March 26, 2024, 4:43 a.m. | Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng, Liang Wang, Quanquan Gu

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.16576v1 Announce Type: cross
Abstract: Antibody design, a crucial task with significant implications across various disciplines such as therapeutics and biology, presents considerable challenges due to its intricate nature. In this paper, we tackle antigen-specific antibody design as a protein sequence-structure co-design problem, considering both rationality and functionality. Leveraging a pre-trained conditional diffusion model that jointly models sequences and structures of complementarity-determining regions (CDR) in antibodies with equivariant neural networks, we propose direct energy-based preference optimization to guide the generation …

abstract antibody arxiv biology challenges cs.lg design energy nature optimization paper protein q-bio.bm therapeutics type via

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Scientist

@ Publicis Groupe | New York City, United States

Bigdata Cloud Developer - Spark - Assistant Manager

@ State Street | Hyderabad, India