Rapid and accurate protein structure database search using inverse folding model and contrastive learning

Lyu, Q.; Wei, H.; Chen, S.; Peng, Z.; Yang, J.

doi:10.1101/2025.05.15.654382

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bioRxiv · 10.1101/2025.05.15.654382

Rapid and accurate protein structure database search using inverse folding model and contrastive learning

Lyu, Q.·Wei, H.·Chen, S.·Peng, Z.·Yang, J.

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Abstract

Protein structure database search has become increasingly challenging due to the growing number of experimental and computational structures. We introduce mTM-align2, a novel two-step approach for rapid and accurate protein structure database search. In the first step, protein structures are first transformed into embeddings using a pre-trained inverse folding model (ESM-IF) and 3D Zernike polynomials. The ESM-IF embeddings are further optimized through a contrastive learning network, which is trained on [~]7 million structure pairs. Structures with similar embeddings are returned on the fly in this step. The second step employs a rapid structure alignment program to refine top candidates, ensuring high precision and producing high-quality alignments. Extensive benchmarks reveal that mTM-align2 performs competitively compared to other leading methods, completing monomeric structure search in seconds with over 90% precision for the top 10 hits. The t-SNE visualization of the mTM-align2 embeddings for thousands of structures demonstrates that our embeddings are structurally informed, capturing the global structural features. It uncovers insights such as structure misclassifications and ambiguous structural class boundaries. A web server for mTM-align2 is accessible at https://yanglab.qd.sdu.edu.cn/mTM-align/.

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Lyu, Q., Wei, H., Chen, S., Peng, Z., Yang, J.. 2025-05-20. Rapid and accurate protein structure database search using inverse folding model and contrastive learning. https://doi.org/10.1101/2025.05.15.654382

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