ParaSurf Joins Neurosnap: AI-Driven Antibody-Antigen Binding Site Prediction Now Accessible to All

ParaSurf Joins Neurosnap: A Collaboration for AI-Driven Antibody-Antigen Binding Site Prediction.

Researchers from the Centre for Research and Technology Hellas and the Technical University of Madrid developed ParaSurf, a state-of-the-art deep learning model for antibody-antigen interaction prediction. Parasurf, which is especially useful in the field for biomedical research and drug development has now been integrated into Neurosnap, a leading AI-powered structural biology platform.  

More specifically, ParaSurf predicts antibody binding sites by analyzing molecular surface features, including geometric, chemical, and electrostatic properties. These features are used to train a hybrid deep neural network that combines a 3D ResNet with a transformer module.

Neurosnap hosts cutting-edge models such as AlphaFold3, DiffDock, and now ParaSurf, making antibody-antigen binding site prediction more accessible than ever.

This integration allows researchers to easily analyze antibody binding sites without the need for extensive computational resources or local installations. By simply uploading an antibody structure, users can obtain high-confidence binding site predictions in less than a minute.

This marks a major milestone in making AI-powered antibody design and validation more efficient and accessible as ParaSurf can serve as a powerful tool for validating new protein binder designs in silico.

ParaSurf's Contribution to Biomedical Research 

The ability of ParaSurf to accurately identify antibody binding sites makes it a valuable tool in biomedical research and the development of therapeutic antibodies. Some of its key applications include:

• Advancement of Therapeutic Antibodies: Pharmaceutical companies can use ParaSurf for faster and more accurate selection of antibodies with strong binding affinity to pathogens, leading to more effective treatments.

• Analysis of Immune Responses: Researchers can study how different antibodies interact with antigens, contributing to a better understanding of immune mechanisms and the development of new vaccines.

• Personalized Medicine: By analyzing interactions between patients and molecular targets, ParaSurf can support personalized therapeutic approaches, providing predictions tailored to the genetic profile of each patient.

Read the Paper: https://doi.org/10.1093/bioinformatics/btaf062

Try ParaSurf on Neurosnap: https://neurosnap.ai/service/ParaSurf

See an Example Job in Action: Example Prediction 

See the Code: https://github.com/aggelos-michael-papadopoulos/ParaSurf