Computational Studies for the Design of Metalloenzyme Mimics

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Machine learning for protein modeling faces significant challenges due to proteins' inherently dynamic nature, yet most graph-based machine learning methods rely solely on static structural information. Recently, the growing availability of molecular dynam ...

Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. For example, clathrin coats adopt a wide variety of architectures to adapt to vesicular cargos of various sizes. Although computational me ...

Protein catalysis and allostery require the atomic-level orchestration and motion of residues and ligand, solvent and protein effector molecules. However, the ability to design protein activity through precise protein–solvent cooperative interactions has n ...

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 ...

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 ...

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 ...

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 ...

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

Artificial photosynthesis is considered to be a promising approach for energy storage and global warming mitigation. However, the suboptimal selectivity of products and the low conversion efficiency of CO2 persist as challenges, driving continuous interest ...

The sensitivity of enteroviruses to disinfectants varies among genetically similar variants and coincides with amino acid changes in capsid proteins, although the effect of individual substitutions remains unknown. Here, we employed reverse genetics to inv ...

The constant urge to construct new molecules in an economical and sustainable fashion led to the development of numerous metal-catalyzed transformations. Organocatalysts consisting of abundant and more sustainable elements offer an elegant solution to over ...

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements freq ...

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 ...

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

Iron-exchanged zeolites are industrial heterogeneous catalysts deployed to remediate anthropogenic emissions of both nitrous oxide (N2O) and nitrogen oxides (NOx = NO + NO2). Despite the extensive scientific attention received, limited knowledge is availab ...

Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, ...

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 ...

Computational Studies for the Design of Metalloenzyme Mimics

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Boosting Protein Graph Representations through Static-Dynamic Fusion

Local structural flexibility drives oligomorphism in computationally designed protein assemblies

Computational design of highly signalling-active membrane receptors through solvent-mediated allosteric networks

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

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

Efficient and insightful descriptors for representing molecular and material space

Enhanced CO2 Photoconversion at Elevated Pressures Using Conductive Polymer Modified Metal–Organic Framework

Influence of Amino Acid Substitutions in Capsid Proteins of Coxsackievirus B5 on Free Chlorine and Thermal Inactivation

New Applications of 1,3,2-Diazaphospholenes in Catalysis

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Solvation Free Energies from Machine Learning Molecular Dynamics

Automated all-functionals infrared and Raman spectra

Machine learning-aided generative molecular design

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Orbital-Resolved DFT plus U for Molecules and Solids

The simultaneous Selective Catalytic Reduction of N2O and NO over Fe-exchanged zeolites

Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO2 Hydrogenation

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