Enhanced Sampling Molecular Dynamics Identifies PrPSc Structures Harboring a C-Terminal beta-Core

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (30)

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins

Anne-Florence Raphaëlle Bitbol

Author summaryWhen two protein families interact, their sequences feature statistical dependencies. First, interacting proteins tend to share a common evolutionary history. Second, maintaining structure and interactions through the course of evolution yiel ...

PUBLIC LIBRARY SCIENCE2023

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining

Qiang Liu, Feng Yu, Yichen Xu

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

Assoc Computing Machinery2023

De novo design of protein interactions with learned surface fingerprints

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

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

Trans‐seeding of Alzheimer‐related tau protein by a yeast prion

Henning Paul-Julius Stahlberg, Zhiva Skachokova

Abnormal tau protein aggregates constitute a hallmark of Alzheimer's disease. The mechanisms underlying the initiation of tau aggregation in sporadic neurodegeneration remain unclear. Here we investigate whether a non-human prion can seed tau aggregation. ...

2022

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

Mahdi Hijazi, Patrick Daniel Barth, Lucas Sebastian Powell-Rudden

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

Validation of spectral simulation tools in the context of ipRGC-influenced light responses of building occupants

Marilyne Andersen, Clotilde Marie A Pierson

With the growing awareness about ipRGC-influenced light (IIL) responses, design applications related to these responses are flourishing. To compare design options and optimize lighting conditions for building occupants, lighting simulations are typically u ...

2023

A generic framework for hierarchical de novo protein design

Bruno Emanuel Ferreira De Sousa Correia, Zander Harteveld, Jaume Bonet Martinez, Fabian Sesterhenn, Che Yang, Stéphane Rosset

De novo protein design enables the exploration of novel sequences and structures absent from the natural protein universe. De novo design also stands as a stringent test for our understanding of the underlying physical principles of protein folding and may ...

National Academy of Sciences2022

Scaffolding protein functional sites using deep learning

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

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 ...

American Association for the Advancement of Science2022

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

Page 2 sur 2