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

Publications associées (39)

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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 ...

WILEY2022

Scaffolding protein functional sites using deep learning

Bruno Emanuel Ferreira De Sousa Correia, Karla Montserrat Castro Gilabert, Basile Isidore Martin Wicky, Jue Wang

The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing ...

AMER ASSOC ADVANCEMENT SCIENCE2022

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 partn ...

EPFL2021

Direct-coupling analysis (DCA) for studying the coevolution of residues in proteins has been widely used to predict the three-dimensional structure of a protein from its sequence. We present RADI/raDIMod, a variation of the original DCA algorithm that grou ...

OXFORD UNIV PRESS2021

BackgroundStatistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein-protein interaction (PPI) structures. In previous works we deco ...

BMC2021

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

IEEE COMPUTER SOC2021

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Bruno Emanuel Ferreira De Sousa Correia, Jaume Bonet Martinez

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improv ...

AMER CHEMICAL SOC2021

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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 ...

2020

rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics

Bruno Emanuel Ferreira De Sousa Correia, Zander Harteveld, Andreas Scheck, Jaume Bonet Martinez, Fabian Sesterhenn

BackgroundLarge-scale datasets of protein structures and sequences are becoming ubiquitous in many domains of biological research. Experimental approaches and computational modelling methods are generating biological data at an unprecedented rate. The deta ...

2019

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Pablo Gainza Cirauqui, Freyr Sverrisson

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features that fin ...

2019