Researchers Unite Protein Sequence and Structure to Map the Protein Universe
An international team of researchers, including those from the University of Haifa, Tel Aviv University, and the Earth-Life Science Institute (ELSI), has developed a new protein language model called Contrastive Learning Sequence-Structure (CLSS). This model integrates both amino acid sequences and three-dimensional structures of proteins to create a unified 'protein world map.' Traditionally, protein analysis has treated sequence and structure separately, despite their complex relationship. CLSS uses contrastive learning to produce similar numerical representations (embeddings) for both the sequence and structure of a protein, allowing them to occupy similar locations on the map. This approach provides a novel way to visualize relationships across the vast protein universe and investigate their evolution over billions of years. The findings, led by Prof. Rachel Kolodny, PhD candidate Guy Yanai, Prof. Nir Ben-Tal, graduate student Gabriel Axel, and Specially Appointed Associate Professor Liam M. Longo, wer...
