Publications associées à Structure des protéines

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

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

Ksenia Briling, Puck Elisabeth van Gerwen, Yannick Calvino Alonso, Malte Martin Franke

In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based ...

Royal Soc Chemistry2024

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Alireza Karimi, Elias Sebastian Klauser

A novel approach for linear parameter-varying (LPV) controller synthesis for adaptive rejection of time-varying sinusoidal disturbances is proposed. Only the frequency response data of a linear time-invariant (LTI) multiple-input multiple-output (MIMO) sys ...

2024

Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection

Nako Nakatsuka, Xinyu Zhang, Haiying Hu

Single-molecule proteomics based on nanopore technology has made significant advances in recent years. However, to achieve nanopore sensing with single amino acid resolution, several bottlenecks must be tackled: controlling nanopore sizes with nanoscale pr ...

2024

Fast viral dynamics revealed by microsecond time-resolved cryo-EM

Marcel Drabbels, Ulrich Lorenz, Sarah Victoria Barrass, Oliver Florian Harder

Observing proteins as they perform their tasks has largely remained elusive, which has left our understanding of protein function fundamentally incom- plete. To enable such observations, we have recently proposed a technique that improves the time resoluti ...

2023

Indication of 310-Helix Structure in Gas-Phase Neutral Pentaalanine

Vasyl Yatsyna

We investigate the gas-phase structure of the neutral pentaalanine peptide. The IR spectrum in the 340-1820 cm-1 frequency range is obtained by employing supersonic jet cooling, infrared multiphoton dissociation, and vacuum-ultraviolet action spectroscopy. ...

AMER CHEMICAL SOC2023

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

Anne-Florence Raphaëlle Bitbol, Umberto Lupo, Damiano Sgarbossa

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

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

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

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

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 ...

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

Structure des protéines

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

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

Graph Chatbot

Chattez avec Graph Search

Opportunities and challenges in design and optimization of protein function

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection

Fast viral dynamics revealed by microsecond time-resolved cryo-EM

Indication of 310-Helix Structure in Gas-Phase Neutral Pentaalanine

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

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

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

A new age in protein design empowered by deep learning

Opportunities and challenges in design and optimization of protein function

Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

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

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

Fast viral dynamics revealed by microsecond time-resolved cryo-EM

A new age in protein design empowered by deep learning

Indication of 310-Helix Structure in Gas-Phase Neutral Pentaalanine