Breaking the Fourth Wall: Modulating Quaternary Associations for Protein Regulation and Drug Discovery

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

Anthony Marchand

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

EPFL2024

Predicting protein interactions using geometric deep learning on protein surfaces

Freyr Sverrisson

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

EPFL2024

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Mahdi Hijazi

The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

EPFL2024

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

Alexandra Krina Van Hall-Beauvais

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 functions. Evolution has created highly efficient proteins in diverse fold ...

EPFL2023

Optimised three-dimensional in vitro retinoblastoma models tailored for drug discovery and clinical translatability

Irina Sinenko

Retinoblastoma, while relatively rare, stands as the most prevalent intraocular cancer. In Switzerland, the survival rate approaches 100%, but it drops to less than 50% in low-income countries. The current treatment options for retinoblastoma rely on a lim ...

EPFL2023

De novo design of protein interactions with learned surface fingerprints

Didier Trono, Henning Paul-Julius Stahlberg, Beat Fierz, Priscilla Turelli, Bruno Emanuel Ferreira De Sousa Correia, Elisa Oricchio, Sandrine Madeleine Suzanne Georgeon, Dongchun Ni, Andreas Scheck, Michael Bronstein

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

2023

Systems and methods for de novo design of protein interactions with learned surface fingerprints

Andreas Scheck, Michael Bronstein, Anthony Marchand, Pablo Gainza Cirauqui, Zander Harteveld, Sarah Wehrle, Freyr Sverrisson, Alexandra Krina Van Hall-Beauvais

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

Hierarchy of the Components in Spray-Dried, Protein-Excipient Particles Using DNP-Enhanced NMR Spectroscopy

David Lyndon Emsley, Pierrick Berruyer, Andrea Bertarello, Baptiste Busi

Protein-based drugs are becoming increasingly important, but there are challenges associated with their formulation (for example, formulating stable inhalable aerosols while maintaining the proper long-term stability of the protein). Determining the morpho ...

Amer Chemical Soc2023

A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

Lucien Fabrice Krapp

Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

EPFL2023

The predictive capacity of in vitro preclinical models to evaluate drugs for the treatment of retinoblastoma

Paul Joseph Dyson, Irina Sinenko, Roland Christopher Turnell-Ritson

Retinoblastoma is a rare childhood cancer of the eye. Of the small number of drugs are used to treat retinoblastoma, all have been repurposed from drugs developed for other conditions. In order to find drugs or drug combinations better suited to the improv ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2023

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

Anthony Marchand

EPFL2024

Predicting protein interactions using geometric deep learning on protein surfaces

Freyr Sverrisson

EPFL2024

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Mahdi Hijazi

EPFL2024