Empowering AI drug discovery with explicit and implicit knowledge

Motivation: Recently, research on independently utilizing either explicit knowledge from knowledge graphs or implicit knowledge from biomedical literature for AI drug discovery has been growing rapidly. These approaches have greatly improved the prediction accuracy of AI models on multiple downstream tasks. However, integrating explicit and implicit knowledge independently hinders their understanding of molecules. Results: We propose DeepEIK, a unified deep learning framework that incorporates both explicit and implicit knowledge for AI drug discovery. We adopt feature fusion to process the multi-modal inputs, and leverage the attention mechanism to denoise the text information. Experiments show that DeepEIK significantly outperforms state-of-the-art methods on crucial tasks in AI drug discovery including drug-target interaction prediction, drug property prediction and protein-protein interaction prediction. Further studies show that benefiting from explicit and implicit knowledge, our framework achieves a deeper understanding of molecules and shows promising potential in facilitating drug discovery applications.Comment: Bioinformatic

A New Parallel Framework of SPH-SWE for Dam Break Simulation Based on OpenMP

Due to its Lagrangian nature, Smoothed Particle Hydrodynamics (SPH) has been used to solve a variety of fluid-dynamic processes with highly nonlinear deformation such as debris flows, wave breaking and impact, multi-phase mixing processes, jet impact, flooding and tsunami inundation, and fluid–structure interactions. In this study, the SPH method is applied to solve the two-dimensional Shallow Water Equations (SWEs), and the solution proposed was validated against two open-source case studies of a 2-D dry-bed dam break with particle splitting and a 2-D dam break with a rectangular obstacle downstream. In addition to the improvement and optimization of the existing algorithm, the CPU-OpenMP parallel computing was also implemented, and it was proven that the CPU-OpenMP parallel computing enhanced the performance for solving the SPH-SWE model, after testing it against three large sets of particles involved in the computational process. The free surface and velocities of the experimental flows were simulated accurately by the numerical model proposed, showing the ability of the SPH model to predict the behavior of debris flows induced by dam-breaks. This validation of the model is crucial to confirm its use in predicting landslides’ behavior in field case studies so that it will be possible to reduce the damage that they cause. All the changes made in the SPH-SWEs method are made open-source in this paper so that more researchers can benefit from the results of this research and understand the characteristics and advantages of the solution proposed

Phase stability and mechanical property of γ′- (Ni1-xCox)3Al1-yCry alloys

The phase stability and mechanical property of γ ′-(Ni _1-x Co _x ) _3 Al _1-y Cr _y phase of Ni-Co based superalloys are studied by the first-principles method. The calculated mixing enthalpies at 0 K indicate that the alloys are thermodynamically unstable against phase separation into Ni _3 AlCr and Co _3 AlCr alloys. Additions of 6.25 at % of Cr into (NiCo) _3 Al alloy can decrease the positive mixing enthalpy by 34%, hence Cr has a significant stabilizing effect on γ ′ phase. The configurational entropy can further stabilize the alloy at finite temperature. A strong tetragonal shear softening is observed for (Ni _1-x Co _x ) _3 Al _1-y Cr _y alloys with large Co concentration. Cr additions could increase C ′ of the alloys, and thus offset the softening effect of Co by a certain extent. The electronic density of states analysis demonstrates that the flexibility of Al p band and synergistic alloying effect are the physics behind the stabilization the γ ′ phase of Ni-Co based superalloy by Cr alloying

Selective production of 2-(tert-butyl)-3-methylphenol from depolymerization of enzymatic hydrolysis lignin with MoS2 catalyst

| openaire: EC/H2020/101006744/EU//EHLCATHOL This work is supported by the National Natural Science Foundation of China (21808163). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101006744. The content presented in this document represents the views of the authors, and the European Commission has no liability in respect of the content.Low selectivity and complex product distribution are the main challenges for the utilization of lignin. Herein, the selective production of 2-(tert-butyl)-3-methylphenol (TBC), an antioxidant in the polymer industry, from depolymerization of enzymatic hydrolysis lignin (EHL) on a hydrothermally synthesized MoS2 catalyst is studied. The total aromatic monomer yield is 124.1mg/g EHL and the selectivity of TBC is up to 40.3wt% in methanol at 280oC under 2MPa H2 for 6h. The FT-IR analysis of products reveals that MoS2 has a high activity for demethylation, dehydroxylation and alkylation, and the dimer conversions reveal that C-O and C-C bonds in EHL are broken with MoS2. The guaiacol and its derivants are identified as the intermediate for formation of TBC in EHL depolymerizaiton according to the effect of time on product distribution and monomer converison.Peer reviewe

Nanoliter Centrifugal Liquid Dispenser Coupled with Superhydrophobic Microwell Array Chips for High-Throughput Cell Assays

Microfluidic systems have been regarded as a potential platform for high-throughput screening technology in drug discovery due to their low sample consumption, high integration, and easy operation. The handling of small-volume liquid is an essential operation in microfluidic systems, especially in investigating large-scale combination conditions. Here, we develop a nanoliter centrifugal liquid dispenser (NanoCLD) coupled with superhydrophobic microwell array chips for high-throughput cell-based assays in the nanoliter scale. The NanoCLD consists of a plastic stock block with an array of drilled through holes, a reagent microwell array chip (reagent chip), and an alignment bottom assembled together in a fixture. A simple centrifugation at 800 rpm can dispense ~160 nL reagents into microwells in 5 min. The dispensed reagents are then delivered to cells by sandwiching the reagent chip upside down with another microwell array chip (cell chip) on which cells are cultured. A gradient of doxorubicin is then dispensed to the cell chip using the NanoCLD for validating the feasibility of performing drug tests on our microchip platform. This novel nanoliter-volume liquid dispensing method is simple, easy to operate, and especially suitable for repeatedly dispensing many different reagents simultaneously to microwells

Catalytic Ethanolysis of Enzymatic Hydrolysis Lignin over an Unsupported Nickel Catalyst : The Effect of Reaction Conditions

The effect of reaction conditions on ethanolysis of enzymatic hydrolysis lignin (EHL) with an unsupported nickel catalyst, that is, Ni(220H), was investigated. The two-dimensional heteronuclear single quantum coherence-nuclear magnetic resonance (2D-HSQC NMR) analysis of liquid products revealed that both the ether and C-C linkages in EHL were cleaved during the reaction and the ether linkages were completely cleaved under mild reaction conditions, while the cleavage of C-C linkages needed harsh reaction conditions. At 280 °C under 2 MPa H2 within 6 h, the highest aromatic monomer yield of 28.5 wt % was achieved. Further increasing the reaction temperature to 300 °C or decreasing the initial hydrogen pressure to 0 MPa was conducive to the repolymerization reaction. The ortho-alkyl phenol monomers originated from the alkyl free radicals produced from ethanol. Under 0 MPa H2, the hydrogenation of -HCCH- in side chains was inefficient, and hence, the decarboxylation and alkenyl elimination reactions of side chains were favorable.Peer reviewe

Covalent organic networks for in situ entrapment of enzymes with superior robustness and durability

Enzyme-based nanobiohybrids (EnNBHs) are an emerging biocatalyst family that can manufacture industrial products such as fuels and chemicals in a green and low- carbon manner. Designing high-performance EnNBHs could confer enzymes with superior robustness and durability, while current strategies confront grand challenges. Indeed, the reticular chemistry materials, especially metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bond organic frameworks (HOFs), are several good candidates for constructing EnNBHs. While, MOFs and HOFs are constructed by coordination bond and hydrogen bond, respectively, which may be destroyed by acid or organic solvents, thus causing structural degradation and loss of protection to enzymes. The use of acetic acid (6 mol L-1) and organic solvents is conventional conditions for the synthesis of COFs, which may be inapplicable for de novo constructing EnNBHs. Herein, a facile and versatile in situ entrapment strategy is developed to entrap a series of enzymes in crystalline imine-based covalent organic networks (CONs) under mild conditions. Notably, the growth rate of CONs induced by glucose oxidase (GOx) is increased by 2 folds than that of CONs in the absence of GOx. Moreover, the crystalline CONs could create confinement environment and safeguard the hosted enzymes from being denatured under unfavorable conditions. Given moderate crystallinity of CONs, short-range ordered micro/meso-porous structures are generated. Compared with GOx@ZIFs, the larger transport channels for reactants/products in GOx@CONs result in 1.73-fold enhancement in the catalytic efficiency. The crystalline CONs could also serve as a cell-mimic nanoreactor for multienzyme catalysis, demonstrating the potential applications in biomanufacturing, bioimaging, biosensing and so on

PLGA nanoparticles for the oral delivery of nuciferine: preparation, physicochemical characterization and in vitro/in vivo studies

This article reports a promising approach to enhance the oral delivery of nuciferine (NUC), improve its aqueous solubility and bioavailability, and allow its controlled release as well as inhibiting lipid accumulation. NUC-loaded poly lactic-co-glycolic acid nanoparticles (NUC-PLGA-NPs) were prepared according to a solid/oil/water (s/o/w) emulsion technique due to the water-insolubility of NUC. PLGA exhibited excellent loading capacity for NUC with adjustable dosing ratios. The drug loading and encapsulation efficiency of optimized formulation were 8.89 ± 0.71 and 88.54 ± 7.08%, respectively. NUC-PLGA-NPs exhibited a spherical morphology with average size of 150.83 ± 5.72 nm and negative charge of −22.73 ± 1.63 mV, which are suitable for oral administration. A sustained NUC released from NUC-PLGA-NPs with an initial exponential release owing to the surface associated drug followed by a slower release of NUC, which was entrapped in the core. In addition, ∼77 ± 6.67% was released in simulating intestinal juice, while only about 45.95 ± 5.2% in simulating gastric juice. NUC-PLGA-NPs are more efficient against oleic acid (OA)-induced hepatic steatosis in HepG2 cells when compared to naked NUC (n-NUC, *p < 0.05). The oral bioavailability of NUC-PLGA-NPs group was significantly higher (**p < 0.01) and a significantly decreased serum levels of total cholesterol (TC), triglycerides (TG) and low-density lipoprotein cholesterol (LDL-C), as well as a higher concentration of high-density lipoprotein cholesterol (HDL-C) was observed, compared with that of n-NUC treated group. These findings suggest that NUC-PLGA-NPs hold great promise for sustained and controlled drug delivery with improved bioavailability to alleviating lipogenesis