Publication

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Related publications (82)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Hamed Khakzad, Casper Alexander Goverde, Arne Schneuing, Ilia Igashov

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cambridge2023

, , , ,

De novo protein design enhances our understanding of the principles that govern protein folding and interactions, and has the potential to revolutionize biotechnology through the engineering of novel protein functionalities. Despite recent progress in comp ...

2023

, ,

Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...

eLIFE SCIENCES PUBL LTD2023

Author summaryWhen two protein families interact, their sequences feature statistical dependencies. First, interacting proteins tend to share a common evolutionary history. Second, maintaining structure and interactions through the course of evolution yiel ...

PUBLIC LIBRARY SCIENCE2023

, , , , , , ,

The present application relates to a computer-implemented systems and methods for protein interaction design using surface fingerprints. The method comprises predicting at least one target interface site with high binding propensity, wherein, optionally, t ...

2023

Computer-implemented design of peptide:receptor signaling complexes for enhanced chemotaxis

Patrick Daniel Barth, Robert Everett Jefferson

The present invention relates to a computer-implemented method for engineering the interaction between a protein and a cognate peptide that are capable of forming a molecular complex, wherein the method comprises (a) preparing in silico a library of test p ...

2023

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics

Li Tang, Bruno Emanuel Ferreira De Sousa Correia, Sandrine Madeleine Suzanne Georgeon, Pablo Gainza Cirauqui, Anthony Marchand, Leo Scheller, Lucia Bonati, Stéphane Rosset, Sailan Shui

Protein-based therapeutics, such as monoclonal antibodies and cytokines, are important therapies for various pathophysiological conditions such as oncology, autoimmune disorders, and viral infections. However, the wide application of such protein therapeut ...

2023

Difference in astringency of the main pea protein fractions

Francesco Stellacci, Hanna Fanny Clarisse Lesme

Interactions between food and saliva govern complex mouthfeel perceptions such as astringency. Herein, we present a study of the interactions of salivary proteins with the main pea protein fractions that are obtained by isoelectric and salt precipitation ( ...

London2023

Tricyclic peptides have reduced conformational flexibility, making them well suited for ligand development. Researchers have now generated large combinatorial libraries of tricyclic peptides using a disulfide-directing motif. Screening these libraries disc ...

NATURE PORTFOLIO2023

Towards automating de novo protein design for novel functionalities: controlling protein folds and protein-protein interactions

Zander Harteveld

The sheer size of the protein sequence space is massive: a protein of 100 residues can have 20^100 possible sequence combinations; and knowing that this exceeds the number of atoms in the universe, the chance of randomly discovering a stable new sequence w ...

EPFL2022