Biocatalysis Strategies

Delighted to share our work just published in Angewandte Chemie on a chemoenzymatic strategy for the ‘skeletal editing’ of complex natural product scaffolds with engineered P450s! This approach enables the ring expansion of an organic molecule at the level of an aliphatic (methylene) C─H site by merging a site-selective C–H oxidation reaction with engineered P450 enzymes with subsequent Baeyer–Villiger rearrangement or ketone homologation. Thanks to the tunable regioselectivity of P450 enzymes (via protein engineering) and their ability to target unactivated C(sp3)-H bonds, this strategy can allow for the site-selective introduction of a subtle structural modification at multiple C(sp3)-H positions within a complex organic framework, including ‘remote’ aliphatic C-H  sites that are inaccessible to chemical methods alone. As a point in case, using this approach, we were able to obtain five ring-expanded derivatives of a complex natural product (cedrol) through P450-mediated oxidation of three distinct aliphatic C(sp3)-H sites within the molecule, none of which was possible via oxidation with reported chemical methods. This general strategy, which can be readily extended to other classes of oxidizing enzymes capable of C-H hydroxylation (e.g., NHI dioxygenases, UPOs, etc), can provide a powerful tool to rapidly access skeletally edited derivatives of natural products and other bioactive molecules toward the discovery of bioactive molecules with new or improved biological activity. Illustrating this point, screening of less than 20 compounds derived from chemoenzymatic skeletal editing of a panel of different natural products led to the discovery of two derivatives with drastically altered anticancer profile. Big congratulations to the excellent team behind this work: John Bennett, Andrew Bortz, Zheyuan Wang, and Muhammed Fastheem! #chemoenzymaticsynthesis #skeletalediting #naturalproducts #P450 #biocatalysis #proteinengineering

A dynamic approach for expanding enzyme substrate range with molecular simulations and neural sequence design Enhancing enzymes so they can process more substrates is crucial for industrial biocatalysis, green chemistry, and pollutant remediation. Yet traditional enzyme engineering often hinges on static crystal structures or extensive lab screening, risking overlooks of important molecular details. In their latest work, Sun et al. introduce CMDmpnn, a method that combines molecular dynamics simulations and ProteinMPNN sequence generation to broaden enzyme substrate scope while keeping key properties like thermostability intact. The CMDmpnn workflow begins by performing molecular dynamics on the wild-type protein with a known substrate, capturing its dynamic conformation and identifying residues that consistently interact with the active-site substrate. ProteinMPNN then mutates those residues while leaving the rest of the structure “frozen,” producing a library of sequence variants for the enzyme. Each variant is briefly docked with candidate substrates and subjected to short molecular dynamics runs to see if it maintains a catalytically favorable distance and binding mode, akin to the original. This two-step strategy—combining a robust neural-network-based sequence design with accurate, time-dependent simulations—enables quick, efficient screening for variants likely to handle new substrates. Using Arabidopsis glycosyltransferase as a demonstration, CMDmpnn promptly identified multiple enzyme variants that glycosylate a broad set of phenolic compounds. The entire computational pipeline was performed on a standard personal computer in under two weeks, cutting experimental costs by reducing the need for exhaustive mutational scans. Additionally, by incorporating dynamic information into residue selection, CMDmpnn avoids detrimental alterations to other catalytic properties, a persistent challenge in enzyme engineering. This method thus shows a compelling way to combine fast neural network–based design with molecular simulations for rapid, reliable substrate spectrum expansion. Paper: https://lnkd.in/dMFZntnT #MolecularDynamics #EnzymeEngineering #ProteinMPNN #MachineLearning #Biocatalysis #GreenChemistry #DrugDiscovery #SubstrateSpecificity #Proteomics #StructuralBiology #Catalysis #ProteinDesign #Sustainability #AIforScience #ResearchInnovation

𝗧𝗵𝗿𝗲𝗲 𝘄𝗮𝘆𝘀 𝘁𝗼 𝘁𝘂𝗿𝗻 𝗖𝗢₂ 𝗶𝗻𝘁𝗼 𝗺𝗲𝘁𝗵𝗮𝗻𝗲. 𝗢𝗻𝗲 𝗶𝘀 𝗯𝗮𝗻𝗸𝗮𝗯𝗹𝗲 𝘁𝗼𝗱𝗮𝘆. The Sabatier reaction has been on the books since 1897: CO₂ + 4 H₂ → CH₄ + 2 H₂O, ΔH° = −165 kJ/mol. Thermodynamics is favorable at low temperature. Kinetics is the bottleneck, because CO₂ carries a C=O bond of roughly 750 kJ/mol. Three catalytic pathways are currently pursued. Each one pays the activation-energy bill in a different currency. 𝟭. 𝗧𝗵𝗲𝗿𝗺𝗼𝗰𝗮𝘁𝗮𝗹𝘆𝘀𝗶𝘀 — 𝘁𝗵𝗲 𝗶𝗻𝗰𝘂𝗺𝗯𝗲𝗻𝘁 • Ni or Ru catalyst, 250–400 °C, 1–30 bar • >95% CO₂ conversion, ~100% CH₄ selectivity with Ru • ~80% methanation efficiency (LHV CH₄ / LHV H₂) when heat is recovered • TRL 8–9. Reference: Audi e-gas, Werlte (DE), 6 MWₑₗ, online since 2013, ~1,000 t CH₄/yr • ~70% of operating cost is electricity for H₂ (IEA Bioenergy Task 44) 𝟮. 𝗕𝗶𝗼𝗰𝗮𝘁𝗮𝗹𝘆𝘀𝗶𝘀 — 𝘁𝗵𝗲 𝗹𝗶𝘃𝗶𝗻𝗴 𝗦𝗮𝗯𝗮𝘁𝗶𝗲𝗿 • Hydrogenotrophic archaea (e.g. Methanothermobacter) at 40–70 °C, 1–10 bar • >95% CO₂ conversion, >98% CH₄ purity directly on raw biogas; H₂S tolerant • ~78–83% methanation efficiency reported by independent operators (Q Power) • TRL 7–8. Reference: Electrochaea BioCat, 1 MWₑₗ, Avedøre (DK, 2016); 10 MWₑₗ Roslev in construction • Volumetric productivity is the cost-binding constraint — 50–200 L CH₄ per L_reactor per day 𝟯. 𝗣𝗹𝗮𝘀𝗺𝗮𝗰𝗮𝘁𝗮𝗹𝘆𝘀𝗶𝘀 — 𝘁𝗵𝗲 𝗲𝗹𝗲𝗰𝘁𝗿𝗶𝗳𝗶𝗲𝗱 𝗳𝗿𝗼𝗻𝘁𝗶𝗲𝗿 • Non-thermal plasma (typically DBD) + Ni/Ru support, <200 °C bulk, atmospheric pressure • Electron temperatures >10,000 K activate CO₂ while the gas stays near ambient • Intrinsic millisecond ramp rates, well matched to renewable intermittency • Biset-Peiró et al. (ACS Sustainable Chem. Eng., 2020): ~20× higher CO₂ conversion vs pure thermal at 150 °C when plasma is combined with Ni • TRL 3–5. No industrial reference. Recent TEA (J. CO₂ Util., 2025) projects ~1,845 €/t e-CH₄ only in high-solar regions • Energy efficiency today sits at 30–55%, trailing both alternatives One structural fact ties all three together. Every pathway consumes 4 mol H₂ per mol CH₄: a stoichiometry no catalyst can change. The real competition on molecule cost is decided upstream, in the electrolyzer and the electricity market. The useful question is narrower: where each route first clears the bar of cost, infrastructure, and bankability and whether supply can concentrate there before policy disperses it into lower-value end uses. Same reaction. Same molecule. Three engineering bets, and one shared dependency: cheap renewable electrons. #PowerToGas #Methanation #EnergyTransition #CleanFuels

🚀 Exciting Breakthrough in Green Chemistry! 🌱 I'm thrilled to share the findings of our latest study in collaboration with Ivaldo Itabaiana Jr and Robert Wojcieszak on LinkedIn! We investigated the oxidation of 5-hydroxymethylfurfural (HMF) to produce valuable products like 2,5-furandicarboxaldehyde (DFF), 5-formyl-2-furancarboxylic acid (FFCA), and 2,5-furandicarboxylic acid (FDCA) using (photo)chemical and enzymatic catalysis. Our research evaluated various laccases, with Trametes versicolor (LacTV) emerging as the most effective catalyst, achieving complete conversion of HMF under specific pH conditions. We discovered that the reaction favored the primary alcohol oxidation pathway, leading to the formation of DFF and its subsequent conversion to FFCA and FDCA. Optimal HMF conversion occurred at concentrations below 100 mM, with reduced performance at higher concentrations. We also examined the influence of blue light (430 nm) on this reaction, finding that light exposure affected gC3N4-based catalysts but negatively impacted LacTV. Additionally, we introduced a modular flow chemical platform using Continuous Stirred Tank Reactors (CSTR) in a cascade configuration, which led to a 40-fold increase in FDCA productivity compared to traditional batch systems. These findings have immense potential for advancing green chemistry and sustainable chemical synthesis, opening up new possibilities for environmentally friendly HMF oxidation processes. Let's drive the future of sustainable chemistry together! 🌍🔬 https://lnkd.in/dA8pe8mJ #GreenChemistry #SustainableSynthesis #Innovation #ChemicalResearch #HMFoxidation #Laccases #ContinuousFlowChemistry #EnvironmentalScience #FDCA #Biocatalysis

Understanding and designing enzymes for drug discovery has evolved beyond static active sites. This ACS Omega review highlights the importance of detailed mechanistic modeling in enzyme engineering and covalent drug design. The authors present a strong argument that QM/MM simulations, free-energy methods, and explicit treatment of protein dynamics, entropy, and allostery are crucial for advancing from empirical screening to predictive catalytic models. Their insights on covalent inhibitors are particularly pertinent for the pharmaceutical industry: accurate modelling of reaction pathways and transition states is now a vital design tool rather than merely a post-hoc rationalisation. For those engaged in the intersection of computational chemistry and biocatalysis, this review serves as a timely reminder that significant advancements will arise from workflows that combine mechanistic simulations with modern enzyme design. Article link: https://lnkd.in/ej48ZWXv #enzymes #proteins #computational #CADD #drugdesign

𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐄𝐧𝐳𝐲𝐦𝐞 𝐃𝐞𝐬𝐢𝐠𝐧: 𝐀 𝐍𝐞𝐰 𝐄𝐫𝐚 𝐟𝐨𝐫 𝐁𝐢𝐨𝐜𝐚𝐭𝐚𝐥𝐲𝐬𝐢𝐬 Enzymes are nature’s catalysts, driving essential biochemical reactions with incredible precision. But what if we could design entirely new enzymes with functions beyond nature’s repertoire? Enter AI.zymes, a modular AI-driven enzyme design platform that integrates cutting-edge machine learning, structural biology, and computational evolution to engineer next-generation biocatalysts. A recent study by Lucas Merlicek  et al. (2025) introduces AI.zymes, which optimizes enzyme activity, stability, and catalytic efficiency through iterative in silico evolution. Unlike traditional static design methods, AI.zymes continuously refines enzyme candidates, pushing the boundaries of catalytic performance. 💡 What Makes AI.zymes a Game-Changer? 🔹 Evolutionary Design Over Static Design Traditional protein design relies on a single input sequence, limiting exploration of the fitness landscape. AI.zymes evolves enzyme structures across multiple generations, selecting the best candidates in each iteration for further optimization. 🔹 Multi-Objective Optimization Beyond just structural stability, AI.zymes refines catalytic electrostatics, substrate binding, and conformational flexibility, ensuring that designed enzymes not only fold correctly but also function efficiently. 🔹 AI-Driven Toolkit for Enzyme Engineering The platform integrates top-tier AI-based tools: 🧬 AlphaFold3 & ESMFold – Predicting structural accuracy 🛠️ Rosetta & ProteinMPNN – Designing stable and functional proteins ⚡ FieldTools – Optimizing catalytic electric fields, a crucial but often overlooked factor in enzymatic reactions 🔹 Benchmarking Success: Kemp Eliminase Engineering AI.zymes was tested on ketosteroid isomerase, improving its Kemp eliminase activity by 7.7-fold after just seven experimental validations. The AI-driven approach outperformed traditional methods, refining enzyme function while maintaining structural stability. 🚀 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐄𝐧𝐳𝐲𝐦𝐞 𝐃𝐞𝐬𝐢𝐠𝐧 The modularity of AI.zymes allows seamless integration of new AI models, molecular dynamics simulations, and deep-learning-based reaction modeling. This could revolutionize biocatalysis, drug development, and synthetic biology, offering tailored solutions for industrial and medical applications.  https://lnkd.in/dvNAEWqg 💬 𝐇𝐨𝐰 𝐝𝐨 𝐲𝐨𝐮 𝐬𝐞𝐞 𝐀𝐈 𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐭𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐞𝐧𝐳𝐲𝐦𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠? 𝐂𝐨𝐮𝐥𝐝 𝐭𝐡𝐢𝐬 𝐛𝐞 𝐭𝐡𝐞 𝐤𝐞𝐲 𝐭𝐨 𝐝𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐧𝐞𝐱𝐭-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐡𝐞𝐫𝐚𝐩𝐞𝐮𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐠𝐫𝐞𝐞𝐧 𝐜𝐡𝐞𝐦𝐢𝐬𝐭𝐫𝐲 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬! #AIinScience #Biocatalysis #ProteinEngineering #ArtificialIntelligence #StructuralBiology #ComputationalBiology #MachineLearning #SyntheticBiology #AIforGood

We are pleased to share the research work "Intracellular CO2 Capture Triggered Outperforming Biocatalytic Production of Selective Acetic Acid & Biohydrogen Housing in Porous-Organic-Nanofiber" by Nitumani Das, Triya Mukherjee, Chitra Sarkar, Ratul Paul, Duy Quang Dao, S Venkata Mohan and John Mondal published in Angewandte Chemie International Edition (2025). This research focuses on a novel Electrofermentation platform integrated with polycarbazole-based Porous-Organic-Polymer (POP) coated electrodes to enhance selective Acetic acid (AA) biosynthesis by Bacillus subtilis. Impressive high surface area and tailored porosity facilitate efficient CO2 capture, modulate intracellular metabolic fluxes, and improve electron transfer, thereby driving product specificity. In the Bioreactor equipped with POP, acetic acid production reached 2.11 g/L with a yield of 0.48 g/g, achieving 71% of the theoretical maximum without genetic modifications. The process also resulted in enriched Bio-hydrogen content (52%) in the Biogas (H2+CO2) composition. This pioneering approach with unique investigation results presents a scalable and sustainable biocatalytic framework for CO2 valorization, bridging material science and microbial electrochemical systems for selective AA and enhanced biohydrogen production.

🚀 The Dissolved Oxygen Paradox: Why More O₂ Killed My Biocatalysis Reaction! During my PhD, I was working on a whole-cell resting biocatalysis process—first growing yeast cells and then using them for asymmetric reduction of beta-keto esters to optically pure beta-hydroxy esters. In shake flasks, everything looked perfect—>99% conversion, >99% enantiomeric excess, and all in just 15 minutes. But when I scaled up to a fermenter with 30% dissolved oxygen (DO), I ran into an unexpected problem. Biomass doubled, yet reaction conversion dropped below 20%. 🔍 What went wrong? At first, it was puzzling. More cells should have meant better conversion, right? But then I considered k_La (volumetric mass transfer coefficient). In shake flasks, oxygen transfer is passive, relying on surface aeration and mild agitation. In fermenters, high-speed mixing and sparging drastically increase k_La, shifting yeast metabolism. Since this was a resting cell biocatalysis, the excess oxygen likely altered metabolic flux, making the yeast favor growth over catalytic activity. The NADH/NADPH balance was disrupted, impacting the reduction reaction. 🔬 The Fix? Lower DO. After optimization, we found that cells grown at 15% DO gave excellent conversion, restoring high efficiency. Too much oxygen was actually harming the reaction! 💡 Key Takeaways for Bioprocess Scale-up: ✅ k_La isn’t just about oxygen supply—it shapes metabolism. ✅ Scaling up is more than increasing volume; metabolic shifts must be considered. ✅ Cofactor balance (NADH/NADPH) is critical for whole-cell biocatalysis. ✅ Resting cells behave differently from growing cells—optimizing conditions for biocatalysis is key! This experience reinforced that scaling up is a science, not just an engineering adjustment. Sometimes, less oxygen is more. Have you ever faced such scale-up surprises? Let’s discuss! 🚀 #Biotech #Bioprocessing #Fermentation #ScaleUp #Biocatalysis #IndustrialBiotechnology #MetabolicEngineering #EnzymeTechnology #OxygenTransfer #MicrobialFermentation #Biomanufacturing #ProcessOptimization #WholeCellBiocatalysis #NADH #RestingCells

I’m pleased to share our latest research paper published in Food Bioscience, where we explored a novel strategy to enhance the synthesis of arachidonic acid (ARA)-rich medium- and long-chain triglycerides (MLCT) using bio-imprinted lipase. 🔬 What did we do? We successfully boosted lipase-catalyzed acidolysis of microbial oil with caprylic acid by applying bio-imprinting techniques to Lipozyme RM IM. This approach significantly improved catalytic efficiency and selectivity. ✨ Key highlights: - ✅ 1.99-fold increase in initial enzymatic activity after bio-imprinting - ✅ Reduced activation energy (26.46 → 18.08 kJ/mol), confirming improved catalytic performance - ✅ Molecular docking insights revealed strong hydrogen-bonding interactions between caprylic acid and the active site (Ser-161), explaining the enhanced activity - ✅ Preferential binding to shorter-chain substrates, supporting selective MLCT synthesis - ✅ Under optimized conditions, achieved 27.82 mol% caprylic acid incorporation, with: - 34.20 mol% sn-2 ARA - 37.44 mol% sn-1,3 caprylic acid 📌 Why does this matter? ARA-rich MLCTs hold strong potential for nutritional, medical, and functional lipid applications. Our findings not only advance MLCT production strategies but also deepen mechanistic understanding of lipase-mediated acidolysis, bridging experimental data with molecular-level insights. #FoodBioscience #MLCT #ArachidonicAcid #Lipase #Biocatalysis #BioImprinting #FunctionalLipids #EnzymeEngineering #MolecularDocking #ResearchPublication https://lnkd.in/dC86A7ca

I'm happy to share two of the recent publications from our research group, both of which describe strategies to transform aldehydes to amine-containing molecules using engineered bacterial cells. #Biocatalysis #SyntheticBiology #GenomeEngineering In the 2023 Futures Issue of the AIChE - American Institute of Chemical Engineers journal, we report the creation of a strain that can stabilize terephthalaldehyde, an aldehyde that can be derived from waste plastic (specifically from polyethylene terephthalate). We identified a new set of aldehyde reductases that were responsible for the undesired transformation of terephthalaldehyde to benzenedimethanol, eliminated those genes using multiplexed genome engineering, and then converted terephthalaldehyde to its corresponding diamine. This work was led by Roman Dickey, and he and I will both be speaking about it at the 2023 AIChE Annual Meeting. https://lnkd.in/g-XhXMcv A major interest in our lab is designing biosynthetic routes to non-standard amino acids (nsAAs). One set of nsAAs with biomedical importance are beta-hydroxylated aromatic amino acids, which can be made by L-threonine transaldolases (TTAs). The TTA discovered in 2017 that can catalyze the formation of many of these products is quite interesting but has some limitations, including its ability to work well in bacterial cells during fermentation, which is a common means of producing natural products and proteins. In our latest publication, we show how we found that some distantly related sequences to the known enzyme can produce beta-hydroxylated nsAAs better. We found one homolog that exhibited higher affinity for the co-substrate L-threonine, higher diastereomeric selectivity, and higher catalytic efficiency. Our paper also shows how we can produce aldehyde- and azide-containing nsAAs from simple precursors by expressing these TTAs in engineered bacteria grown aerobically. This work was led by Michaela Jones, with important contributions also from Neil Butler, Shelby Anderson, Sean Wirt, Ishika Govil, and wonderful collaborators in chemistry. Find it here, open access in Communications Biology: https://lnkd.in/gQe4wJTv