In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...

Scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs, opening up a world of possibilities in the computational design ...

Advancements in spatial proteomics enable detailed tissue mapping, linking protein localization to disease mechanisms and ...

A recent article in hLife explores the advancements in protein science recognized by the 2024 Nobel Prize in Chemistry. The ...

Researchers developed a new machine learning method that, given a relevant amino acid sequence, can automatically predict the location of a protein in any human cell line down to the single-cell level ...

WEST LAFAYETTE, Ind. – Proteins are often called the working molecules of the human body. A typical body has more than 20,000 different types of proteins, each of which are involved in many functions ...

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...

A year and a half later, the team has reported – again in Nature ("Targeting protein-ligand neosurfaces with a generalizable deep learning tool") – an exciting advancement of this technology. They ...

In 2023, scientists in the joint School of Engineering and School of Life Sciences Laboratory of Protein Design and Immunoengineering (LPDI), led by Bruno Correia, published in Nature a deep-learning ...