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Novel generative AI model enables atomic-scale prediction of protein–protein interactions

Researchers have developed a generative AI model called Void-X that can predict protein-protein interactions with high accuracy, enabling the design of new biomolecules for drug discovery and synthetic biology. The model achieves predictive accuracies of 78.3% for intra-chain clusters and 68.2% for inter-chain clusters.

SourceChinese Academy of Sciences Headquarters·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateJun 15, 2026

Shedding light on receptor selectivity: “one of the most comprehensive projects in my entire scientific career”

The study identified amino acids crucial for ligand selectivity in two groups of receptors, β-adrenergic and D1-like dopamine receptors. By modifying these amino acids, the researchers made each receptor prefer its native ligand. The findings suggest that regions outside of the primary binding site also play a role in selectivity.

SourceUppsala University·JournalNature Communications·TypeExperimental study·DateMay 12, 2026

Behind nature’s blueprints

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.

SourceInstitute of Science and Technology Austria·JournalNature Physics·TypeComputational simulation/modeling·DateJan 8, 2026

More polar ocean turbulence due to planetary warming

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 ...

SourceInstitute for Basic Science·JournalNature Climate Change·TypeComputational simulation/modeling·DateNov 5, 2025

Graz University of Technology researchers open up new avenues of understanding proteins

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.

SourceGraz University of Technology·JournalStructure·TypeComputational simulation/modeling·DateOct 30, 2025

Tailored collagen binding of albumin-fused hyperactive coagulation factor IX dictates in vivo distribution and functional properties

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.

SourceUniversity of Oslo, Ullevaal University Hospital·JournalNature Communications·DateSep 29, 2025

Artificial biosensor can better measure the body’s main stress hormone

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.

SourceUniversity of California - Santa Cruz·JournalJournal of the American Chemical Society·DateJul 28, 2025

Harnessing generative AI to expand the mitochondrial targeting toolkit

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.

New method searches through 10 sextillion drug molecules

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.

SourceUppsala University·JournalNature Communications·TypeComputational simulation/modeling·DateFeb 26, 2025

New photochemical tools based on thioketal

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.

SourceScience China Press·JournalScience Bulletin·TypeRandomized controlled/clinical trial·DateFeb 25, 2025

Engineering biological reaction crucibles to rapidly produce proteins

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...

SourceDuke University·JournalNature Chemistry·TypeExperimental study·DateFeb 11, 2025

Harnessing generative AI to treat undruggable 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.

SourceDuke University·JournalScience Advances·TypeComputational simulation/modeling·DateJan 30, 2025

A new geometric machine learning method promises to accelerate precision drug development

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.

SourceCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences·JournalNature·TypeComputational simulation/modeling·DateJan 15, 2025

Major breakthrough for ‘smart cell’ design

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...

SourceRice University·JournalScience·TypeExperimental study·DateJan 3, 2025

Programming cells: Revolutionizing genetic circuits with cutting-edge RNA tools

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.

SourcePohang University of Science & Technology (POSTECH)·JournalNucleic Acids Research·DateDec 20, 2024

Tinkering with the “clockwork” mechanisms of life

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.

SourceUniversity of Montreal·JournalJournal of the American Chemical Society·DateDec 19, 2024

New method for designing artificial proteins

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.

SourceTechnical University of Munich (TUM)·JournalScience·TypeExperimental study·DateNov 21, 2024