A comprehensive overview of recent advances in generative models for antibodies

FX Meng and N Zhou and GC Hu and RT Liu and YY Zhang and M Jing and QZ Hou, COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 23, 2648-2660 (2024).

DOI: 10.1016/j.csbj.2024.06.016

Therapeutic antibodies are an important class of biopharmaceuticals. With the rapid development of deep learning methods and the increasing amount of antibody data, antibody generative models have made great progress recently. They aim to solve the antibody space searching problems and are widely incorporated into the antibody development process. Therefore, a comprehensive introduction to the development methods in this field is imperative. Here, we collected 34 representative antibody generative models published recently and all generative models can be divided into three categories: sequence- generating models, structure-generating models, and hybrid models, based on their principles and algorithms. We further studied their performance

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