Publications associées à An Automatic, Data-Driven Definition of Atomic-Scale Structural Motifs

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

Post-translational modifications (PTMs) play a pivotal role in regulating protein structure, interaction, and function. Aberrant PTM patterns are associated with diseases. Moreover, individual PTMs have a complex interaction with each other, known as PTM c ...

EPFL2024

Predicting protein interactions using geometric deep learning on protein surfaces

Freyr Sverrisson

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

EPFL2024

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero, Mohan Vamsi Nallapareddy

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

PMLR2024

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Ursula Röthlisberger, Justin Villard, Martin Peter Bircher

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, wit ...

Royal Soc Chemistry2024

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

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Mahdi Hijazi

The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

EPFL2024

Microsecond Time-Resolved Cryo-Electron Microscopy

Oliver Florian Harder

Recently, single-particle cryo-electron microscopy emerged as a technique capable of determining protein structures at near-atomic resolution and resolving protein dynamics with a temporal resolution ranging from second to milliseconds. This thesis describ ...

EPFL2024

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Anthony Marchand

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

EPFL2024

Prolamins' 3D structure: A new insight into protein modeling using the language of numbers and shapes

Niloufar Sharif

This study combined protein modeling methods to generate the prolamins' fractions as precise as possible. Hence, gliadins, zeins, kafirins, hordeins, secalins, avenins and oryzins were generated based on their characteristics and disulfide mapping. Finding ...

Elsevier Sci Ltd2024

Computational drug development for membrane protein targets

Pierre Vogel, Henning Paul-Julius Stahlberg, Dongchun Ni, Babatunde Edukpe Ekundayo, Shuguang Yuan

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

2024