The relationship between structure and reactivity plays a dominant role in water dissociation on the various TiOsub.2 crystallines. To observe the adsorption and dissociation behavior of Hsub.2O, the ...reaction force field (ReaxFF) is used to investigate the dynamic behavior of Hsub.2O on rutile (110) and anatase (101) surfaces in an aqueous environment. Simulation results show that there is a direct proton transfer between the adsorbed Hsub.2O (Hsub.2Osub.ad) and the bridging oxygen (Osub.br) on the rutile (110) surface. Compared with that on the rutile (110) surface, an indirect proton transfer occurs on the anatase (101) surface along the H-bond network from the second layer of water. This different mechanism of water dissociation is determined by the distance between the 5-fold coordinated Ti (Tisub.5c) and Osub.br of the rutile and anatase TiOsub.2 surfaces, resulting in the direct or indirect proton transfer. Additionally, the hydrogen bond (H-bond) network plays a crucial role in the adsorption and dissociation of Hsub.2O on the TiOsub.2 surface. To describe interfacial water structures between TiOsub.2 and bulk water, the double-layer model is proposed. The first layer is the dissociated Hsub.2O on the rutile (110) and anatase (101) surfaces. The second layer forms an ordered water structure adsorbed to the surface Osub.br or terminal OH group through strong hydrogen bonding (H-bonding). Affected by the H-bond network, the Hsub.2O dissociation on the rutile (110) surface is inhibited but that on the anatase (101) surface is promoted.
Featured Cover Vlassis, Nikolaos N.; Zhao, Puhan; Ma, Ran ...
International journal for numerical methods in engineering,
09/2022, Letnik:
123, Številka:
17
Journal Article
Recenzirano
Odprti dostop
The cover image is based on the Original Article Molecular dynamics inferred transfer learning models for finite‐strain hyperelasticity of monoclinic crystals: Sobolev training and validations ...against physical constraints by Nikolaos Vlassis et al., https://doi.org/10.1002/nme.6992.
Since the first attempts at structure-based drug design about four decades ago, molecular modelling techniques for drug design have developed enormously, along with the increasing computational power ...and structural and biological information of active compounds and potential target molecules. Nowadays, molecular modeling can be considered to be an integral component of the modern drug discovery and development toolbox. Nevertheless, there are still many methodological challenges to be overcome in the application of molecular modeling approaches to drug discovery. The eight original research and five review articles collected in this book provide a snapshot of the state-of-the-art of molecular modeling in drug design, illustrating recent advances and critically discussing important challenges. The topics covered include virtual screening and pharmacophore modelling, chemoinformatic applications of artificial intelligence and machine learning, molecular dynamics simulation and enhanced sampling to investigate contributions of molecular flexibility to drug–receptor interactions, the modeling of drug–receptor solvation, hydrogen bonding and polarization, and drug design against protein–protein interfaces and membrane protein receptors.
The inclusion complexes of cucurbitnuril, CBn (n = 6–8), with poly aromatic hydrocarbon (PAH) Benzo(a)Pyrene (BaP), and fluoranthene (FLT) were investigated carefully in aqueous media. Fluorescence ...and sup.1H NMR spectroscopy were used to characterize and investigate the inclusion complexes that were prepared in the aqueous media. The most predominant complexes of both guests with hosts were the 1:1 guest: host complexes. Stability constants of 2322 ± 547 Msup.−1, 7281 ± 689 Msup.−1, 3566 ± 473 Msup.−1 were obtained for the complexes of BaP with CB6, CB7, and CB8, respectively. On the other hand, stability constants of 5900.270 ± 326 Msup.−1, 726.87 ± 78 Msup.−1, 3327.059 ± 153 Msup.−1 were obtained for the complexes of FLT with CB6, CB7, and CB8, respectively. Molecular dynamic (MD) simulations were used to study the mode and mechanism of the inclusion process and to monitor the stability of these complexes in aqueous media at an atomistic level. Analysis of MD trajectories has shown that both BaP and FLT form stable inclusion complexes with CB7 and CB8 in aqueous media throughout the simulation time, subsequently corroborating the experimental results. Nevertheless, the small size of CB6 prohibited the encapsulation of the two PAHs inside the cavity, but stable exclusion complex was observed between them. The main driving forces for the stability of these complexes are the hydrophobic forces, van der Waals interactions, electrostatic effect, the π····π and C–H···π interaction. These results suggest that BaP and FLT can form stable complexes with CBn (n = 6–8) in solution.
How to fabricate large area controllable surface-enhanced Raman scattering (SERS) active nanostructure substrates has always been one of the important issues in the development of nanostructure ...devices. In this paper, nano-etching technology and magnetron sputtering technology are combined to prepare nanostructure substrate with evolvable structure, and Ag/TiOsub.2/Ag composites are introduced into the evolvable composite structure. The activity of SERS is further enhanced by the combination of TiOsub.2 and Ag and the electron transfer characteristics of TiOsub.2 itself. Deposition, plasma etching, and transfer are carried out on self-assembled 200 nm polystyrene (PS) colloidal sphere arrays. Due to the shadow effect between colloidal spheres and the size of metal particles introduced by deposition, a series of Ag/TiOsub.2/Ag nanostructure arrays with adjustable nanostructure substrates such as nano-cap (NC), nano cap-star (NCS), and nano particle-disk (NPD) can be obtained. These nanoarrays with rough surfaces and different evolutionary structures can uninterruptedly regulate optical plasmon resonance and reconstruct SERS hotspots over a large range, which has potential application value in surface science, chemical detection, nanometer photonics, and so on.
Despite the biological importance of protein–protein complexes, determining their structures and association mechanisms remains an outstanding challenge. Here, we report the results of atomic-level ...simulations in which we observed five protein–protein pairs repeatedly associate to, and dissociate from, their experimentally determined native complexes using a molecular dynamics (MD)–based sampling approach that does not make use of any prior structural information about the complexes. To study association mechanisms, we performed additional, conventional MD simulations, in which we observed numerous spontaneous association events. A shared feature of native association for these five structurally and functionally diverse protein systems was that if the proteins made contact far from the native interface, the native state was reached by dissociation and eventual reassociation near the native interface, rather than by extensive interfacial exploration while the proteins remained in contact. At the transition state (the conformational ensemble from which association to the native complex and dissociation are equally likely), the protein–protein interfaces were still highly hydrated, and no more than 20% of native contacts had formed.
This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio calculations for molecular ...dynamics simulations. While most contemporary symmetry-aware models use invariant convolutions and only act on scalars, NequIP employs E(3)-equivariant convolutions for interactions of geometric tensors, resulting in a more information-rich and faithful representation of atomic environments. The method achieves state-of-the-art accuracy on a challenging and diverse set of molecules and materials while exhibiting remarkable data efficiency. NequIP outperforms existing models with up to three orders of magnitude fewer training data, challenging the widely held belief that deep neural networks require massive training sets. The high data efficiency of the method allows for the construction of accurate potentials using high-order quantum chemical level of theory as reference and enables high-fidelity molecular dynamics simulations over long time scales.
![Comparison of H[sub.2]O Ads...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/1420-3049/small "Comparison of H[sub.2]O Adsorption and Dissociation Behaviors on Rutile Surfaces Based on ReaxFF Molecular Dynamics Simulation")
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![Design of Ag/TiO[sub.2]/Ag ...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/1996-1944/small "Design of Ag/TiO[sub.2]/Ag Composite Nano-Array Structure with Adjustable SERS-Activity")
