Researchers at the Massachusetts Institute of Technology have developed a generative AI model that was able to generate novel antibiotic structures from either chemical fragments or de novo, starting from ammonia, methane, water or no starting point at all. In a study that was published online in Cell, the team tested two dozen of more than 10 million structures that were proposed as potential antibiotics by the model.

Deep learning tools for protein design can also be used to create molecules that bind to them. Certain peptides, such as intrinsically disordered proteins (IDPs), are challenging to target due to their variable nature. However, scientists from the lab of Nobel laureate David Baker have developed a method to generate binders for IDPs by searching the world’s largest protein database with their AI-powered tool RFdiffusion.

Rakovina Therapeutics Inc. has reported progress in its AI-driven KT-5000AI program, advancing the development of precision ATR (ataxia telangiectasia and Rad3-related) inhibitors designed to disrupt the DNA damage response (DDR) pathway in cancer cells. Through its collaboration with Variational AI Inc., Rakovina has evaluated a vast chemical space of potential molecular structures using Variational’s AI Enki platform to identify novel compounds

Qanatpharma AG (QP), Zuse Institute Berlin (ZIB), Enamine Ltd. and Proteros biostructures GmbH have announced the launch of a research collaboration to accelerate the discovery of novel therapeutics targeting cerebral perfusion deficits associated with subarachnoid hemorrhage (SAH).

Chugai Pharmaceutical Co. Ltd. and Gero Pte Ltd. have entered into a joint research and license agreement to develop novel therapies for age-related diseases. Chugai will create novel antibody-drug candidates for new drug targets discovered by Gero using its AI target discovery platform.

Researchers at the Massachusetts Institute of Technology and Recursion Pharmaceuticals Inc. have released an open-source AI model that can predict the binding strength of small molecules as well as structures of proteins and biomolecular complexes. The model, which is called Boltz-2 and was released by the research team on the developer platform Github on June 6, addresses a major bottleneck in drug discovery with its improved ability to predict binding strengths.

The U.S. FDA’s decision to phase out animal testing for INDs is driving a new market of alternative, nonanimal testing technologies like organoids and organs-on-a-chip, speakers at Bio Korea 2025 said.

Traditional neoantigen prediction methods primarily rely on HLA-peptide binding databases, often producing false positives. This challenge highlights the need for improved strategies to identify truly immunogenic neoantigens. Neoantigen-based cancer vaccines have shown promising efficacy in recent clinical trials for treating solid tumors, offering a potential solution.

Scientists at the Center for Genomic Regulation (CRG) have developed an AI-based tool to design thousands of sequences that regulate DNA. They have also synthesized these molecules, called enhancers, to control gene activation in mouse hematopoietic stem cells, which they have tested in vitro.