐡𝐚𝐭 𝐀𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐂𝐨𝐬𝐭? There’s a misconception that mammalian expression is expensive, but it’s not as bad as you think: Using the MEXI system, you pay ~120 €/L. With flasks, PEI, and setup, you can easily express protein in 100 mL for less than 50 €. And the quality? It’s hard to beat—your protein will have all the required PTMs (glycosylation, disulfide bonds, etc.) and behave as it should in downstream assays. ✅ Pro Tip: Using the Twin-Strep tag for secreted proteins will save you a lot of trouble. 🔬 𝐓𝐡𝐞 𝐇𝐚𝐫𝐝 𝐏𝐚𝐫𝐭? 𝐈𝐭’𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐃𝐞𝐬𝐢𝐠𝐧. After expressing more than 100 proteins in mammalian systems, I can confidently say the most challenging part isn’t the cell culture or transfection—it’s the construct design. 𝐊𝐞𝐲 𝐜𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: Promoter choice Signal sequence for secretion Affinity tag selection The plasmid system you’re using Master these, and you’ll unlock the full potential of mammalian expression. 💬 𝐘𝐨𝐮𝐫 𝐓𝐮𝐫𝐧! Have you explored mammalian expression systems for your proteins? What’s your go-to approach, and how do you plan for speed and efficiency? Share your thoughts and challenges in the comments! 👉 Stay tuned! In the coming days, I’ll dive deeper into mammalian expression, covering promoters, signal sequences, and affinity tags to help you optimize your workflows. #BiotechTips #LabTips #ScienceMatters #30daysProteinPurification #MammalianExpression ___________ 🚀 I’m Nikolay – 𝗔 𝗥𝗲𝗹𝗲𝗻𝘁𝗹𝗲𝘀𝘀 𝗘𝘅𝗽𝗹𝗼𝗿𝗲𝗿 𝗼𝗻 𝘁𝗵𝗲 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿 𝗼𝗳 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗗𝗲𝘀𝗶𝗴𝗻, 𝗟𝗮𝗯 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰𝘀 🚀 Driven by an unquenchable curiosity, I’m passionately dedicated to pioneering the latest techniques and innovations in protein design. If you like my content, please click my name and follow me. Do not forget to ring the 🔔. Image source: IBA Lifesciences

🎯 Protein Production Tips – Part 30: 𝐈𝐭’𝐬 𝐄𝐚𝐬𝐲 𝐭𝐨 𝐌𝐮𝐭𝐚𝐭𝐞, 𝐁𝐮𝐭 𝐈𝐬 𝐈𝐭 𝐒𝐭𝐢𝐥𝐥 𝐭𝐡𝐞 𝐒𝐚𝐦𝐞 𝐏𝐫𝐨𝐭𝐞𝐢𝐧? For this final post, I want to share an important lesson from one of the projects. I’ve worked on—a lesson that has stuck with me ever since. When studying protein-protein interactions (PPIs), the workflow seems straightforward: Purify the complex Solve the structure Identify the interface Mutate the residues to disrupt the interaction Sounds simple, right? Well, not quite. 💡 𝐓𝐡𝐞 𝐇𝐢𝐝𝐝𝐞𝐧 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐨𝐟 𝐌𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐬 While mutations can abolish a specific interaction, they might also have unintended effects. A mutation designed to block binding could inadvertently affect protein stability, folding, or overall structure. This means that in vitro or in vivo outcomes attributed to the disrupted interaction could instead be the result of a destabilized protein. ✨ 𝐀 𝐑𝐞𝐚𝐥-𝐋𝐢𝐟𝐞 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 I remember working on a project where everything looked perfect at first glance. The SDS-PAGE results showed WT and MUT proteins looked identical. “No worries,” right?. But the moment I ran the proteins through nanoDSF, the story changed. The mutant’s behavior was completely different—it wasn’t just about the interaction anymore; the protein itself had fundamentally changed. It’s not enough to assume mutations are solely affecting interactions—they can have far-reaching effects that are easy to overlook without proper quality control (QC). 💡 𝐇𝐨𝐰 𝐭𝐨 𝐄𝐧𝐬𝐮𝐫𝐞 𝐌𝐮𝐭𝐚𝐧𝐭𝐬 𝐌𝐢𝐦𝐢𝐜 𝐭𝐡𝐞 𝐖𝐓 𝐏𝐫𝐨𝐭𝐞𝐢𝐧? 1️⃣ Start with nanoDSF (for example Panta, my favorite device by NanoTemper Technologies) It’s a quick, reliable way to assess protein stability and folding. If the Tm is drastically different from WT, your mutant might have broader issues. 2️⃣ Compare Biophysical Properties Use other techniques like SEC-MALS or CD spectroscopy to confirm the mutant mirrors the WT protein’s behavior. 3️⃣ Validate Functionality ✨ 𝐓𝐚𝐤𝐞-𝐇𝐨𝐦𝐞 𝐌𝐞𝐬𝐬𝐚𝐠𝐞 Don’t rely solely on gels or initial results—dig deeper with biophysical assays to understand what’s really happening. It’s these small checks that ensure your conclusions are solid and your data is reproducible. 💬 𝐘𝐨𝐮𝐫 𝐓𝐮𝐫𝐧! Have you ever encountered surprising results with protein mutants? How do you ensure your mutants truly mimic WT properties? Let’s discuss your insights and experiences in the comments! #ProteinPurification #BiotechTips #LabTips #ScienceMatters #30daysProteinPurification 🚀 I’m Nikolay– 𝗔 𝗥𝗲𝗹𝗲𝗻𝘁𝗹𝗲𝘀𝘀 𝗘𝘅𝗽𝗹𝗼𝗿𝗲𝗿 𝗼𝗻 𝘁𝗵𝗲 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿 𝗼𝗳 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗗𝗲𝘀𝗶𝗴𝗻, 𝗟𝗮𝗯 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰𝘀 🚀 Driven by an unquenchable curiosity, I’m passionately dedicated to pioneering the latest techniques and innovations in protein design. If you found this post helpful, please share it with your network! ♻️ Feel free to click my name and follow me.

🎯 Protein Production Tips 𝐏𝐚𝐫𝐭 12: 𝐈𝐧𝐬𝐞𝐜𝐭 𝐂𝐞𝐥𝐥 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 – 𝐌𝐮𝐥𝐭𝐢𝐁𝐚𝐜, 𝐏𝐞𝐫𝐟𝐞𝐜𝐭 𝐟𝐫𝐨𝐦 𝐒𝐢𝐧𝐠𝐥𝐞 𝐏𝐫𝐨𝐭𝐞𝐢𝐧𝐬 𝐭𝐨 𝐌𝐮𝐥𝐭𝐢𝐦𝐞𝐫𝐢𝐜 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐞𝐬 I remember vividly the time I set up the insect expression system in my PhD lab. Working on a big multimeric complex (10 subunits), I needed a system that could handle co-expression of subcomplexes or even the entire assembly. Enter MultiBac, an elegant system developed by Imre Berger’s lab, which was a game-changer. 💡 𝐖𝐡𝐲 𝐌𝐮𝐥𝐭𝐢𝐁𝐚𝐜 𝐒𝐭𝐚𝐧𝐝𝐬 𝐎𝐮𝐭 The MultiBac system enabled seamless cloning and co-expression: It allowed cloning of two genes in opposite directions under the control of polh and p10 promoters—a feature seen in other systems. 𝐁𝐮𝐭 𝐭𝐡𝐞 𝐮𝐧𝐢𝐪𝐮𝐞 𝐭𝐰𝐢𝐬𝐭? 𝐓𝐡𝐞 𝐦𝐮𝐥𝐭𝐢𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐮𝐥𝐞! Using restriction sites like BstZ17I, SpeI, ClaI, and NruI, compatible with PmeI and AvrII, you could cut out an expression cassette from one plasmid and integrate it into another. This process let you create a single plasmid capable of expressing up to four proteins. Repeat the process, and you could clone all your genes into one expression system! 𝐓𝐡𝐞 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐰𝐚𝐬 𝐬𝐭𝐫𝐚𝐢𝐠𝐡𝐭𝐟𝐨𝐫𝐰𝐚𝐫𝐝: 1️⃣ Transform the final plasmid into DH10MultiBac cells containing the Bacmid. 2️⃣ Perform a blue-white screening to identify recombinant clones. 3️⃣ Extract the Bacmid, produce the baculovirus, and step by step, express your protein. ✨ 𝐎𝐭𝐡𝐞𝐫 𝐈𝐧𝐬𝐞𝐜𝐭 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐨 𝐊𝐧𝐨𝐰 While MultiBac excels at handling large complexes, it’s not the only option. Here are some other systems widely used in the field: 1️⃣ Bac-to-Bac System (Thermo Fisher Scientific) 2️⃣ FlashBAC System (Oxford Expression Technologies) 3️⃣ Which other do you know? Regarding the cell lines, you could use the following: - Sf9 cells - Sf21 cells - High Five (Tn5) cells I had the chance to use all 3 for different projects. 💡 𝐂𝐡𝐨𝐨𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐢𝐠𝐡𝐭 𝐒𝐲𝐬𝐭𝐞𝐦 Your choice of system depends on your project: For large multimeric complexes, MultiBac shines with its modularity. For single proteins or simpler co-expressions, Bac-to-Bac or FlashBAC might suffice. 💬 𝐘𝐨𝐮𝐫 𝐓𝐮𝐫𝐧! Have you worked with insect cell expression systems? Which one do you prefer, and what were the biggest challenges you faced? Let’s discuss in the comments! #ProteinPurification #BiotechTips #LabTips #ScienceMatters #30daysProteinPurification #InsectCellExpression --------- 🚀 I’m Nikolay – 𝗔 𝗥𝗲𝗹𝗲𝗻𝘁𝗹𝗲𝘀𝘀 𝗘𝘅𝗽𝗹𝗼𝗿𝗲𝗿 𝗼𝗻 𝘁𝗵𝗲 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿 𝗼𝗳 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗗𝗲𝘀𝗶𝗴𝗻, 𝗟𝗮𝗯 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰𝘀 🚀 Driven by an unquenchable curiosity, I’m passionately dedicated to pioneering the latest techniques and innovations in protein design. If you like my content, please click my name and follow me. Do not forget to ring the 🔔.

🎯 Protein Production Tips – Part 10: 𝐈𝐬 𝐂𝐥𝐨𝐧𝐢𝐧𝐠 𝐄𝐧𝐨𝐮𝐠𝐡 𝐭𝐨 𝐆𝐞𝐭 𝐨𝐧 𝐚 𝐂𝐞𝐥𝐥 𝐏𝐚𝐩𝐞𝐫? The answer is 𝐘𝐄𝐒—if that cloning is particularly challenging! 💡 𝐓𝐡𝐞 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: 𝐂𝐥𝐨𝐧𝐢𝐧𝐠 𝐚 𝐑𝐞𝐬𝐭𝐫𝐢𝐜𝐭𝐢𝐨𝐧 𝐄𝐧𝐳𝐲𝐦𝐞 The project focused on DNA-damage repair and the role of RNase H. As part of the study, a restriction enzyme had to be cloned into a yeast expression vector. Sounds straightforward, right? Not so fast. Restriction enzymes are highly toxic to cells, and even the tiniest leakage in expression can spell disaster. For over a year, attempts to clone the enzyme failed. Mutations in the ORF (open reading frame) were consistently observed, leading to doubts about the quality of the gene blocks. 💡 𝐇𝐨𝐰 𝐈 𝐒𝐨𝐥𝐯𝐞𝐝 𝐈𝐭: 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐃𝐨𝐭𝐬 When asked to take on this challenge, I was thrilled—it was a chance to tackle a seemingly impossible problem. Here’s how I cracked it in just one week: 1️⃣ 𝐂𝐥𝐮𝐞 1: The “Red Glow” in Another Project At the time, I was working on cloning tdTomato into a yeast vector. Interestingly, positive clones developed a reddish hue even in bacterial colonies. This puzzled me until I realized: Eukaryotic promoters, like the yeast promoter, are leaky in E. coli. 2️⃣ 𝐂𝐥𝐮𝐞 2: Toxicity and Mutation Patterns In the failed attempts to clone the restriction enzyme, all observed mutations were frameshifts. Sequencing confirmed the input gene blocks were intact, but any clone that survived had mutated the ORF—clear evidence of strong selection pressure from leaky expression. 3️⃣ 𝐂𝐥𝐮𝐞 3: A Hidden Gem in a Methods Section In a paper on yeast gene tagging, the authors described a similar cloning challenge with Cre recombinase. Their solution? Adding a short intron to disrupt the ORF in bacteria, which was correctly spliced in yeast, allowing proper expression. ✨ 𝐓𝐡𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧 By combining these clues, I cloned the restriction enzyme successfully: I added a short intron at the start of the gene to disrupt its ORF in bacteria. The gene remained functional in yeast, where the intron was correctly spliced, allowing the enzyme to be expressed without issues. 💬 𝐘𝐨𝐮𝐫 𝐓𝐮𝐫𝐧! Have you ever faced a cloning nightmare? Did you find a creative solution, or did you discover new methods along the way? Share your stories in the comments! #ProteinPurification #BiotechTips #LabTips #ScienceMatters #30daysProteinPurification #CloningTips 🚀 I’m Nikolay – 𝗔 𝗥𝗲𝗹𝗲𝗻𝘁𝗹𝗲𝘀𝘀 𝗘𝘅𝗽𝗹𝗼𝗿𝗲𝗿 𝗼𝗻 𝘁𝗵𝗲 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿 𝗼𝗳 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗗𝗲𝘀𝗶𝗴𝗻, 𝗟𝗮𝗯 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰𝘀 🚀 Driven by an unquenchable curiosity, I’m passionately dedicated to pioneering the latest techniques and innovations in protein design. If you like my content, please click my name and follow me. Do not forget to ring the 🔔.

I love this post from Nikolay Dobrev discussing the power of cell free protein expression! Network, ping me if you ever want to learn how Nuclera enables rapid protein expression screening and can help you go from DNA to soluble protein in hand in 48 hours. #ivtt #cellfree #proteinexpression #CFPS #drugdiscovery

Has protein binder design been solved? We analyze the results of our protein design competition where 130 designers created binders for EGFR. With a 5x improvement in success rates and some designs outperforming clinical antibodies, we explore what worked, what didn't, and what this means for the future of protein engineering. https://lnkd.in/eUYTQaqM TLDR: Not yet — but the rate of progress in protein engineering is astounding. Within just a few months from Round 1 (September) to Round 2 (December), we witnessed dramatic improvements in expression and binding success rates, along with a surge in participation from the protein design community. Generating soluble proteins – those that express and fold well – seems to be essentially solved, at least in our small-scale bacterial cell-free expression systems. The next challenge here will be to figure out how to translate expression between different organisms to ensure high production yields in larger reactions so that all those novel proteins can be put to good use outside of lab-scale testing. Luckily, people are already thinking about generating datasets for predictive models of expression like e.g. at Align to Innovate. Optimization of existing binders is proving remarkably effective and can systematically yield better proteins than previous candidates. Cradle's success in this competition demonstrates how this approach is now being rapidly industrialized and we hope many applications can benefit from such tools. In de novo design, BindCraft has brought about a significant increase in success rates and has immediately been adopted by the protein design community. It remains to be seen whether this represents a broader shift toward hallucination models outperforming diffusion approaches, or if the next generation of diffusion models will shift the meta back. Both in this competition and across the field, we still struggle to predict binding success through computational metrics. This gap between the ability to generate candidates and predict their performance represents one of the field's most pressing challenges and we need to generate more data to build better models here. Thanks again to all participants for making this competition an immense success through sharing your cool designs and interesting approaches. We have exciting plans for 2025 and can't wait to see what kinds of proteins you'll design next.

🎯 Protein Production Tips – Part 29: 𝐍𝐨 𝐂𝐞𝐥𝐥𝐬, 𝐍𝐨 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 – 𝐓𝐡𝐞 𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐂𝐞𝐥𝐥-𝐅𝐫𝐞𝐞 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 In the world of protein production, the saying “no cells = no expression” no longer holds true. Enter cell-free expression systems, where the magic of protein synthesis happens without the need for living cells. ✨ 𝐖𝐡𝐚𝐭 𝐈𝐬 𝐂𝐞𝐥𝐥-𝐅𝐫𝐞𝐞 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧? Cell-free expression systems use the molecular machinery of protein synthesis (e.g., ribosomes, tRNAs, enzymes) extracted from cells to produce proteins in vitro. Instead of growing and lysing cells, you add your DNA or mRNA template directly to a prepared mix—and voila, protein production begins in hours! 💡 𝐖𝐡𝐲 𝐆𝐨 𝐂𝐞𝐥𝐥-𝐅𝐫𝐞𝐞? 1️⃣ Speed Forget multi-day growth and expression workflows. Most cell-free systems can produce proteins in a matter of hours, making them ideal for rapid prototyping. 2️⃣ Flexibility Cell-free systems are compatible with toxic, unstable, or hard-to-express proteins that traditional systems struggle with. 3️⃣ Customization Easily incorporate non-standard amino acids, perform site-specific labeling, or produce membrane proteins with nanodiscs in one step. Pro Tip: you can use the CFS for small scale (50 µL reaction) HT expression. Think about 10 x 96 well plates, or why not more... ⚠️ The Challenges 1️⃣ Cost Cell-free systems are expensive compared to traditional expression. The need to reduce costs is critical for their broader adoption. 2️⃣ Yield While excellent for rapid production, current systems don’t yet match the large-scale yields of bacterial or mammalian systems. ✨ Leading Players in the Cell-Free Revolution Here are some innovators shaping the field: ALiCE by LenioBio A robust eukaryotic (plant) cell-free system, excelling in producing glycosylated proteins. SYNTHELIS Specializing in membrane proteins and nanodiscs for functional studies. Invitris A leader in developing scalable cell-free platforms for diverse applications. Nuclera The only end-to-end protein prototyping system that accelerates construct design, expression, solubility characterization and purification of target proteins in drug discovery programs. 💬 𝐘𝐨𝐮𝐫 𝐓𝐮𝐫𝐧! Have you tried a cell-free expression system? What’s your experience—pros, cons, or game-changing moments? Share your thoughts in the comments! #ProteinPurification #BiotechTips #LabTips #ScienceMatters #30daysProteinPurification #CellFreeExpression 🚀 I’m Nikolay – 𝗔 𝗥𝗲𝗹𝗲𝗻𝘁𝗹𝗲𝘀𝘀 𝗘𝘅𝗽𝗹𝗼𝗿𝗲𝗿 𝗼𝗻 𝘁𝗵𝗲 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿 𝗼𝗳 𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗗𝗲𝘀𝗶𝗴𝗻, 𝗟𝗮𝗯 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝗵𝗲𝗿𝗮𝗽𝗲𝘂𝘁𝗶𝗰𝘀 🚀 Driven by an unquenchable curiosity, I’m passionately dedicated to pioneering the latest techniques and innovations in protein design. If you found this post helpful, please share it with your network! ♻️ Feel free to click my name and follow me.

This feels revolutionary and interesting simultaneously

21 proteinogenic amino acids organized into categories 🔬 Building Blocks of Life: The Proteinogenic Amino Acids 🧬 In the fascinating world of biochemistry, amino acids stand out as the fundamental building blocks of proteins. These small molecules combine in myriad ways to form proteins, which perform a plethora of functions essential to life. The image showcases the 21 proteinogenic amino acids found in eukaryotes, artfully categorized based on their side chain properties. Let's delve into these categories and appreciate the diversity they offer! 🌟 1. Hydrophobic Sidechains 🌊: - These amino acids, including L-Alanine, L-Phenylalanine, and L-Valine, possess non-polar side chains that shy away from water. Their hydrophobic nature often positions them within the core of proteins, stabilizing the structure. 2. Polar Neutral Sidechains💧: - Comprising L-Serine, L-Threonine, and others, these amino acids have side chains that engage in hydrogen bonding. They are polar but uncharged, often found on protein surfaces interacting with the aqueous environment. 3. Unique Sidechains 🌟: - L-Cysteine, Glycine, L-Proline, and L-Selenocysteine are hard to pigeonhole due to their unique properties. For instance, L-Cysteine can form disulfide bonds, crucial for protein stability, while Glycine's small size allows flexibility in protein folds. 4. Basic Sidechains ⚡: - L-Lysine, L-Histidine, and L-Arginine feature positively charged side chains at physiological pH, classifying them as basic. These amino acids often play key roles in enzyme active sites and protein-protein interactions. 5. Acidic Sidechains 🔋: - L-Aspartic acid and L-Glutamic acid have negatively charged side chains, making them acidic. These amino acids are vital for catalytic functions and maintaining protein structure through ionic interactions. Understanding these amino acids' distinct properties is crucial for anyone interested in protein function and structure. Proteins, after all, are not just structural entities; they are dynamic molecules driving biochemical processes, from metabolism to immune responses. Whether you're a student, researcher, or enthusiast, exploring these amino acids can deepen your appreciation for the intricate dance of life at the molecular level. This knowledge forms the cornerstone of fields like molecular biology, genetics, and biotechnology. Let's celebrate these tiny yet mighty molecules that make life possible! 🌿 #Biochemistry #AminoAcids #Proteins #MolecularBiology #LifeScience #Research #Innovation #ScienceLovers #Biotech #ProteinStructure