Small organic molecules underpin modern life, from medicines and flavours to advanced materials. Much of this functional diversity comes from shape: modest changes in a molecule's 3D structure can completely change its properties.
Alkynes are widely used as feedstock chemicals and functional groups in organic chemistry. However, while the hydrogenation from an alkyne to an alkene is well established, typical methods for the reverse reaction—conversion of an alkene to an alkyne—are based on elimination chemistry reported in the 1860s and use forcing conditions (strong base or high temperatures).
The exponential growth of scientific literature presents an increasingly acute challenge across disciplines. Hundreds of thousands of new chemical reactions are reported annually, yet translating them into actionable experiments becomes an obstacle1,2. Recent applications of large language models (LLMs) have shown promise3,4,5,6, but systems that reliably work for diverse transformations across de novo compounds have remained elusive. Here we introduce MOSAIC (Multiple Optimized Specialists for AI-assisted Chemical Prediction), a computational framework that enables chemists to harness the collective knowledge of millions of reaction protocols.
Now, researchers have created an artificial-intelligence system that vastly simplifies and accelerates the process of chemical synthesis. The system, which is called MOSAIC and is described in a study published in Nature on 19 January, recommended conditions that researchers were able to use to generate 35 compounds with the potential to become products like pharmaceuticals, agrochemicals or cosmetics without needing to do any further trawling or tweaking.
GEMINI leverages a computationally designed protein assembly as an intracellular memory device to record the history of individual cells. GEMINI grows predictably within live cells, capturing cellular events as tree-ring-like fluorescent patterns for imaging-based retrospective readout. Absolute chronological information of activity histories is attainable with hour-level accuracy.
Biology is undergoing a transformation. After centuries of studying life as it evolves naturally, researchers are now using a combination of computation and genome engineering to intervene, generating new proteins and even whole bacteria from scratch. The use of artificial-intelligence tools to design biological components, an approach known as generative biology, is set to turbocharge this area of research. Just last year, scientists used AI-assisted design to produce artificial genes that can be expressed in mammalian cells.
In terms of making things happen, energy is an indispensable consideration. Systems spontaneously tend towards the lowest-energy state. When a system reaches equilibrium, no further energy can be extracted. That maximum entropy, lowest energy state is the inevitable end-state of the Universe. But until that moment arrives, reactions of all kinds will occur, continuing to liberate energy. In our bodies, chemical bonds break and reform: releasing energy.