Publications related to Duocarmycins binding to DNA explored by molecular simulation

Related publications (32)

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

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

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

Ursula Röthlisberger, Sophia Kathryn Johnson

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

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

Peptide-based virucidal drugs

Francesca Olgiati

Before the COVID-19 pandemic, viruses were not a major priority for the scientific community. Today, many events have changed the world and the importance of studying viruses, vaccines, and antiviral drugs is fully appreciated. The development of effective ...

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

MiMiC: A high-performance framework for multiscale molecular dynamics simulations

Ursula Röthlisberger, Sophia Kathryn Johnson, François Louis Mouvet, Andrea Levy, Andrej Antalik

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach ...

2024

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

Optimality principles for the analysis of biological processes across scales: From enzyme kinetics to microbiome dynamics

Asli Sahin

Microorganisms are essential for life on Earth, performing key roles in numerous biological processes. Their influence extends across a wide spectrum, from human health and ecological balance to advancements in biotechnology and industrial applications. Th ...

EPFL2024

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Sauradeep Majumdar

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

Chalcogen bonding catalysis

Jieping Zhu

Catalysts play a major role in chemical synthesis, and catalysis is considered to be a green and economic process. Catalysis is dominated by covalent interactions between the catalyst and substrate. The design of non-covalent catalysts came into limelight ...

Royal Society of Chemistry2024

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

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

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites

Paul Joseph Dyson, Farzaneh Fadaei Tirani, Mouna Hadiji

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Amer Chemical Soc2024

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

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

Ursula Röthlisberger, Martin Peter Bircher, Justin Villard

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

Exciton migration in two-dimensional materials

Giovanni Consalvo Cistaro

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

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

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