bioRxivBioengineeringPreprint
Accurate antibody loop structure prediction enables zero-shot design of target-specific antibodies
Yewon Bang, Yoon‐Aa Choi, Jeonghyeon GuiD, Sohee KwoniD, Dohoon LeeiD, Eun Seo Lee, Myeong Sup LeeiD, Sangchoon Lee, Soyul Lee, Jungsub Lim, Jin Young Maeng, Juno NamiD, Jinsung NohiD, Hyunjeong Oh, Sun Young ParkiD, Taeyong ParkiD, Sumin Seo, Chaok SeokiD, Moo Young Song, Jonghun WoniD, Hyeonuk WooiD, Jinsol YangiD, Min Ji Yoon, Woong Bae, Jae‐Hoon KimiD, , Hasun Yu
Abstract
Protein loops, characterized by their versatile structures with varying sizes and shapes, can recognize a wide range of targets with high specificity and affinity. The variable loops of the antibody complementarity-determining region (CDR) are particularly crucial for immune responses and therapeutic applications due to their effective target recognition capabilities. Accurate structure prediction of these antibody loops is essential for the efficient in silico design of target-binding antibodies for therapeutic or industrial use. However, predicting antibody loop structures is challenging due to the lack of evolutionary information from related proteins. Thus, a successful ab initio structure prediction method, which operates without structural templates or related sequences, is crucial for the effective design of antibody loop-mediated interactions. This study demonstrates that highly accurate antibody loop structure prediction enables the effective zero-shot design of target-binding antibody loops. The performance of loop design has been shown to depend on the accuracy of ab initio loop structure prediction, as tested with two versions of our design model. The high affinity, diversity, novelty, and specificity of the antibody loops designed with these new methods were validated experimentally on four target proteins.
- assay: protein structure
- research focus: drug response / drug discovery
- research focus: protein structure prediction
- approach: deep learning
- approach: statistical model
- Citations
- 6
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