Mining Highly Active Oleate Hydratases by Structure Clustering, Sequence Clustering, and Ancestral Sequence Reconstruction.

Oleate hydratases (Ohys) catalyze the conversion of oleic acid (OA) to 10-()-hydroxystearic acid (10-HSA), a compound widely used in the chemical industry. However, the limited activity of Ohys has hindered their broader applications. To address this limitation, we propose a novel strategy for mining highly active Ohys through structure clustering, sequence clustering, and ancestral sequence reconstruction (SSA strategy).

PANoptosis: A new era for anti-cancer strategies.

Cancer cells possess an extraordinary ability to dodge cell death through various pathways, granting them a form of immortality-a key obstacle in oncotherapy. Thus, it's vital to unravel the intricate mechanisms behind newly discovered types of cell death that drive tumor suppression, going beyond apoptosis alone. The emergence of PANoptosis, a form of cell death intertwining necroptosis, pyroptosis, and apoptosis, offers a fresh perspective, integrating these pathways into one cohesive process.

Enzymatic Synthesis of Structured Lipids Enriched with Medium- and Long-Chain Triacylglycerols via Pickering Emulsion-Assisted Interfacial Catalysis: A Preliminary Exploration.

Medium- and long-chain triacylglycerol (MLCT), as a novel functional lipid, is valuable due to its special nutritional properties. Its low content in natural resources and inefficient synthesis during preparation have limited its practical applications. In this study, we developed an effective Pickering emulsion interfacial catalysis system (PE system) for the enzymatic synthesis of MLCT by trans-esterification.

A Highly Sensitive Model Based on Graph Neural Networks for Enzyme Key Catalytic Residue Prediction.

Determining the catalytic site of enzymes is a great help for understanding the relationship between protein sequence, structure, and function, which provides the basis and targets for designing, modifying, and enhancing enzyme activity. The unique local spatial configuration bound to the substrate at the active center of the enzyme determines the catalytic ability of enzymes and plays an important role in the catalytic site prediction. As a suitable tool, the graph neural network can better understand and identify the residue sites with unique local spatial configurations due to its remarkable ability to characterize the three-dimensional structural features of proteins.

Prediction of Plasticizer Property Based on an Improved Genetic Algorithm.

Different plasticizers have obvious differences in plasticizing properties. As one of the important indicators for evaluating plasticization performance, the substitution factor (SF) has great significance for product cost accounting. In this research, a genetic algorithm with "variable mutation probability" was developed to screen the key molecular descriptors of plasticizers that are highly correlated with the SF, and a SF prediction model was established based on these filtered molecular descriptors.

Feasible Cluster Model Method for Simulating the Redox Potentials of Laccase CueO and Its Variant.

Laccases are regarded as versatile green biocatalysts, and recent scientific research has focused on improving their redox potential for broader industrial and environmental applications. The density functional theory (DFT) quantum mechanics approach, sufficiently rigorous and efficient for the calculation of electronic structures, is conducted to better comprehend the connection between the redox potential and the atomic structural feature of laccases. According to the crystal structure of wild type laccase CueO and its variant, a truncated miniature cluster model method was established in this research.

Quantum Mechanical Investigation of the Oxidative Cleavage of the C-C Backbone Bonds in Polyethylene Model Molecules.

Recalcitrant plastic waste has caused serious global ecological problems. There is an urgent need to develop environmentally friendly and efficient methods for degrading the highly stable carbon skeleton structure of plastics. To that end, we used a quantum mechanical calculation to thoroughly investigate the oxidative scission of the carbon-carbon (C-C) backbone in polyethylene (PE).

Computational Assessment of the Molecular Structure and Properties for High Energy Density Fuel.

High energy density fuels (HEDFs) that have high volumetric net heat of combustion (NHOC), high stability, and high environmental resistance are greatly important in the fuel field and in military bases and aerospace applications. In this paper, molecular dynamics and quantum chemistry were used to compute the significant physical properties of candidate molecules for HEDFs, such as their enthalpies of combustion, enthalpies of vaporization, densities, and melting points. A computational protocol for evaluating these properties in the fuel field was established, including a new method for estimating the melting point.

A Quantum Mechanism Study of the C-C Bond Cleavage to Predict the Bio-Catalytic Polyethylene Degradation.

The growing amount of plastic solid waste (PSW) is a global concern. Despite increasing efforts to reduce the residual amounts of PSW to be disposed off through segregated collection and recycling, a considerable amount of PSW is still landfilled and the extent of PSW ocean pollution has become a worldwide issue. Particularly, polyethylene (PE) and polystyrene (PS) are considered as notably recalcitrant to biodegradation due to the carbon-carbon backbone that is highly resistant to enzymatic degradation via oxidative reactions.

Force Field Benchmark of Amino Acids. 2. Partition Coefficients between Water and Organic Solvents.

Unlabelled: The partitioning of amino acids between water and apolar environments is of vital importance in protein function and drug delivery. Here we present an extensive benchmark for octanol/water (log P), chloroform/water (log P), and cyclohexane/water (log P) partition coefficients of neutral amino acid side chain analogues (SCAs) with Amber families of ff99SB-ILDN, ff03, ff14SB, fb15, and ff15ipq, CHARMM 27, GROMOS 53A6, and OPLS-AA/L force fields. A root-mean-square error (RMSE) of 0.

Comparative Assessment of Computational Methods for Free Energy Calculations of Ionic Hydration.

Experimental observations for ionic hydration free energies are highly debated mainly due to the ambiguous absolute hydration free energy of proton, ΔG(H). Hydration free energies (HFEs) of the 112 singly charged ions in the Minnesota solvation database were predicted by six methods with explicit and implicit solvent models, namely, thermodynamic integration (TI), energy representation module (ERmod), three-dimensional reference interaction site model (3D-RISM), and continuum solvation models based on the quantum mechanical charge density (SMD) and on the Poisson-Boltzmann (PB) and generalized Born (GB) theories. Taking the solvent Galvani potential of water into account, the resulting real HFEs from TI calculations for the generalized Amber force field (GAFF) modeled ions best match the experiments based on ΔG(H) = -262.

Modeling Coordination-Directed Self-Assembly of ML Nanocapsule Featuring Competitive Guest Encapsulation.

Exploring the mechanism of self-assembly and guest encapsulation of nanocapsules is highly imperative for the design of sophisticated molecular containers and multistimuli-responsive functional materials. Here we present a molecular dynamics simulation protocol with implicit solvent and simulated annealing techniques to investigate the self-assembly and competitive guest (C and C fullerenes) encapsulation of a ML nanocapsule that is self-assembled by the coordination of mercury cations and bent bidentate ligands. Stepwise formation of the nanocapsule and competitive fullerene encapsulation during dynamic structural changes in the self-assembly were detected successfully.