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Concept

Rosetta (bioinformatics)

Related publications (15)

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao, Kaouther Messaoud Ben Amor

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

2024

Climbing into their Skin to Understand Contextual Protein-Protein Associations and Localizations: Functional Investigations in Transgenic Live Model Organisms

Yimon Aye

Borrowing some quotes from Harper Lee's novel "To Kill A Mockingbird" to help frame our manuscript, we discuss methods to profile local proteomes. We initially focus on chemical biology regimens that function in live organisms and use reactive biotin speci ...

Wiley-V C H Verlag Gmbh2024

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

Bruno Lemaitre, Luciano Andres Abriata, Samuel Rommelaere

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

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics

Bruno Emanuel Ferreira De Sousa Correia, Li Tang, Pablo Gainza Cirauqui, Sandrine Madeleine Suzanne Georgeon, Stéphane Rosset, Leo Scheller, Anthony Marchand, Sailan Shui, Lucia Bonati

Protein-based therapeutics, such as monoclonal antibodies and cytokines, are important therapies for various pathophysiological conditions such as oncology, autoimmune disorders, and viral infections. However, the wide application of such protein therapeut ...

2023

Machine-learned interatomic potentials: Recent developments and prospective applications

William Curtin

High-throughput generation of large and consistent ab initio data combined with advanced machine-learning techniques are enabling the creation of interatomic potentials of near ab initio quality. This capability has the potential of dramatically impacting ...

Springer Heidelberg2023

De novo protein design by inversion of the AlphaFold structure prediction network

Bruno Emanuel Ferreira De Sousa Correia, Stéphane Rosset, Casper Alexander Goverde, Hamed Khakzad, Benedict Dieter Gregor Wolf

De novo protein design enhances our understanding of the principles that govern protein folding and interactions, and has the potential to revolutionize biotechnology through the engineering of novel protein functionalities. Despite recent progress in comp ...

2023

On the durability of surgical masks after simulated handling and wear

Jian Wang, Véronique Michaud, Baris Çaglar, Vincent Marc Varanges, Yann Albert Gérard Lebaupin

After the spread of COVID-19, surgical masks became highly recommended to the public. They tend to be handled and used multiple times, which may impact their performance. To evaluate this risk, surgical masks of Type IIR were submitted to four simulated tr ...

Nature Research2022

De Novo Crystal Structure Determination from Machine Learned Chemical Shifts

David Lyndon Emsley, Manuel Cordova, Albert Hofstetter, Martins Balodis

Determination of the three-dimensional atomic-level structure of powdered solids is one of the key goals in current chemistry. Solid-state NMR chemical shifts can be used to solve this problem, but they are limited by the high computational cost associated ...

2022

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

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Bruno Emanuel Ferreira De Sousa Correia, Jaume Bonet Martinez

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improv ...

AMER CHEMICAL SOC2021

A Rosetta-based protein design protocol converging to natural sequences

Bruno Emanuel Ferreira De Sousa Correia, Stéphane Rosset, Zander Harteveld

Computational protein design has emerged as a powerful tool capable of identifying sequences compatible with pre-defined protein structures. The sequence design protocols, implemented in the Rosetta suite, have become widely used in the protein engineering ...

AMER INST PHYSICS2021

Constrained optimization applied to multiscale integrative modeling

Giorgio Elikem Tamo

Multiscale integrative modeling stands at the intersection between experimental and computational techniques to predict the atomistic structures of important macromolecules. In the integrative modeling process, the experimental information is often integra ...

EPFL2018

Anharmonic and Quantum Fluctuations in Molecular Crystals: A First-Principles Study of the Stability of Paracetamol

Michele Ceriotti, Mariana Rossi Carvalho, Piero Gasparotto

Molecular crystals often exist in multiple competing polymorphs, showing significantly different physicochemical properties. Computational crystal structure prediction is key to interpret and guide the search for the most stable or useful form, a real chal ...

2016

On the role of water density fluctuations in the inhibition of a proton channel

Lucie Monique Françoise Delemotte

Hv1 is a transmembrane four-helix bundle that transports protons in a voltage-controlled manner. Its crucial role in many pathological conditions, including cancer and ischemic brain damage, makes Hv1 a promising drug target. Starting from the recently sol ...

National Academy of Sciences2016

In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene

Vassily Hatzimanikatis

Background: Bioremediation offers a promising pollution treatment method in the reduction and elimination of man-made compounds in the environment. Computational tools to predict novel biodegradation pathways for pollutants allow one to explore the capabil ...

BioMed Central2010