The database of 200 million protein-structure predictions now includes homodimers, adding new biological relevance.
Leveraging AI and quantum calculations, scientists developed a new tool that yielded higher-quality structural information and solved notoriously elusive proteins.
Structural biology is shifting from predicting protein shapes to uncovering broader organizational rules; AI tools like AlphaFold have made large-scale protein structure data far ...
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 ...
Proteins, one of the smallest building blocks of life on Earth, hold promise for answering some of biology's biggest ...
Using a tool to solve a protein's structure, for most researchers in the world of structural biology and computational chemistry, is not unlike using the Rosetta Stone to unlock the secrets of ancient ...
Giving Structure to Language: Profluent’s AI Models Move toward Precise and Steerable Protein Design
The “ChatGPT moment” for biology proceeds to unfold as protein language models, or machine learning tools trained on large databases of protein sequences, work to decode the language of life with the ...
In 2020, news headlines repeated John Moult’s words at the end of a stunning competition: Artificial intelligence had “solved” a long-standing grand challenge in biology, protein structure prediction.
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