Anandamide Hydrolysis in FAAH Reveals a Dual Strategy for Efficient Enzyme-Assisted Amide Bond Cleavage via Nitrogen Inversion

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Microsecond time-resolved cryo-electron microscopy has emerged as a novel approach for directly observing protein dynamics. By providing microsecond temporal and near-atomic spatial resolution, it has the potential to elucidate a wide range of dynamics tha ...

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Arylative Ring Expansion of 3-Vinylazetidin-3-Ols and 3-Vinyloxetan-3-Ols to Dihydrofurans by Dual Palladium and Acid Catalysis

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In contrast to the well-studied 1-vinylcyclobu- tanols, the reactivity of 3-vinylazetidin-3-ols 1 and 3- vinyloxetan-3-ols 2 under transition metal catalysis remains largely unexplored. We report herein their unique reactivity under dual palladium and acid ...

Wiley-VCH Verlag GmbH2024

A bistable inhibitory optoGPCR for multiplexed optogenetic control of neural circuits

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Information is transmitted between brain regions through the release of neurotransmitters from long-range projecting axons. Understanding how the activity of such long-range connections contributes to behavior requires efficient methods for reversibly mani ...

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

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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 ...

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Efficient and insightful descriptors for representing molecular and material space

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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 ...

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Computational drug development for membrane protein targets

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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 ...

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Solvation Free Energies from Machine Learning Molecular Dynamics

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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 ...

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At present, there is no general standard automated method for engineering metalloenzymes, industrially-relevant systems able to catalyze environmentally friendly reactions. One of the most studied natural metalloenzymes is the second isoform of human carbo ...

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Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations

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One of the main challenges hampering the development of kinetic models is the lack of kinetic parameters for many enzymatic reactions. Here, the authors introduce a framework to explore the catalytically optimal operating conditions of any complex enzyme m ...

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Advancing first principle-based molecular dynamics of biological systems with machine learning

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Molecular dynamics (MD) simulations have emerged as a transformative approach to analyse molecular systems at the atomic level, offering valuable insights into complex biological processes. Many biological phenomena can only accurately be described by inco ...

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Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

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Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

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