Publications de Stéphane Rosset

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The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols an ...

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 protein design has emerged as a powerful tool capable of identifying sequences compatible with pre-defined protein structures. The sequence design protocols, implemented in the Rosetta suite, have become widely used in the protein engineering ...

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 ...

Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted wi ...

Hepatitis C virus (HCV) infection causes similar to 290,000 annual human deaths despite the highly effective antiviral treatment available. Several viral immune evasion mechanisms have hampered the development of an effective vaccine against HCV, among the ...

Anti-CRISPR (Acr) proteins are powerful tools to control CRISPR-Cas technologies. However, the available Acr repertoire is limited to naturally occurring variants. Here, we applied structure-based design on AcrIIC1, a broad-spectrum CRISPR-Cas9 inhibitor, ...

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 ...

De novo design of complex protein folds using solely computational means remains a substantial challenge1. Here we use a robust deep learning pipeline to design complex folds and soluble analogues of integral membrane proteins. Unique membrane topologies, ...

Recent advances in protein-design methodology have led to a dramatic increase in reliability and scale. With these advances, dozens and even thousands of designed proteins are automatically generated and screened. Nevertheless, the success rate, particular ...

De novo protein design has been successful in expanding the natural protein repertoire. However, most de novo proteins lack biological function, presenting a major methodological challenge. In vaccinology, the induction of precise antibody responses remain ...

De novo protein design has enabled the creation of new protein structures. However, the design of functional proteins has proved challenging, in part due to the difficulty of transplanting structurally complex functional sites to available protein structur ...

Deep mutational scanning is a powerful method for exploring the mutational fitness landscape of proteins. Its adaptation to anti-CRISPR proteins, which are natural CRISPR-Cas inhibitors and key players in the co-evolution of microbes and phages, facilitate ...

De novo protein design explores uncharted sequence and structure space to generate novel proteins not sampled by evolution. A main challenge in de novo design involves crafting “designable” structural templates to guide the sequence searches toward adoptin ...

Stéphane Rosset

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Rosetta FunFolDes - A general framework for the computational design of functional proteins

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

A Rosetta-based protein design protocol converging to natural sequences

De novo design of protein interactions with learned surface fingerprints

RosettaSurf-A surface-centric computational design approach

Epitope-focused immunogens targeting the hepatitis C virus glycoproteins induce broadly neutralizing antibodies

Computational design of anti-CRISPR proteins with improved inhibition potency

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics

Computational design of soluble and functional membrane protein analogues

Assessing and enhancing foldability in designed proteins

De novo protein design enables the precise induction of RSV-neutralizing antibodies

Bottom-up de novo design of functional proteins with complex structural features

A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins

Exploring “dark-matter” protein folds using deep learning

Driving Immune Responses with Synthetic Proteins - Development of De Novo Designed Immunogens to Elicit Respiratory Syncytial Virus Neutralizing Antibodies

De Novo Design of Site-specific Protein Binders Using Surface Fingerprints