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

Related publications (155)

Opportunities and challenges in design and optimization of protein function

Bruno Emanuel Ferreira De Sousa Correia, Casper Alexander Goverde

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 ...

Nature Portfolio2024

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 the ...

EPFL2024

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero, Mohan Vamsi Nallapareddy

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome dwell times ...

2024

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

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

Anne-Florence Raphaëlle Bitbol, Damiano Sgarbossa, Umberto Lupo

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 ...

eLIFE SCIENCES PUBL LTD2023

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Hamed Khakzad, Casper Alexander Goverde, Arne Schneuing, Ilia Igashov

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 ...

Cambridge2023

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

Bruno Emanuel Ferreira De Sousa Correia, Hamed Khakzad, Casper Alexander Goverde, Stéphane Rosset, Benedict Dieter Gregor Wolf

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 ...

2023

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

Ghérici Hassaïne

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 ...

NATURE PORTFOLIO2023

Protein target highlights in CASP15: Analysis of models by structure providers

Bruno Lemaitre, Luciano Andres Abriata, Samuel Rommelaere, Kuan-Lin Wu, Han Xiao

We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the su ...

WILEY2023

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, Michael Bronstein, Pablo Gainza Cirauqui, Zander Harteveld, Andreas Scheck, Charlène Mireille Raymonde Raclot, Anthony Marchand, Alexandra Teslenko, Casper Alexander Goverde, Aaron Simone Petruzzella, Stephen Michael Buckley, Martin Pacesa, Stéphane Rosset, Sarah Wehrle, Freyr Sverrisson, Alexandra Krina Van Hall-Beauvais, Jane Marsden

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

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