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De novo design of protein interactions with learned surface fingerprints

Michael Bronstein, Stephen M Buckley, Bruno Emanuel Ferreira De Sousa Correia, Beat Fierz, Pablo Gainza Cirauqui, Sandrine Madeleine Suzanne Georgeon, Casper Alexander Goverde, Zander Harteveld, Anthony Marchand, Jane Marsden, Dongchun Ni, Elisa Oricchio, Aaron Simone Petruzzella, Charlène Mireille Raymonde Raclot, Stéphane Rosset, Andreas Scheck, Henning Paul-Julius Stahlberg, Freyr Sverrisson, Alexandra Teslenko, Didier Trono, Priscilla Turelli, Alexandra Krina Van Hall-Beauvais, Sarah Wehrle

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 knowledge gap has been a major obstacle for the comprehensive understanding of cellular protein–protein interaction networks and for the de novo design of protein binders that are crucial for synthetic biology and translational applications. Here we use a geometric deep-learning framework operating on protein surfaces that generates fingerprints to describe geometric and chemical features that are critical to drive protein–protein interactions10. We hypothesized that these fingerprints capture the key aspects of molecular recognition that represent a new paradigm in the computational design of novel protein interactions. As a proof of principle, we computationally designed several de novo protein binders to engage four protein targets: SARS-CoV-2 spike, PD-1, PD-L1 and CTLA-4. Several designs were experimentally optimized, whereas others were generated purely in silico, reaching nanomolar affinity with structural and mutational characterization showing highly accurate predictions. Overall, our surface-centric approach captures the physical and chemical determinants of molecular recognition, enabling an approach for the de novo design of protein interactions and, more broadly, of artificial proteins with function.

2023

Computational design of vaccine immunogens

Karla Montserrat Castro Gilabert, Bruno Emanuel Ferreira De Sousa Correia, Andreas Scheck, Shuhao Xiao

Computational protein engineering has enabled the rational design of customized proteins, which has propelled both sequence-based and structure-based immunogen engineering and delivery. By discerning antigenic determinants of viral pathogens, computational methods have been implemented to successfully engineer representative viral strains able to elicit broadly neutralizing responses or present antigenic sites of viruses for focused immune responses. Combined with improvements in customizable nanoparticle design, immunogens are multivalently displayed to enhance immune responses. These rationally designed immunogens offer unique and powerful approaches to engineer vaccines for pathogens, which have eluded traditional approaches.

CURRENT BIOLOGY LTD2022

On the exploration of novel methodological approaches for immunogen design: case studies in influenza and hepatitis C

Andreas Scheck

Proteins are fundamental components in biological systems and crucial for a variety of biological functions. Over the last decades, significant progress in structural biology has facilitated the study of proteins and their interactions with molecular partners, shedding light on the relationship between protein structure and function.Progressing beyond the natural protein repertoire, the development of computational methods has enabled the design of novel proteins, primarily focusing on defined structural and biophysical properties. However, consistently introducing new functions into proteins has remained an ambitious challenge. Continuous refinement of computational design methods may prove key to solve emerging biomedical needs. One major challenge where functional protein design could have profound impact is the development of improved vaccines for pathogens that have resisted current vaccine development strategies. Among these pathogens are the influenza and hepatitis C virus (HCV) that cause severe morbidity and mortality across the population. In recent years, several broadly protective antibodies targeting conserved antigenic sites have been isolated and the structural characterization in complex with their cognate epitopes has revealed the structural aspects of these interactions. Computational design of tailor-made immunogens could be an effective tool in inducing a robust neutralizing antibody response against these key antigenic sites.To address these problems, my thesis work introduces a novel surface-centric computational design approach, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering. The surface-centric design approach presents a general framework to design proteins that mimic functional sites, including complex structural motifs characterized by irregular or discontinuous segments. Beyond the design of potent immunogens mimicking epitopes, the protocol allows computational screening for highly specific protein binders and together provide potentially new routes for the design of functional proteins through the optimization of surface features.Building upon the introduced design concepts, my work demonstrates for the first time the successful design of influenza epitope mimetics derived from heterologous protein scaffolds for a conserved, structurally complex antigenic site. The designed immunogens elicited subtype cross-reactive antibodies in vivo and a preliminary study suggests protection of mice from lethal viral infection. Additionally, engineered epitope-specific immunogens for HCV conferred significant cross-neutralization activity against a panel of different HCV genotypes displaying varying neutralization resistance. Diverging from traditional vaccine design approaches, these results provide a general roadmap to engineer novel immunogens eliciting a focused immune response for other pathogens. Overall, the work presented in this thesis introduces a versatile protein design approach for the development of sophisticated functional proteins and showcases the design of precision immunogens. The development of functional proteins could be transformative to solve biomedical questions including not only the design of novel immunogens but also protein components for synthetic biology or other protein-based biotechnologies.

EPFL2021