Laboratoire de conception de protéines et d'immuno-ingénierie

Laboratoire

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The field of protein design has made remarkable progress over the past decade. Historically, the low reliability of purely structure-based design methods limited their application, but recent strategies that combine structure-based and sequence-based calcu ...

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 ...

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 ...

Post-translational modifications (PTMs) play a pivotal role in regulating protein structure, interaction, and function. Aberrant PTM patterns are associated with diseases. Moreover, individual PTMs have a complex interaction with each other, known as PTM c ...

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 ...

Recently, single-particle cryo-electron microscopy emerged as a technique capable of determining protein structures at near-atomic resolution and resolving protein dynamics with a temporal resolution ranging from second to milliseconds. This thesis describ ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Scaffold-based protein libraries are designed to be both diverse and rich in functional/folded proteins. However, introducing an extended diversity while preserving stability of the initial scaffold remains a challenge. Here we developed an original approa ...

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 ...

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 ...

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 ...

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 ...

Following the hugely successful application of deep learning methods to protein structure prediction, an increasing number of design methods seek to leverage generative models to design proteins with improved functionality over native proteins or novel str ...

Proteins are the basic building blocks necessary for the operation and regulation of virtually all functions in living organisms. Over millions of years, evolution has created a vast repertoire of proteins finely tuned to execute their biological functions ...

Understanding how proteins fold into their native structure is a fundamental problem in biophysics, crucial for protein design. It has been hypothesized that the formation of a molten globule intermediate precedes folding to the native conformation of glob ...

Laboratoire de conception de protéines et d'immuno-ingénierie

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Opportunities and challenges in design and optimization of protein function

Predicting protein interactions using geometric deep learning on protein surfaces

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

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

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

Microsecond Time-Resolved Cryo-Electron Microscopy

A new age in protein design empowered by deep learning

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

De novo protein design by inversion of the AlphaFold structure prediction network

Generative power of a protein language model trained on multiple sequence alignments

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

De novo design of protein interactions with learned surface fingerprints

Design of an artificial phage-display library based on a new scaffold improved for average stability of the randomized proteins

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

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

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics

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

Deep learning approaches for conformational flexibility and switching properties in protein design

Targeting molecular surfaces to engineer novel protein-based immunogens and inhibitors

Molten globule-like transition state of protein barnase measured with calorimetric force spectroscopy