New Study Challenges Established Model of How Proteins Help ...

Researchers at University of Utah Health and Brigham Young University have tracked how a chaperone guides protein folding, challenging a prevailing model of ...

Machine learning cracked the protein-folding problem and won the ...

The challenge of protein folding · A new era of machine learning · Designer proteins to fight disease · AI will enable research's next chapter.

Did AI Solve the Protein-Folding Problem?

Almost instantaneously, a squiggly blue model of a molecule appears. This protein molecule has never been modeled in a lab using techniques like the ones ...

Simulations reveal mechanism behind protein build-up in ...

Researchers have used computational models to understand what drives the accumulation of alpha-synuclein protein, a key culprit in the ...

UCLA Study Challenges Long-Held Beliefs in Bioengineering and ...

UCLA stem cell scientists ID surprise genetic instructions for boosting protein secretion, with big implications for biotech and cell therapy.

The Nobel Prize in Chemistry 2024 - Popular information

The research group drew a protein with an entirely new structure, and then had Rosetta compute which type of amino acid sequence could result in the desired ...

Recent Advances in Deep Learning for Protein-Protein Interaction ...

AlphaFold utilizes a deep-learning-based approach to predict protein structure, a problem of profound significance in biology. The AI model has been ...

DeepMind says it will release the structure of every protein known to ...

AlphaFold can predict the shape of proteins to within the width of an atom. The breakthrough will help scientists design drugs and understand ...

The Protein Science Revolution: Implications for human health and ...

RGA's Craig Armstrong explores recent key breakthroughs in protein science, the new possibilities they enable, and the potential implications for mortality ...

How AI Revolutionized Protein Science, but Didn't End It

Some claimed that AlphaFold2 would revolutionize drug development; now that biologists could quickly learn proteins' shapes, they could create ...

The Protein Folding Problem - PMC - PubMed Central

Structural genomics is likely to help here (87, 222). In any case, the current successes in computer-based predictions of native protein structures are far ...

Generative models for protein sequence modeling: recent advances ...

RNN and its variants have been implemented in protein design tasks for both generative and discriminative applications. For example, a ...

Groundbreaking Study Challenges Key Theory on Parkinson's ...

A new study reveals that liquid droplets formed by proteins may protect against, rather than promote, the aggregation into amyloid fibrils seen in Parkinson's ...

The opportunities and challenges posed by the new generation of ...

PTM sites are generally found on accessible, flexible regions of proteins, and AlphaFold models can help locate such regions. This approach effectively filters ...

De novo design of protein structure and function with RFdiffusion

There has been considerable recent progress in designing new proteins using deep-learning methods1–9. Despite this progress, a general ...

Professor David Baker's audacious approach to creating new proteins

They digest foods, fire neurons and contract muscles. To do their jobs, they fold up into specific shapes—following a code that scientists haven't been able to ...

Case study: AlphaFold uses open data and AI to discover the 3D ...

To address this challenge, scientists looked towards computational methods, to help predict protein structures. How a protein folds itself ...

AlphaFold—for predicting protein structures - Lasker Foundation

Third, being able to predict protein structure helps us understand how disease-associated mutations might affect protein structure and function, ...

DeepMind solves 50-year-old challenge in predicting protein folding

CASP was founded almost 30 years ago as a means of spurring research to help solve this great scientific challenge by sharing their progress ...

A comparative study of protein structure prediction tools for ...

Recent advances in deep learning and artificial intelligence have led to the development of several protein structure prediction tools, such as ...