Publications associées à Advancing Drug Discovery via Artificial Intelligence

Cyclic Peptides for Drug Development

Christian Heinis, Xinjian Ji, Alexander Lund Nielsen

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

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

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

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

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

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

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

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

Effective Inhibition of TDP-43 Aggregation by Native State Stabilization

Hilal Lashuel, Lixin Yang, Yllza Jasiqi

Preventing the misfolding or aggregation of transactive response DNA binding protein with 43 kDa (TDP-43) is the most actively pursued disease-modifying strategy to treat amyotrophic lateral sclerosis and other neurodegenerative diseases. In this work, we ...

Wiley-VCH Verlag GmbH2024

Alchemical analysis of FDA approved drugs

Jean-Louis Reymond, Philippe Schwaller, Markus Orsi, 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

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

Gerardo Turcatti, Marc Chambon, Nicola Harris, 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

Generating macrocyclic inhibitors of protein-protein interactions

Gontran Sangouard

Protein-protein interactions (PPIs) play important roles in many diseases and their modulation is an attractive strategy for developing new therapeutics. However, the relatively large and often flat binding surfaces of PPIs makes the development of inhibit ...

EPFL2022

Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets

Ngoc Hien Du, Christoph Merten

Anti-cancer therapies often exhibit only short-term effects. Tumors typically develop drug resistance causing relapses that might be tackled with drug combinations. Identification of the right combination is challenging and would benefit from high-content, ...

Nature Research2022

NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism

Vassily Hatzimanikatis, Noushin Hadadi, Jasmin Maria Hafner, Anush Chiappino-Pepe, Homa Mohammadi Peyhani

The discovery of a drug requires over a decade of intensive research and financial investments – and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied ...

2021

High-content, targeted RNA-seq screening in organoids for drug discovery in colorectal cancer

Jörg Hülsken, Paloma Ordonez Moran, Maxim Norkin

Organoids allow the recapitulation of intestinal homeostasis and cancerogenesis in vitro; however, RNA sequencing (RNA-seq)-based methods for drug screens are missing. We develop targeted organoid sequencing (TORNADO-seq), a high-throughput, high-content d ...

2021

Alpha-Synuclein oligomerization and aggregation: All models are useful but only if we know what they model This is the reply to a comment "Alpha-synuclein oligomerization and aggregation: A model will always be a model" on the original article "Monitoring alpha-synuclein oligomerization and aggregation using bimolecular fluorescence complementation assays: What you see is not always what you get". The articles are accompanied by a Preface "How good are cellular models?"

Hilal Lashuel

Alpha-synuclein oligomerization is one of the early events on the pathway to Lewy body formation. Therefore, interfering with this process holds tremendous potential for developing therapies that block alpha-Syn pathology formation and toxicity. The develo ...

Wiley-Blackwell2021

Drug-to-Antibody Ratio Estimation via Proteoform Peak Integration in the Analysis of Antibody-Oligonucleotide Conjugates with Orbitrap Fourier Transform Mass Spectrometry

Yury Tsybin, Laure Menin, Anton Kozhinov, Natalia Gasilova, Konstantin Nagornov

The therapeutic efficacy and pharmacokinetics of antibody-drug conjugates (ADCs) in general, and antibody-oligonucleotide conjugates (AOCs) in particular, depend on the drug-to-antibody ratio (DAR) distribution and average value. The DAR is considered a cr ...

AMER CHEMICAL SOC2021

Towards the Development of Orally Available Peptide Therapeutics

Christian Heinis, Xudong Kong

Peptides have a number of attractive properties that make them an interesting modality for drug development, including their ability to bind challenging targets, their high target specificity, and their non-toxic metabolic products. However, a major limita ...

2021