Structural heterogeneity of the ion and lipid channel TMEM16F

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A new age in protein design empowered by deep learning

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

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 ...

Cell Press2023

Computational design of dynamic receptor—peptide signaling complexes applied to chemotaxis

Andreas Füglistaler, Aurélien Laurent Jean-Charles Oggier, Mahdi Hijazi, Patrick Daniel Barth, Robert Everett Jefferson, Ana Paola Rico Villarreal

Engineering protein biosensors that sensitively respond to specific biomolecules by triggering precise cellular responses is a major goal of diagnostics and synthetic cell biology. Previous biosensor designs have largely relied on binding structurally well ...

Nature Research2023

Extracting transport channel transmissions in scanning tunneling microscopy using superconducting excess current

Klaus Kern, Markus Etzkorn, Jacob Senkpiel

Transport through quantum coherent conductors, such as atomic junctions, is described by conduction channels. Information about the number of channels and their transmissions can be extracted from various sources, such as multiple Andreev reflections, dyna ...

AMER PHYSICAL SOC2022

Water as a contrast agent for imaging interfacial structure and ion transport in giant vesicles

David Roesel

Hydrated lipid bilayer membranes and their asymmetry play a fundamental role in living cells by maintaining and regulating concentration gradients between cells, their environment, and their compartments. They achieve this not only through various channels ...

EPFL2022

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

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

High-Throughput Nanopore Fabrication and Classification Using Xe-Ion Irradiation and Automated Pore-Edge Analysis

Andras Kis, Aleksandra Radenovic, Martina Lihter, Michal Daniel Macha, Sanjin Marion, Mukeshchand Thakur, Mukesh Kumar Tripathi

Large-area nanopore drilling is a major bottleneck in state-of-the-art nanoporous 2D membrane fabrication protocols. In addition, high-quality structural and statistical descriptions of as-fabricated porous membranes are key to predicting the corresponding ...

AMER CHEMICAL SOC2022

Computationally designed GPCR quaternary structures bias signaling pathway activation

Patrick Daniel Barth, Robert Everett Jefferson

Communication across membranes controls critical cellular processes and is achieved by receptors translating extracellular signals into selective cytoplasmic responses. While receptor tertiary structures can be readily characterized, receptor associations ...

Nature Research2022

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

Nicola Dietler, Anne-Florence Raphaëlle Bitbol, 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 ...

Public Library Science2022

Second harmonic scattering of water in a biological context

Tereza Schönfeldová

Water is one of the most abundant molecules in the universe. It forms a hydrogen bond network with unique structure and dynamics. Hydrogen bonding is highly relevant to many biological processes including membrane formation, protein folding, adsorption, an ...

EPFL2022

Mass transport of water vapor and ions from Å-scale graphene nanopores

Wan-Chi Lee

Hydrodynamics at the nanoscale involves both fundamental study and application of fluid and mass transport phenomena in nanometer-sized confinements. Nanopores in single-layer graphene can be highly attractive for exploring the molecular transport of gas a ...

EPFL2022

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