Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens

F Guarra, G Colombo - Journal of Chemical Theory and …, 2023 - ACS Publications
The design of new biomolecules able to harness immune mechanisms for the treatment of
diseases is a prime challenge for computational and simulative approaches. For instance, in …

[HTML][HTML] Computational design of vaccine immunogens

KM Castro, A Scheck, S **ao, BE Correia - Current opinion in …, 2022 - Elsevier
Computational protein engineering has enabled the rational design of customized proteins,
which has propelled both sequence-based and structure-based immunogen engineering …

Deep learning of protein sequence design of protein–protein interactions

R Syrlybaeva, EM Strauch - Bioinformatics, 2023 - academic.oup.com
Motivation As more data of experimentally determined protein structures are becoming
available, data-driven models to describe protein sequence–structure relationships become …

De novo design of site-specific protein interactions with learned surface fingerprints

P Gainza, S Wehrle, A Van Hall-Beauvais, A Marchand… - bioRxiv, 2022 - biorxiv.org
Physical interactions between proteins are essential for most biological processes
governing life. However, the molecular determinants of such interactions have been …

Nucleic Acid-Protein Interaction Prediction Using Geometric Deep Learning

E Geraseva, A Golovin - Russian Supercomputing Days, 2023 - Springer
In biology, it remains challenging to predict interactions between proteins and DNA or RNA.
When it comes to nucleic acids, existing methods of binding site identification or interaction …

De novo designed proteins: a study in engineering novel folds and functions

V Hall-Beauvais, A Krina - 2023 - infoscience.epfl.ch
Proteins control nearly every facet of life on a molecular level. Proteins are formed from
linear strings of amino acids, which fold into three-dimensional structures that can enact …

Leveraging topology, geometry, and symmetries for efficient Machine Learning

M Defferrard - 2022 - infoscience.epfl.ch
When learning from data, leveraging the symmetries of the domain the data lies on is a
principled way to combat the curse of dimensionality: it constrains the set of functions to …

[PDF][PDF] Project 2. Single amino acid prediction at protein-protein interaction interfaces

M Jansen, K Roman, J Zeng, ML Course - epfl.ch
Proteins consist of building blocks which are called amino acids. Computational protein
design can benefit from accurate amino acid type predictions at the interfaces between …