AI Medical Compendium Journal:
Nature chemistry

Showing 1 to 10 of 11 articles

Machine learning designs new GCGR/GLP-1R dual agonists with enhanced biological potency.

Nature chemistry
Several peptide dual agonists of the human glucagon receptor (GCGR) and the glucagon-like peptide-1 receptor (GLP-1R) are in development for the treatment of type 2 diabetes, obesity and their associated complications. Candidates must have high poten...

Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning.

Nature chemistry
Late-stage functionalization is an economical approach to optimize the properties of drug candidates. However, the chemical complexity of drug molecules often makes late-stage diversification challenging. To address this problem, a late-stage functio...

Deep learning study of tyrosine reveals that roaming can lead to photodamage.

Nature chemistry
Amino acids are among the building blocks of life, forming peptides and proteins, and have been carefully 'selected' to prevent harmful reactions caused by light. To prevent photodamage, molecules relax from electronic excited states to the ground st...

Parallel transmission in a synthetic nerve.

Nature chemistry
Bioelectronic devices that are tetherless and soft are promising developments in medicine, robotics and chemical computing. Here, we describe bioinspired synthetic neurons, composed entirely of soft, flexible biomaterials, capable of rapid electroche...

Deep learning to design nuclear-targeting abiotic miniproteins.

Nature chemistry
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of ...

Stereoelectronic effects in stabilizing protein-N-glycan interactions revealed by experiment and machine learning.

Nature chemistry
The energetics of protein-carbohydrate interactions, central to many life processes, cannot yet be manipulated predictably. This is mostly due to an incomplete quantitative understanding of the enthalpic and entropic basis of these interactions in aq...

Quantum machine learning using atom-in-molecule-based fragments selected on the fly.

Nature chemistry
First-principles-based exploration of chemical space deepens our understanding of chemistry and might help with the design of new molecules, materials or experiments. Due to the computational cost of quantum chemistry methods and the immense number o...

Computational advances in combating colloidal aggregation in drug discovery.

Nature chemistry
Small molecule effectors are essential for drug discovery. Specific molecular recognition, reversible binding and dose-dependency are usually key requirements to ensure utility of a novel chemical entity. However, artefactual frequent-hitter and assa...