Articles tagged with Protein Design
BRIGHT at DTU joins forces with Novonesis to develop microbes that can efficiently utilize acetic acid produced from captured carbon, enabling the production of sustainable protein. The collaboration aims to accelerate microbial fermentation and reduce costs, ultimately contributing to a circular bioeconomy.
Researchers developed a method called optovolution that uses light to guide the evolution of proteins with dynamic, multi-state, and computational functions. This approach favors variants with better dynamics, allowing for the creation of new variants with improved light sensitivity and responsiveness.
Scientists from ISTA and Brandeis University develop a geometric framework that predicts viable structures in self-assembling particles. The 'high-dimensional convex polyhedron' tool helps identify constraints that prevent certain outcomes, offering insights into designing custom-made nanomaterials.
New research suggests that ocean turbulence and horizontal stirring will dramatically increase in the Arctic and Southern Oceans due to human-induced Global Warming. The study uses ultra-high-resolution simulations to investigate how mesoscale horizontal stirring (MHS) responds to warming, revealing a pronounced future intensification ...
Researchers at Graz University of Technology have developed a new approach to understand protein function and stability, identifying amino acids crucial for both with high accuracy. The FSA method combines machine-learning-generated sequences with natural sequences, revealing functional and structural significance of amino acids.
A new mathematical framework, STIV, can predict larger-scale effects like proteins unfolding and crystals forming without costly simulations or experiments. The framework solves a 40-year-old problem in phase-field modeling, allowing for the design of smarter medicines and materials.
Researchers have generated a new ring-shaped protein nanomaterial capable of strongly binding to and neutralizing the SARS-CoV2 virus. The system can integrate therapeutic and diagnostic capabilities and be adapted to combat other viruses.
Researchers designed long-acting human albumin-fused FIX variants with unique pharmacokinetic properties, including extended plasma half-lives and enhanced extravascular distribution. The findings endorse the use of engineered albumin-fused FIX variants as personalized therapy options for hemophilia B.
A team of researchers has developed a new method to produce sturdy and reusable bioplastics from domestic raw materials, reducing reliance on petroleum-based chemicals. The bioplastics, known as polyhydroxyalkanoates (PHAs), have similar levels of toughness and malleability to traditional plastics, but are infinitely recyclable.
A new artificial biosensor developed by University of California, Santa Cruz's Andy Yeh can accurately measure cortisol levels across all relevant ranges for human health. The sensor uses a smartphone camera to detect light emissions, providing high sensitivity and dynamic range for detecting small molecule analytes.
The University of Illinois team created a user-friendly process to improve enzyme performance using AI and automated robotics. By predicting sequence changes and testing variants, they increased the activity of two key industrial enzymes by up to 26 times and 90 times.
Linna An joins Rice University to develop protein-based biosensors for cancer detection, drug monitoring, and personalized diagnostics. Her work focuses on mapping the 'metabolism landscape' of cancer using synthetic proteins.
A new Center for Protein Design at the University of Copenhagen aims to create artificially designed proteins with tailored properties to tackle diseases, environmental issues, and industrial applications. The centre will drive fundamental research and translate basic findings into concrete solutions.
Researchers at Colorado State University have created a programmable plant circuit that can turn genes on and off, allowing farmers to time harvests and adapt to drought. The breakthrough could lead to automated genetic circuit design through machine learning, revolutionizing agriculture.
Researchers have developed new seed varieties of wheat that remove harmful gluten proteins without affecting breadmaking quality. The modified wheat can reduce the risk of triggering celiac disease in people without the condition and improve flour quality.
Researchers used generative AI to design diverse mitochondrial targeting sequences, achieving a 50-100% success rate in yeast, plant cells, and mammalian cells. The AI-generated sequences showed improved targeting abilities compared to existing ones, with potential applications in metabolic engineering and therapeutics.
Researchers at MIT developed a control circuit that can precisely regulate gene expression levels, improving the efficacy and safety of gene therapy treatments. The 'COMMAND' circuit uses microRNA to suppress gene expression, allowing for tighter control over treatment outcomes.
Researchers developed a novel protein, LSUBP, to enhance uranium extraction from seawater. The engineered protein achieves high adsorption capacity, offering a promising new material for effective uranium extraction.
A research team has discovered that protein misfolding is a major cause of efficiency problems when using split inteins to produce proteins. By introducing specific mutations to the intein fragment, they were able to suppress aggregation and increase productivity.
The Protein Society recognizes five award winners in 2025 for their groundbreaking research in protein science and technology. Professor Jan Steyaert receives the Christian B. Anfinsen Award for pioneering nanobody technology, while Dr. Brian Kuhlman wins the Emil Thomas Kaiser Award for novel protein design and structural modeling.
A new bacterial protein, BeeR, has been identified and its structure is being used to develop protein nanoparticles for targeted cancer drug delivery. The protein forms a hollow tube with a cavity capable of containing drug molecules.
A new paper proposes that temperature plays a fundamental role in setting off shapeshifting in metamorphic proteins. Researchers analyzed differences in hydrophobic contacts and found significant temperature-dependent changes, supporting their theory.
Researchers at Sanford Burnham Prebys have discovered a way to target the energy supply chain of cancer cells. By understanding how enzymes like ubiquitous mitochondrial creatine kinase (uMtCK) function, scientists can design new treatments that slow or stop tumor growth.
A team of scientists has found that some artificially designed proteins contain flexible components that can take on multiple structures, leading to surprising properties and potential applications. This discovery could open up new avenues for the development of customized proteins.
Researchers developed a new method to search through billions of molecules to identify potential anti-inflammatory drug candidates. The method uses computer algorithms to explore vast chemical space and has the potential to speed up the costly drug development process.
A new universal photocage modification strategy based on thioketal enables real-time live cell subcellular imaging. The thioketal-based probe SiR-EDT exhibits improved dark stability and can be specifically activated by UV-visible light.
Biomedical engineers at Duke University have developed a new technique that traps together cellular machinery to increase protein production rates. This approach uses synthetic disordered proteins to form compartments called biological condensates, which enhance the rate of protein production by bringing together biomolecular machinery...
Researchers at the University of Maryland discovered multiple pathways for dsRNA molecules to enter cells, challenging previous assumptions about RNA transport. They found that a protein called SID-1 plays a key role in regulating genes across generations, which could lead to better targeted treatments for human diseases.
A team of researchers at Duke University has developed a novel AI-based platform that can design and match small peptides with complex proteins, previously considered unreachable. The PepPrCLIP platform utilizes generative large language models to create peptide guide proteins and an algorithm framework to screen and test the peptides.
Researchers developed ProtET, an AI model leveraging multi-modal learning to controllably edit proteins through text-based instructions. This approach enhances functional protein design across domains like enzyme activity, stability, and antibody binding, promising real-world applicability in biomedical research.
A team of scientists developed a computational design tool called SPaDES to create new membrane receptors that outperform natural counterparts. The new receptors were designed by optimizing water-mediated interactions, resulting in higher stability and signaling efficiency.
Researchers developed ProteinReDiff, an AI-powered method to redesign proteins for improved ligand binding. The approach uses initial protein sequences and ligand SMILES strings, reducing reliance on detailed structural data.
A new study demonstrates how fluorescent cholesterol probes can visualize cholesterol in live cells, revealing its role in amyloid plaque formation and cellular signaling. The novel probes have the potential to enhance our understanding of how cholesterol imbalances contribute to neurodegenerative disorders.
The EPFL team has developed a deep-learning pipeline called MaSIF to design new proteins that interact with therapeutic targets. They have successfully designed novel protein binders that can recognize and bind to drug-protein complexes, offering potential applications in cell-based therapies and biosensors.
Researchers at the University of Washington have developed new proteins that can neutralize lethal snake venom toxins using deep learning computational methods. These protein designs show promise for creating safer and more cost-effective antivenoms, potentially saving millions of lives annually.
Researchers created new proteins using AI that bind to and neutralize deadly snake toxins, providing a safer alternative to traditional antivenoms. The study's results show an 80-100% survival rate in mice, offering potential benefits for people in developing countries.
Researchers have developed a new geometric machine learning method called MaSIF, which enables the design of proteins that bind specifically to desired molecular structures. This approach accelerates precision drug development by allowing for precise dosing and control of biological drugs.
Researchers have made a major breakthrough in synthetic biology by developing a new construction kit for building custom sense-and-respond circuits in human cells. The new approach harnesses the power of phosphorylation to amplify weak input signals into macroscopic outputs, enabling rapid response times and sensitivity to external sig...
The US Department of Energy is investing $179 million in three Microelectronics Science Research Centers to develop next-generation microelectronics designed for extreme environments. PNNL will lead projects on neuromorphic computing, EUV lithography, and heterogeneous computing.
Researchers developed AI-driven therapeutic platform mimicking viral structures to deliver therapeutic genes to target cells. The innovative approach achieved precise symmetrical structures and effectively delivered payloads, paving the way for breakthroughs in gene therapies and next-generation vaccines.
Researchers at U of T have created SIMPL2, a platform that simplifies detection and improves accuracy of protein-protein interactions. The tool enables the rapid identification of protein interactions, including weak ones, for targeted drug therapies.
The team developed a Synthetic Translational Coupling Element (SynTCE) that enhances the precision and integration density of genetic circuits in synthetic biology. This allows for more efficient gene circuit integration, minimizing interference between biological parts and enabling precise control over multiple genes.
Researchers at Université de Montréal successfully recreated two distinct mechanisms that can program the activation and deactivation rates of nanomachines in living organisms across multiple timescales. This breakthrough suggests how engineers can exploit natural processes to improve nanomedicine and other technologies.
Researchers from USTC and Harvard Medical School create PocketGen, a deep generative model for generating protein pocket sequences and spatial structures. The model achieves over 10-fold improvement in speed and demonstrates high accuracy in binding small molecules.
A new method to enhance pea protein solubility, combining heat treatment and guarana extract, offers potential as an ingredient in plant-based beverages. The approach improves emulsion stability and vitamin D3 preservation.
Researchers have developed a new method for designing large artificial proteins with high accuracy, utilizing AI-based software Alphafold2. The approach combines accurate structure prediction with optimization techniques, allowing for the creation of proteins with tailored properties, such as precise binding and stability.
Researchers at University of California - San Francisco designed biological sensors that can ensure engineered cells are activated in tumor environments, making cancer therapies more effective. The new sensors, called SNIPRs, can bind to soluble molecules and alter gene expression, offering a promising approach for targeted therapies.
Pharma.AI Week will showcase the latest advancements in Insilico's generative AI platform, including PandaOmics and Science42, with expert speakers and hands-on demos. The event aims to empower researchers and scientists with tools for faster and more accurate discoveries.
Scientists have designed bioluminescent proteins that can produce multiple colors of light for real-time imaging in cellular and animal models. These proteins are small, efficient, highly stable and can be used for non-invasive bioimaging, diagnostics, drug discovery and more.
Researchers at Argonne National Laboratory have developed an AI-driven protein design framework that uses multimodal data to speed up the design of new proteins. The framework has been selected as a finalist for the prestigious Gordon Bell Prize, recognizing breakthroughs in high-performance computing.
Researchers from the IBB-UAB have developed novel nanoparticles capable of trapping and neutralizing large quantities of SARS-CoV2 virus particles. These nanostructures could be used to manufacture antiviral materials such as wastewater and air filters, and develop new tests for early Covid-19 detection.
Researchers at Linköping University have developed a new version of AlphaFold that can predict the shape of very large and complex protein structures, integrating experimental data. This breakthrough aims to improve the development of new proteins for medical drugs.
Researchers design a high-throughput approach to create novel polypeptides with diverse chemical properties, leading to the discovery of hundreds of unique low-energy repeating structures. The study paves the way for broader applications in materials design and biotechnology.
Researchers developed a novel, homogeneous customizable OpenGUS immunoassay that detects target analytes quickly and effectively. The platform provides a hassle-free approach for biomarker detection in point-of-care diagnostics, high-throughput testing, and environmental monitoring.
Researchers at Institute of Science Tokyo create terpene-based chiral capsules that facilitate the easy preparation of well-defined host–guest composites with tunable chiroptical properties. The resulting composites can be used in water without organic solvents, paving the way for advances in cutting-edge optical technologies.
A research team developed an RNA-based sensor platform that can regulate gene expression in bacteria, mimicking natural biological interactions. The START platform enables tunable control over sensor response and detection of various molecules, including drugs and proteins.
Researchers discovered that mutations affect protein stability following surprisingly simple rules, making it possible to predict protein behavior without complex models. This breakthrough has significant implications for accelerating new treatments and designing more stable proteins with industrial applications.
Researchers at UT Austin developed AI model EvoRank to design protein-based therapies and vaccines by leveraging nature's evolutionary processes. The model identifies useful mutations in proteins, offering a new approach to biomedical research and biotechnology.
A novel synthetic biology platform enables rapid and cost-effective transformation of protein binders into high-contrast nanosensors for various applications. The platform uses fluorogenic amino acids to increase fluorescence up to 100-fold, enabling the detection of specific proteins, peptides, and small molecules.
A clinical trial led by UC San Francisco aims to develop new therapies for progressive supranuclear palsy, with a focus on reducing time to find effective treatments and increasing diverse participant enrollment. The five-year grant could lead to the first effective drugs for this incurable neurodegenerative disorder.