Transition Path Sampling Study of Engineered Enzymes That Catalyze the Morita-Baylis-Hillman Reaction: Why Is Enzyme Design so Difficult?

It is hoped that artificial enzymes designed in laboratories can be efficient alternatives to chemical catalysts that have been used to synthesize organic molecules. However, the design of artificial enzymes is challenging and requires a detailed molecular-level analysis to understand the mechanism they promote in order to design efficient variants. In this study, we computationally investigate the mechanism of proficient Morita-Baylis-Hillman enzymes developed using a combination of computational design and directed evolution.

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation.

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional neural network with ground-truth (GT) annotations of images representing different brain postures.

Molecular Dynamics Study of the Collision-Induced Reaction of H with CO on Small Water Clusters.

The successive hydrogenation of CO is supposed to be the main mechanism leading to the formation of complex oxygenated species in the interstellar medium, possibly mediated by ice layers or ice grains. In order to simulate the dynamical influence of a water environment on the first step of the hydrogenation process, we perform molecular dynamics simulations of the reactive collision of H with CO adsorbed on water clusters in the framework of the self-consistent-charge density functional based tight-binding approach (SCC-DFTB) to calculate potential energy surfaces. The reaction probabilities and the reactive cross sections are determined for water cluster sizes up to ten water molecules.

Theoretical investigation of the solid-liquid phase transition in protonated water clusters.

Protonated water clusters have received a lot of attention as they offer tools to bridge the gap between molecular and bulk scales of water. However, their properties are still not fully understood and deserve further theoretical and experimental investigations. In this work, we simulate the caloric curves of protonated water clusters (HO)H (n = 20-23).

Metadynamics combined with auxiliary density functional and density functional tight-binding methods: alanine dipeptide as a case study.

Application of ab initio molecular dynamics to study free energy surfaces (FES) is still not commonly performed because of the extensive sampling required. Indeed, it generally necessitates computationally costly simulations of more than several hundreds of picoseconds. To achieve such studies, efficient density functional theory (DFT) formalisms, based on various levels of approximate computational schemes, have been developed, and provide a good alternative to commonly used DFT implementations.

Structural Characterization of Sulfur-Containing Water Clusters Using a Density-Functional Based Tight-Binding Approach.

A global optimization search of low-energy isomers is carried out to investigate the structural and stability properties of sulfur-containing water clusters, including both (HO)SO and (HO)HSO aggregates. The systematic optimization algorithm involves a combination of parallel-tempering molecular dynamics and periodic gradient-driven quenches with energy and energy-gradient calculations performed using the Self-Consistent-Charge Density-Functional based Tight-Binding (SCC-DFTB) scheme. Comparisons with new MP2 and DFT calculations on the smallest systems and previous ab initio investigations of the literature show that the SCC-DFTB approach provides a fairly accurate description of both neutral and ionic species, comparable to that of DFT.

A density functional tight binding/force field approach to the interaction of molecules with rare gas clusters: application to (C6H6)(+/0)Ar(n) clusters.

We propose in the present paper a SCC-DFTB/FF (Self-Consistent-Charge Density Functional based Tight Binding/Force-Field) scheme adapted to the investigation of molecules trapped in rare gas environments. With respect to usual FF descriptions, the model involves the interaction of quantum electrons in a molecule with rare gas atoms in an anisotropic scheme. It includes polarization and dispersion contributions and can be used for both neutral and charged species.