Publications associées à On the active site of mononuclear B1 metallo beta-lactamases: a computational study

Publications associées (41)

CementFF4: Formal atomic charge polarizable force field for cementitious systems – Bulk and surface

Tecla Bottinelli Montandon, Karen Scrivener, Paul Bowen, Manuel Cordova, Ziga Casar

A general-purpose formal charge polarizable force field for cementitious systems, CementFF4, is presented. The force field includes the following species: Ca, Si, O, H, Al, Zn, OH− and H2O. The force field is a significant extension of previous force field ...

Pergamon-Elsevier Science Ltd2025

Unraveling metal effects on CO2 uptake in pyrene-based metal-organic frameworks

Berend Smit, Emad Oveisi, Wendy Lee Queen, Pascal Alexander Schouwink, Christopher Patrick Ireland, Andres Adolfo Ortega Guerrero, Elias Moubarak, Jordi Espin Marti, Fatma Pelin Uran, Nency Patricio Domingues, Miriam Jasmin Pougin, Yutao Li

Pyrene-based metal-organic frameworks (MOFs) have tremendous potential for various applications. With infinite structural possibilities, the MOF community often relies on simulations to identify the most promising candidates for given applications. Among t ...

NATURE PORTFOLIO2025

Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery

Patrick Daniel Barth

G protein-coupled receptors (GPCRs) are the largest human membrane protein family that transduce extracellular signals into cellular responses. They are major pharmacological targets, with approximately 26% of marketed drugs targeting GPCRs, primarily at t ...

2025

Distribution and diversity of classical deacylases in bacteria

Carlos Moreno Yruela

Classical Zn2+-dependent deac(et)ylases play fundamental regulatory roles in life and are well characterized in eukaryotes regarding their structures, substrates and physiological roles. In bacteria, however, classical deacylases are less well understood. ...

Nature Portfolio2024

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

Well-Defined Ti Surface Sites in Ziegler-Natta Pre-Catalysts from 47/49Ti Solid-State Nuclear Magnetic Resonance Spectroscopy

Pierrick Berruyer

Treatment of Ziegler-Natta (ZN) catalysts with BCl3 improves their activity by increasing the number of active sites. Here we show how Ti-47/49 solid-state nuclear magnetic resonance (NMR) spectroscopy enables us to understand the electronic structure of t ...

Amer Chemical Soc2024

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli, Paolo Pegolo

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Frontiers Media Sa2024

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

Probing Catalytic Sites and Adsorbate Spillover on Ultrathin FeO2-x Film on Ir(111) during CO Oxidation

Harald Brune, Hao Yin

The spatially resolved identification of active sites on the heterogeneous catalyst surface is an essential step toward directly visualizing a catalytic reaction with atomic scale. To date, ferrous centers on platinum group metals have shown promising pote ...

Amer Chemical Soc2024

The rule of four: anomalous distributions in the stoichiometries of inorganic compounds

Nicola Marzari, Marnik Bercx, Carl Simon Adorf, Elena Gazzarrini

Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle, given the vastness of compositional and configurational space. We highlight he ...

Nature Portfolio2024

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

Balancing computational chemistry's potential with its environmental impact

Philippe Schwaller, Oliver Tobias Schilter

Computational chemistry techniques offer tremendous potential for accelerating the discovery of sustainable chemical processes and reactions. However, the environmental impacts of the substantial computing power required for these digital methods are often ...

ROYAL SOC CHEMISTRY2024

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

Rapid Mining of Fast Ion Conductors via Subgraph Isomorphism Matching

Mouyi Weng

The rapidly evolving field of inorganic solid-state electrolytes (ISSEs) has been driven in recent years by advances in data-mining techniques, which facilitates the high-throughput computational screening for candidate materials in the databases. The key ...

AMER CHEMICAL SOC2024

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

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

Federico De Biasi

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

Large-cage occupation and quantum dynamics of hydrogen molecules in sII clathrate hydrates

Richard Gaal, Livia Eleonora Bove Kado, Umbertoluca Ranieri

Hydrogen clathrate hydrates are ice-like crystalline substances in which hydrogen molecules are trapped inside polyhedral cages formed by the water molecules. Small cages can host only a single H-2 molecule, while each large cage can be occupied by up to f ...

Aip Publishing2024

Surface segregation in high-entropy alloys from alchemical machine learning

Michele Ceriotti, Sandip De, Guillaume André Jean Fraux, Arslan Mazitov, Nataliya Lopanitsyna

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

Iop Publishing Ltd2024

Live-cell imaging powered by computation

Suliana Manley

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Nature Portfolio2024

The Electronic-Structure Genome of Inorganic Crystals

Junfeng Qiao

Electronic structure theory plays a central role in understanding properties of crystalline materials. Among all the ab initio methods, density functional theory (DFT) is the most popular choice due to its balance between accuracy and computational cost, a ...

EPFL2024