Though experimentation is still king in most chemists’ minds, computational chemistry has the potential to transform the field.
AI for drug discovery: What can we do?
Artificial intelligence and machine learning are playing increasing roles in drug discovery, potentially saving significant time and money.
Can we live without AI?
The benefits and controversies around AI are clear, but by drawing on current experiences, we can establish an order that ensures AI does not become a threat but a very useful aid.
Neural networks overcome the setbacks of current computational drug discovery
Computer-aided drug discovery looks to neural networks that can better predict chemical properties to streamline the search for new therapeutics.
A “time-accelerated computational microscope” provides biologists with powerful insights
A new simulation technique accelerates modeling to help us better understand complex molecular processes and facilitate rational drug design.
Artificial intelligence could be promising alternative to animal models
Replacing animal testing with the ever-growing capabilities of AI and deep learning could help minimize the need for animals in scientific discovery.
Simulations that reach biological timescales
A new computational technique allows researchers to model biological processes with better accuracy and at a lower computational cost.
Skin pigment properties and the importance of heterogeneity
Computational chemistry is key to understanding the unusual properties of eumelanin.
Computer simulations of organic materials for next-generation batteries
Computer simulations provide a better means of optimizing, predicting, and understanding experimental observations in the search for new battery materials.
The high-throughput highway to computational optoelectronic semiconductor screening
High-throughput computational materials screening is turning out to be an efficient highway to optoelectronic semiconductor design.