Apple developed an alternative AI model to predict the 3D structure of proteins, and it shows promise. Here are the details.

Scientists from Université de Lille, France, Linköping University, Sweden, and collaborating institutions have introduced MassiveFold, a new version of AlphaFold that dramatically reduces computing ...

Receptor proteins, expressed on the cell surface or within the cell, bind to different signaling molecules, known as ligands, ...

Harnessing the power of AI, a research team at the MRC-University of Glasgow Center for Virus Research has launched ...

Jacobs School researcher Thomas Grant has secured a $2.18 million grant to pioneer a protein-studying tool that could lead to ...

From CASP to the Virtual Cell Challenge, researchers are leveraging science competitions and high-risk, high-reward grants to ...

By combining AI with molecular dynamics simulations, researchers at the Department of Energy's Oak Ridge National Laboratory ...

Physical interactions between proteins influence anything from cell signaling and growth to immune responses, so the ability to control these interactions is of great interest to biologists.

A Nigerian researcher, Muinat Zubair, has developed a method for predicting protein structure and protein-protein interactions using a combination of experimental and computational approaches.Zubair ...

Recent advances in computational biology have revolutionised the field of protein structure and function prediction. Traditionally, determining the three‐dimensional architecture of a protein from its ...

By combining AI with molecular dynamics simulations, researchers have developed a new tool to more accurately predict how ...