Publications associées à Conception de médicament

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

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

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

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

Improved microfluidic transcriptome based screening methods

Christoph Merten, Xiaoli Ma, Leonie Kolmar, 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

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

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

Augmenting large language models with chemistry tools

Philippe Schwaller, Oliver Tobias Schilter, Andres Camilo Marulanda Bran, Carlo Baldassari

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Nature Portfolio2024

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

Drug Screening in C. elegans to identify new pharmacological mitochondrial stress inducers

Amélia Lalou

Mitochondria are essential organelles participating in numerous cellular functions, including energy harvesting, regulation of homeostasis and apoptosis. Changes in mitochondrial number, morphology, and function not only impact cellular metabolism but also ...

EPFL2024

Antibody-peptide conjugates for targeted inhibition of cysteine proteases

Elisa Oricchio

We developed a rational approach to design peptide-based covalent inhibitors and coupled the inhibitors with antibodies for cell-specific delivery. We used this platform to generate antibody-peptide inhibitor conjugates (APICs) that target a family of prot ...

Nature Portfolio2024

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

Methods for high-throughput synthesis and screening of peptide libraries

Zsolt Bognár

Macrocycles provide an attractive modality for drug development but the identification of ligands to targets of interest is hindered by the lack of large macrocyclic compound libraries for high-throughput screening. A strategy to efficiently synthesize lar ...

EPFL2024

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

Photogeneration of Hydrogen: Insights from a Pt(II)-Complex Incorporated into a Covalent Organic Framework

Federico De Biasi, Paolo Costa

Pt(II)-based molecular catalysts stand as a prototypical system in hydrogen evolution reactions (HER) owing to their consistently elevated activity levels. Their integration into heterogeneous systems thus provides an ideal platform to develop catalytic ma ...

Wiley-VCH Verlag2024

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

Solid-phase peptide synthesis in 384-well plates

Christian Heinis, Anne Sofie Luise Zarda, Alexander Lund Nielsen, Sevan Mleh Habeshian, Gontran Sangouard, Mischa Schüttel, Edward Jeffrey Will

Newer solid-phase peptide synthesis and release strategies enable the production of short peptides with high purity, allowing direct screening for desired bioactivity without prior chromatographic purification. However, the maximum number of peptides that ...

2024

Artificial intelligence for natural product drug discovery

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

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

Asymmetric Construction of α,α‐Disubstituted Piperazinones Enabled by Benzilic Amide Rearrangement

Jieping Zhu, Hua Wu, Yuping He

An unprecedent asymmetric catalytic benzilic amide rearrangement for the synthesis of α,α-disubstituted piperazinones is reported. The reaction proceeds via a domino [4+1] imidazolidination/formal 1,2-nitro- gen shift/1,2-aryl or alkyl migration sequence, ...

Wiley-VCH Verlag GmbH2023

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