Predicting purification process fit of monoclonal antibodies using machine learning
In early-stage development of therapeutic monoclonal antibodies, assessment of the viability
and ease of their purification typically requires extensive experimentation. However, the …
and ease of their purification typically requires extensive experimentation. However, the …
ParaSurf: A Surface-Based Deep Learning Approach for Paratope-Antigen Interaction Prediction
Motivation Identifying antibody binding sites, is crucial for develo** vaccines and
therapeutic antibodies, processes that are time-consuming and costly. Accurate prediction of …
therapeutic antibodies, processes that are time-consuming and costly. Accurate prediction of …
Accurate antibody loop structure prediction enables zero-shot design of target-specific antibodies
Y Bang, YA Choi, J Gu, S Kwon, D Lee, ES Lee… - bioRxiv, 2024 - biorxiv.org
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 …
recognize a wide range of targets with high specificity and affinity. The variable loops of the …
[PDF][PDF] IgFlow: Flow Matching for De Novo Antibody Design
In this work, we present IgFlow, an SE (3)-flow matching model for de novo design of
antibody structures. We focus on generating novel variable domain regions of the antibody …
antibody structures. We focus on generating novel variable domain regions of the antibody …