cgDNA: a software package for the prediction of sequence-dependent coarse-grain free energies of B-form DNA

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Control-oriented modeling and analysis of tubular dielectric elastomer actuators dedicated to cardiac assist devices

Yves Perriard, Yoan René Cyrille Civet, Thomas Guillaume Martinez, Armando Matthieu Walter, Ning Liu

This paper deals with the control-oriented modeling of a multilayered dielectric elastomer actuator based tube. The actuator is clamped at both sides and performs a radial displacement. The hyperelastic deformation and the viscoelastic performance, togethe ...

2022

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

New methods for structure determination and speciation by NMR crystallography

Martins Balodis

NMR crystallography has been around for half a century, but with the advent of NMR crystal structure determination protocols in the last decade it has shown perspectives that were not seen before. Amalgamation of NMR and crystal structure determination has ...

EPFL2022

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

A complete description of thermodynamic stabilities of molecular crystals

Venkat Kapil, Edgar Albert Engel

Predictions of relative stabilities of (competing) molecular crystals are of great technological relevance, most notably for the pharmaceutical industry. However, they present a long-standing challenge for modeling, as often minuscule free energy differenc ...

National Academy of Sciences2022

Protein language models trained on multiple sequence alignments learn phylogenetic relationships

Anne-Florence Raphaëlle Bitbol, Damiano Sgarbossa, Umberto Lupo

Self-supervised neural language models with attention have recently been applied to biological sequence data, advancing structure, function and mutational effect prediction. Some protein language models, including MSA Transformer and AlphaFold's EvoFormer, ...

Nature Portfolio2022

Beyond potentials: Integrated machine learning models for materials

Michele Ceriotti

Over the past decade, interatomic potentials based on machine learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure calculations, they inherit ...

SPRINGER HEIDELBERG2022

Predicting hot-electron free energies from ground-state data

Michele Ceriotti, Federico Grasselli, Chiheb Ben Mahmoud

Machine-learning potentials are usually trained on the ground-state, Born-Oppenheimer energy surface, which depends exclusively on the atomic positions and not on the simulation temperature. This disregards the effect of thermally excited electrons, that i ...

AMER PHYSICAL SOC2022

A generic framework for hierarchical de novo protein design

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

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

cell2mol: encoding chemistry to interpret crystallographic data

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Sergio Vela Llausi, Yuri Cho

The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules ...

NATURE PORTFOLIO2022

Non-destructive Prediction of the Buckling Load of Cylindrical Shells

Emilio José Lozano Vazquez

The current research focuses on the prediction of the maximum axial compression load a cylindrical shell is able to bear. This maximum axial compression load is the value at which a cylindrical shell loses stability and abruptly buckles. After the buckling ...

EPFL2022

Electric metal contacts to monolayer blue phosphorus: electronic and chemical properties

Xiao Zhou

The contact nature when monolayer blue phosphorus (blueP) interfaces with three transition metal electrodes (i. e., Pd, Ir, and Pt) was unraveled by the ab initio density functional theory calculations. Specifically, n-type Schottky contact is observed for ...

ELSEVIER2022