【ELSI】Uniting sequence and structure to map the protein universe

A new protein language model combines sequence and structure information to reveal relationships across billions of years of evolution

Figure. A protein world map
This 2-dimensional map of the protein universe organizes proteins so that neighboring points are closely related. The colouring indicates different protein structure types.
Credit: Guy Yanai

An international team of researchers, including ELSI, has developed a protein language model that brings together two fundamental sources of information about proteins: their amino acid sequences and their three-dimensional structures. The model provides researchers with a new way to map relationships across the protein universe and investigate how proteins have evolved over billions of years.

The research was led by Prof. Rachel Kolodny and PhD candidate Guy Yanai of the University of Haifa, Prof. Nir Ben-Tal and graduate student Gabriel Axel of Tel Aviv University, and Specially Appointed Associate Professor Liam M. Longo of ELSI. Kolodny also spent five months as a visiting researcher at ELSI developing approaches to analyse the new model. The findings were published in Proceedings of the National Academy of Sciences (PNAS).

Reference
Guy Yanai, Gabriel Axel, Liam M. Longo, Nir Ben-Tal and Rachel Kolodny. Contrastive learning unites sequence and structure in a global representation of protein space PNAS DOI: 10.1073/pnas.2532702123

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