The use of DNA scaffolds could mark a turning point in HIV vaccine design. Scientists at Scripps Research and the Massachusetts Institute of Technology (MIT) have created a new vaccine platform based on DNA origami, a material that the immune system does not recognize as a threat, avoiding unwanted responses.
In an effort to generate an effective and safer inhibitor, researchers at the University of Cape Town, University of Dundee and Massachusetts Institute of Technology used structure-guided rational design to improve on their previously reported 2,8-diaryl-1,5-naphthyridine inhibitor.
Two independent studies applied CRISPR-based genetic editing – one to treat leukemia and the other to target myeloma – to overcome the challenges faced by CAR T cells, such as exhaustion, impaired activation and fratricide, a phenomenon in which they attack each other.
Loss of function variants in the lipid transporter gene ATP-binding cassette ABC transporter A7 (ABCA7) nearly double the risk of developing Alzheimer’s disease (AD), which makes ABCA7 the strongest AD genetic risk factor after ApoE4.
Loss of function variants in the lipid transporter gene ATP-binding cassette ABC transporter A7 (ABCA7) nearly double the risk of developing Alzheimer’s disease (AD), which makes ABCA7 the strongest AD genetic risk factor after ApoE4.
Loss of function variants in the lipid transporter gene ATP-binding cassette ABC transporter A7 (ABCA7) nearly double the risk of developing Alzheimer’s disease (AD), which makes ABCA7 the strongest AD genetic risk factor after ApoE4.
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.
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.
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.
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.
