In our paper “Extraction of organic chemistry grammar from unsupervised learning of chemical reactions,” published in the peer-reviewed journal Science Advances, we extract the "grammar" of organic chemistry's "language" from a large number of organic chemistry reactions. For that, we used RXNMapper, a cutting-edge, open-source atom-mapping tool we developed.
Paving the way to the era of Accelerated Discovery, our IBM Research team has developed an AI system that can help speed up the design of molecules for novel antibiotics. In a recent Nature Biomedical Engineering paper, we outline how we used it to create two new non-toxic antimicrobial peptides (AMPs) with strong broad-spectrum potency. Our approach outperforms other leading de novo AMP design methods by nearly 10 percent.
IBM researchers in Japan launch the IBM Molecule Generation Experience, a tool that accelerates new materials design with AI and Hybrid Cloud.
PAGs play a vital role in the manufacturing of computer chips. They are also one of several classes of chemical compounds that have recently come under enhanced scrutiny from environmental regulators. Researchers have been racing to create more sustainable ones – but the traditional process of discovering new materials is too slow, too costly, and too risky. So IBM researchers have turned to AI for help – and created new PAGs much, much faster, paving the way to the era of Accelerated Discovery.