Publications associées à Automated design of ligands to polypharmacological profiles

Publications associées (30)

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

Improved microfluidic transcriptome based screening methods

Christoph Merten, Leonie Kolmar, Xiaoli Ma, Hongxing Hu

The invention provides microfluidic screening systems for the identification of compounds or compositions influencing cellular transcriptomes. The invention is predicated upon taking into account differences in newly synthesized mRNA in contrast to so call ...

2024

Cyclic Peptides for Drug Development

Christian Heinis, Alexander Lund Nielsen, Xinjian Ji

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years ...

Wiley-VCH Verlag GmbH2024

Antibodies expand the scope of angiotensin receptor pharmacology

Shuhao Zhang, Patrick Daniel Barth

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

Computational drug development for membrane protein targets

Pierre Vogel, Henning Paul-Julius Stahlberg, 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

Deconvolution of ex-vivo drug screening data and bulk tissue expression predicts the abundance and viability of cancer cell subpopulations

Alexandre Coudray

Ex-vivo drug sensitivity screening (DSS) allows the prediction of cancer treatment effectiveness in a personalized fashion. However, it only provides a readout on mixtures of cells, potentially occulting important information on clinically relevant cell su ...

EPFL2023

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

Optimised three-dimensional in vitro retinoblastoma models tailored for drug discovery and clinical translatability

Irina Sinenko

Retinoblastoma, while relatively rare, stands as the most prevalent intraocular cancer. In Switzerland, the survival rate approaches 100%, but it drops to less than 50% in low-income countries. The current treatment options for retinoblastoma rely on a lim ...

EPFL2023

The predictive capacity of in vitro preclinical models to evaluate drugs for the treatment of retinoblastoma

Paul Joseph Dyson, Irina Sinenko, Roland Christopher Turnell-Ritson

Retinoblastoma is a rare childhood cancer of the eye. Of the small number of drugs are used to treat retinoblastoma, all have been repurposed from drugs developed for other conditions. In order to find drugs or drug combinations better suited to the improv ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2023

Artificial intelligence for natural product drug discovery

Philippe Schwaller, Albert Hofstetter, Michael Alexander Skinnider, Florian Huber

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to e ...

Nature Portfolio2023

A multi-reservoir extruder for time-resolved serial protein crystallography and compound screening at X-ray free-electron lasers

Christoph Bostedt, Camila Bacellar Cases Da Silveira

Serial crystallography at X-ray free-electron lasers (XFELs) permits the determination of radiation-damage free static as well as time-resolved protein structures at room temperature. Efficient sample delivery is a key factor for such experiments. Here, we ...

Nature Portfolio2023

Modeling tumor size dynamics based on real-world electronic health records and image data in advanced melanoma patients receiving immunotherapy

Federico Amato

The development of immune checkpoint inhibitors (ICIs) has revolutionized cancer therapy but only a fraction of patients benefits from this therapy. Model-informed drug development can be used to assess prognostic and predictive clinical factors or biomark ...

2023

Alchemical analysis of FDA approved drugs

Philippe Schwaller, Daniel Probst

Chemical space maps help visualize similarities within molecular sets. However, there are many different molecular similarity measures resulting in a confusing number of possible comparisons. To overcome this limitation, we exploit the fact that tools desi ...

2023

Translational screening platform to evaluate chemotherapy in combination with focal therapy for retinoblastoma

Paul Joseph Dyson, Valentin Simeonov, Fabien Kuttler, Patrik Aouad, Irina Sinenko

Retinoblastoma is the most common pediatric eye cancer. It is currently treated with a limited number of drugs, adapted from other pediatric cancer treatments. Drug toxicity and relapse of the disease warrant new therapeutic strategies for these young pati ...

WILEY2023

Hierarchy of the Components in Spray-Dried, Protein-Excipient Particles Using DNP-Enhanced NMR Spectroscopy

David Lyndon Emsley, Pierrick Berruyer, Andrea Bertarello, Baptiste Busi

Protein-based drugs are becoming increasingly important, but there are challenges associated with their formulation (for example, formulating stable inhalable aerosols while maintaining the proper long-term stability of the protein). Determining the morpho ...

Amer Chemical Soc2023

Elucidating and modulating regulatory pathways so as to reprogram the immunosuppressive tumor microenvironment for therapeutic benefit

Agnieszka Alicja Chryplewicz

Glioblastoma (GBM) is the most frequent and highly malignant form of brain cancer. New therapeutic regimens are urgently needed as GBM patients present with a minimal response to currently-approved therapies. The goal of this project is to identify new the ...

EPFL2023

Repurposed drug combination via high-throughput screening and dual drug delivery system development for the treatment of retinoblastoma

Po-Jen Tseng

The goal of retinoblastoma (RB) treatment is to save the child's life, eyes and functional vision, with that order of priority. The management of RB is complex and involves strategically chosen methods of surgical enucleation, external beam radiotherapy, i ...

EPFL2022

Novel High-Throughput Fluorescence-Based Assay for the Identification of Nematocidal Compounds That Target the Blood-Feeding Pathway

Nicola Harris, Gerardo Turcatti, Marc Chambon, Anthony Marchand, Tiffany Babette Angélique Bouchery, Mati André Marie Moyat

Hookworm infections cause a neglected tropical disease (NTD) affecting ~740 million people worldwide, principally those living in disadvantaged communities. Infections can cause high morbidity due to their impact on nutrient uptake and their need to feed o ...

2022

In-Cell Quantification of Drugs by Magic-Angle Spinning Dynamic Nuclear Polarization NMR

David Lyndon Emsley, Pierrick Berruyer, Andrea Bertarello

The determination of intracellular drug concentrations can provide a better understanding of the drug function and efficacy. Ideally, this should be performed nondestructively, with no modification of either the drug or the target, and with the capability ...

AMER CHEMICAL SOC2022

Rational design of protein switches: applications in synthetic biology and cancer immunotherapy

Sailan Shui

Synthetic biology aims to engineer cells as miniature biological devices to sense, process, and respond to exogenous stimuli. Protein switches are designed to sense and respond to various molecular queues in a fast and specific manner, which fits the requi ...

EPFL2022