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AI breakthrough designs peptide drugs to target previously untreatable proteins

A study published in Nature Biotechnology reveals a powerful new use for artificial intelligence: designing small, drug-like molecules that can stick to and break down harmful proteins in the body — even when scientists don’t know what those proteins look like. The breakthrough could lead to new treatments for diseases that have long resisted traditional drug development, including certain cancers, brain disorders, and viral infections.

The study was published on August 13, 2025 by a multi-institutional team of researchers from McMaster University, Duke University, and Cornell University. The AI tool, called PepMLM, is based on an algorithm originally built to understand human language and used in chatbots, but was trained to understand the “language” of proteins.

In 2024, the Nobel Prize in Chemistry was awarded to researchers at Google DeepMind for developing AlphaFold, an AI system that predicts the 3D structure of proteins – a major advance in drug discovery. But many disease-related proteins, including those involved in cancer and neurodegeneration, don’t have stable structures. That’s where PepMLM takes a different approach – instead of relying on structure, the tool uses only the protein’s sequence to design peptide drugs. This makes it possible to target a much broader range of disease proteins, including those that were previously considered “undruggable.”

Cubosome-based method for loading mRNA into exosomes

Exosomes, naturally derived vesicles responsible for intercellular communication, are emerging as next-generation drug delivery systems capable of transporting therapeutics to specific cells. However, their tightly packed, cholesterol-rich membranes make it extremely difficult to encapsulate large molecules such as mRNA or proteins.

Conventional approaches have relied on techniques like electroporation or chemical treatment, which often damage both the drugs and exosomes, reduce delivery efficiency, and require complex purification steps—all of which pose significant barriers to commercialization.

The team utilized a lipid-based nanoparticle known as a “cubosome,” which mimics the fusion structure of cell membranes and naturally fuses with exosomes. By mixing cubosomes carrying mRNA with exosomes at room temperature for just 10 minutes, the researchers achieved efficient fusion and confirmed that the mRNA was successfully loaded into the exosomes. Analysis showed that over 98% of the mRNA was encapsulated, while the structural integrity and biological function of the exosomes were preserved.

Furthermore, the engineered exosomes demonstrated the ability to cross the blood-brain barrier, one of the most difficult hurdles in drug delivery. Notably, the team observed a “homing” effect, where exosomes return to the type of cell they originated from, enabling targeted drug delivery to diseased tissues.

Metamaterials: Shaping The Future Of Optics And Electromagnetism

Metamaterials are artificial materials engineered to exhibit unique properties not found in naturally occurring materials, including negative refractive index, perfect absorption of electromagnetic radiation, and tunable optical properties. Researchers have been exploring the use of metamaterials in various applications, including optics, electromagnetism, and acoustics. One area where metamaterials are being explored is in sensing and imaging applications, such as creating ultra-compact optical devices like beam splitters and lenses.

The first practical demonstration of a metamaterial was achieved in 2000 by David Smith and his team at the University of California, San Diego. They created a composite material consisting of copper strips and dielectric materials, which exhibited a negative refractive index at microwave frequencies. This breakthrough sparked widespread interest in the field, and soon researchers began exploring various applications of metamaterials.

One of the key areas of research has been in the development of optical metamaterials. In 2005, a team led by Xiang Zhang at the University of California, Berkeley demonstrated the creation of an optical metamaterial with negative refractive index. They achieved this by using a fishnet-like structure composed of silver and dielectric materials. This work paved the way for further research into optical metamaterials and their potential applications in fields such as optics and photonics.

Metamaterials have also been explored for their potential use in electromagnetic cloaking devices. In 2006, a team led by David Smith demonstrated the creation of a metamaterial cloak that could bend light around an object, effectively making it invisible. This work was based on earlier theoretical proposals by John Pendry and his colleagues.

Sam Altman’s worst-case AI scenario may already be here

Sam Altman, CEO of OpenAI, appeared at a Federal Reserve event on July 22 and outlined three “scary categories” of how advanced artificial intelligence could threaten society.

The first two scenarios — a bad actor using artificial intelligence for malfeasance and a rogue AI taking over the world — were accompanied by the insistence that people were working to prevent them. However, Mr. Altman offered no such comfort with the third scenario, the one that seemed to trouble him most.

He described a future where AI systems become “so ingrained in society … [that we] can’t really understand what they’re doing, but we do kind of have to rely on them. And even without a drop of malevolence from anyone, society can just veer off in a sort of strange direction.”

The first experimental realization of quantum optical skyrmions in a semiconductor QED system

Skyrmions are localized, particle-like excitations in materials that retain their structure due to topological constraints (i.e., restrictions arising from properties that remain unchanged under smooth deformations). These quasiparticles, first introduced in high-energy physics and quantum field theory, have since attracted intense interest in condensed matter physics and photonics, owing to their potential as robust carriers for information storage and manipulation.

Researchers at Sun Yat-sen University and Tianjin University recently reported the first experimental realization of single-photon quantum skyrmions (i.e., localized light structures) in a semiconductor cavity quantum electrodynamics (QED) system. Their paper, published in Nature Physics, could open new possibilities for the study of quantum light-matter interactions, while also contributing to the advancement of photonic quantum devices.

“Our work was motivated by the longstanding challenge of realizing topological photonic structures—specifically skyrmions—at the quantum level,” Ying Yu, co-senior author of the paper, told Phys.org.

Using sound to remember quantum information 30 times longer

While conventional computers store information in the form of bits, fundamental pieces of logic that take a value of either 0 or 1, quantum computers are based on qubits. These can have a state that is simultaneously both 0 and 1. This odd property, a quirk of quantum physics known as superposition, lies at the heart of quantum computing’s promise to ultimately solve problems that are intractable for classical computers.

Many existing quantum computers are based on superconducting electronic systems in which electrons flow without resistance at extremely low temperatures. In these systems, the quantum mechanical nature of electrons flowing through carefully designed resonators creates superconducting qubits.

These qubits are excellent at quickly performing the logical operations needed for computing. However, storing information—in this case quantum states, mathematical descriptors of particular quantum systems—is not their strong suit. Quantum engineers have been seeking a way to boost the storage times of quantum states by constructing so-called “quantum memories” for superconducting qubits.

The shape of the universe revealed through algebraic geometry

How can the behavior of elementary particles and the structure of the entire universe be described using the same mathematical concepts? This question is at the heart of recent work by the mathematicians Claudia Fevola from Inria Saclay and Anna-Laura Sattelberger from the Max Planck Institute for Mathematics in the Sciences, recently published in the Notices of the American Mathematical Society.

Mathematics and physics share a close, reciprocal relationship. Mathematics offers the language and tools to describe physical phenomena, while physics drives the development of new mathematical ideas. This interplay remains vital in areas such as and cosmology, where advanced mathematical structures and physical theory evolve together.

In their article, the authors explore how algebraic structures and geometric shapes can help us understand phenomena ranging from particle collisions such as happens, for instance, in particle accelerators to the large-scale architecture of the cosmos. Their research is centered around . Their recent undertakings also connect to a field called positive geometry—an interdisciplinary and novel subject in mathematics driven by new ideas in and cosmology.

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