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. The powerful transition path sampling method coupled with in-depth post-processing analysis has been successfully used to elucidate the different chemical pathways, transition states, protein dynamics, and free energy barriers of reactions catalyzed by such laboratory-optimized enzymes. This research provides an explanation for how different chemical modifications in an enzyme affect its catalytic activity in ways that are not predictable by static design algorithms.

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. For 3D images, this is very labor intensive. We introduce 'targeted augmentation', a method to automatically synthesize artificial annotations from a few manual annotations. Our method ('Targettrack') learns the internal deformations of the brain to synthesize annotations for new postures by deforming GT annotations. This reduces the need for manual annotation and proofreading. A graphical user interface allows the application of the method end-to-end. We demonstrate Targettrack on recordings where neurons are labeled as key points or 3D volumes. Analyzing freely moving animals exposed to odor pulses, we uncover rich patterns in interneuron dynamics, including switching neuronal entrainment on and off.

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. The collision results are analyzed in terms of different reaction pathways: reactive or nonreactive, sticking or desorption of the products or reactants. We show that the HCO radical, although potentially formed as an intermediate regardless of the size of the water cluster, is significantly stabilized for cluster sizes larger than one water molecule and may remain adsorbed on water clusters with more than three molecules. This behavior is shown to be linked with the dissipation of the collision energy into vibrational excitation of the water cluster.

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 (H2O)nH+ (n = 20-23). These curves, which have recently been measured experimentally, are characteristic of the phase changes occurring in the aggregates with respect to temperature. The present simulations are achieved by combining parallel-tempering molecular dynamics and the self-consistent-charge density-functional based tight-binding approach and are focused on a restricted size range around (H2O)21H+ which presents singular properties. The shape of the experimental caloric curves and their size dependence are satisfactorily reproduced by the simulations which allows us to further provide a description of the phase transition in terms of structural modifications, dynamics of water molecules and proton mobility. Similar to the experiments, we observe that (H2O)21H+ exhibits a sharper phase transition than the neighbouring size clusters, which can be traced back to both structural and dynamic peculiarities.

Modeling of Manganese Atom and Dimer Isolated in Solid Rare Gases: Structure, Stability, and Effect on Spin Coupling.

Structures and energies of the trapping sites of manganese atom and dimer in solid Ar, Kr, and Xe are investigated within the classical model, which balances local distortion and long-range crystal order of the host and provides a means to estimate the relative site stabilities. The model is implemented with the additive pairwise potential field based on the ab initio and best empirical interatomic potential functions. In agreement with experiment, Mn single substitution (SS) and tetrahedral vacancy (TV) occupation are identified as stable for Ar and Kr, whereas the SS site is only found for Xe. Stable trapping sites of the weakly bound Mn2 dimer are shown to be the mergers of SS and/or TV atomic sites. For Ar, (SS + SS) and (TV + TV) sites are close in energy, whereas (SS + TV) site lies higher. The (SS + SS) accommodation is identified as the only stable site in Kr and Xe at low energies. The results are compared with the resonance Raman, electron spin resonance, and absorption spectroscopy data. Reproducing the numbers of stable sites, the calculations tend to underestimate the matrix effect on the dimer vibrational frequency and spin-spin coupling constant. Nonetheless, the level of agreement is found to be informative for tentative assignments of the complex features seen in Mn2 matrix isolation spectroscopy.

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. We report benchmark results on the conformational change FES of alanine dipeptide obtained with auxiliary density functional theory (ADFT) and second- and third-order density functional tight-binding (DFTB) methods coupled to metadynamics simulations. The influence of an explicit water solvent is also studied with DFTB, which was made possible by its lower computational cost compared to ADFT. Simulations lengths of 2.1 and 15 ns were achieved with ADFT and DFTB, respectively, in a reasonably short computational time. ADFT leads to a free energy difference (ΔF eq-ax) of ∼ -3 kcal mol-1 between the two low energy conformers, C7eq and C7ax, which is lower by only 1.5 kcal mol-1 than the ΔF eq-ax computed with DFTB. The two minima in ADFT FES are separated by an energy barrier of 9 kcal mol-1, which is higher than the DFTB barriers by 2-4 kcal mol-1. Despite these small quantitative differences, the DFTB method reveals FES shapes, confor-mation geometries and energies of the stationary points in good agreement with these found with ADFT. This validates the promising applicability of DFTB to FES of reactions occurring in larger-size systems placed in complex environments.

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 (H2O)nSO42- and (H2O)nH2SO4 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. Structural and stability features of larger sulfur-containing clusters, with up to 20 water molecules, are also determined using the SCC-DFTB scheme. The interest of this work is 2-fold: (i) the benchmark on small species demonstrates the ability of SCC-DFTB to describe complex potential energy landscapes involving hydrogen-bonds and proton transfers; (ii) it opens the way to the study of large clusters that can hardly be performed within ab initio approaches.

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. Parameters for this model are determined for hydrocarbon-argon complexes and the model is validated for small hydrocarbons. With the future aim of studying polycyclic aromatic hydrocarbons in Ar matrices, extensive benchmark calculations are performed on (C6H6)(+/0)Arn clusters against DFT and CCSD(T) calculations for the smaller sizes, and more generally against other experimental and theoretical data. Results on the structures and energetics (isomer ordering and energy separation, cohesion energy per Ar atom) are presented in detail for n = 1-8, 13, 20, 27, and 30, for both neutrals and cations. We confirm that the clustering of Ar atoms leads to a monotonous decrease of the ionization potential of benzene for n ⩽ 20, in line with previous experimental and FF data.