Publications associées à Engineering growth factors for regenerative medicine applications

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

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

Antibodies expand the scope of angiotensin receptor pharmacology

Patrick Daniel Barth, Shuhao Zhang

G-protein-coupled receptors (GPCRs) are key regulators of human physiology and are the targets of many small-molecule research compounds and therapeutic drugs. While most of these ligands bind to their target GPCR with high affinity, selectivity is often l ...

2024

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Clinically compliant cryopreservation of differentiated retinal pigment epithelial cells

Cheng Zhao, Gioele La Manno, Alex Russell Lederer

Background aims: Age-related macular degeneration (AMD) is the most common cause of blindness in elderly patients within developed countries, affecting more than 190 million worldwide. In AMD, the retinal pigment epithelial (RPE) cell layer progressively d ...

Elsevier Sci Ltd2024

Computational drug development for membrane protein targets

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

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

The role of computational methods in cardiovascular medicine: a narrative review

Alfio Quarteroni, Luca Dede', Christian Vergara, Stefano Pagani

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Ame Publishing Company2024

A First-in-Human Randomized Study to Assess the Safety, Tolerability, Pharmacokinetics, and Neutralization Profile of Two Investigational Long-Acting Anti-SARS-CoV-2 Monoclonal Antibodies

Didier Trono, Norman Lionel Moullan

Introduction: COVID-19 remains a significant risk for the immunocompromised given their lower responsiveness to vaccination or infection. Therefore, passive immunity through long-acting monoclonal antibodies (mAbs) offers a needed approach for pre-exposure ...

2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Development of cysteine cathepsin inhibitors combined with cell type-specific delivery for the treatment of B-cell lymphoma and solid tumors

Aaron Simone Petruzzella

Cysteine cathepsins proteases are enzymes that play essential physiological roles, but their activity is also associated to different aspects of cancer progression and to the development of other diseases. Therefore, cysteine cathepsins are relevant and pr ...

EPFL2024

Characterization of the gut-bone marrow axis through bile acid signaling

Alejandro Alonso Calleja

Communication between the intestine and other organs such as the lungs, brain or bones is mediated by several metabolites, like short-chain fatty acids or bile acids, that relay information about nutritional and microbiota status. Bile acids are endogenous ...

EPFL2024

Proliferation-driven mechanical compression induces signalling centre formation during mammalian organ development

Pengfei Xu, Sangwoo Kim

Localized sources of morphogens, called signalling centres, play a fundamental role in coordinating tissue growth and cell fate specification during organogenesis. However, how these signalling centres are established in tissues during embryonic developmen ...

Nature Portfolio2024

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

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

Metabolically enhanced CAR T cells efficiently clear solid tumors in mice

Li Tang

Chimeric antigen receptor (CAR) T cells in the solid tumor microenvironment enter a partially dysfunctional state called T cell exhaustion. Interleukin (IL)-10-producing CAR T cells retain their metabolic fitness, resist T cell exhaustion and display unpre ...

Nature Portfolio2024

Oxidative Defect Detection Within Free and Packed DNA Systems: A Quantum Mechanical/Molecular Mechanics (QM/ MM) Approach

Ursula Röthlisberger

Base excision repair enzymes (BERs) detect and repair oxidative DNA damage with efficacy despite the small size of the defects and their often only minor structural impact. A charge transfer (CT) model for rapid scanning of DNA stretches has been evoked to ...

Swiss Chemical Soc2024

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

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

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

Exciton migration in two-dimensional materials

Excitons play an essential role in the optical response of two-dimensional materials. These are bound states showing up in the band gaps of many-body systems and are conceived as quasiparticles formed by an electron and a hole. By performing real-time simu ...

Nature Portfolio2024

Unlocking Hidden Potential: Exploring the Complexities of Signaling in Immune Cell Activation to Optimize CAR Therapy

Mathieu Girardin

Chimeric antigen receptors (CARs) are synthetic, transmembrane proteins that trigger immune cell signaling following their engagement. They have been first utilized in T cells and later in natural killer (NK) cells to redirect their cytotoxicity toward a s ...

EPFL2023