Concept

Protein–protein interaction prediction

Related publications (171)

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

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

Michael Bronstein, Pablo Gainza Cirauqui, Zander Harteveld, Andreas Scheck, Anthony Marchand, Sarah Wehrle, Freyr Sverrisson, Alexandra Krina Van Hall-Beauvais

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 ...

2023

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

Impact of phylogeny on structural contact inference from protein sequence data

Anne-Florence Raphaëlle Bitbol, Nicola Dietler, Umberto Lupo

Local and global inference methods have been developed to infer structural contacts from multiple sequence alignments of homologous proteins. They rely on correlations in amino acid usage at contacting sites. Because homologous proteins share a common ance ...

ROYAL SOC2023

OccuVAE: Integrating unsupervised occupancy inference in data-driven energy modeling for human-centric operation

Andrew James Sonta, Yufei Zhang

Data-driven building energy modeling is an emerging solution to facilitate the implementation of energy-flexible buildings. However, its black-box nature hinders interpretation, including with respect to human-building interaction. This drawback may bring ...

Association for Computing Machinery2023

Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules

Stefano Zamuner

Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference ...

PUBLIC LIBRARY SCIENCE2022

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

Patrick Daniel Barth, Mahdi Hijazi

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 ...

2022

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Anne-Florence Raphaëlle Bitbol, Nicola Dietler, Andonis Samuel Rene Gerardos

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families ...

San Francisco2022

Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

Anne-Florence Raphaëlle Bitbol

Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's ph ...

NATURE PORTFOLIO2022

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

Zander Harteveld

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 ...

EPFL2022

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