Deciphering of interactions between platinated DNA and HMGB1 by hydrogen/deuterium exchange mass spectrometry

A high mobility group box 1 (HMGB1) protein has been reported to recognize both 1,2-intrastrand crosslinked DNA by cisplatin (1,2-cis-Pt-DNA) and monofunctional platinated DNA using trans-[PtCl2(NH3)(thiazole)] (1-trans-PtTz-DNA). However, the molecular basis of recognition between the trans-PtTz-DNA and HMGB1 remains unclear. In the present work, we described a hydrogen/deuterium exchange mass spectrometry (HDX-MS) method in combination with docking simulation to decipher the interactions of platinated DNA with domain A of HMGB1. The global deuterium uptake results indicated that 1-trans-PtTz-DNA bound to HMGB1a slightly tighter than the 1,2-cis-Pt-DNA. The local deuterium uptake at the peptide level revealed that the helices I and II, and loop 1 of HMGB1a were involved in the interactions with both platinated DNA adducts. However, docking simulation disclosed different H-bonding networks and distinct DNA-backbone orientations in the two Pt-DNA-HMGB1a complexes. Moreover, the Phe37 residue of HMGB1a was shown to play a key role in the recognition between HMGB1a and the platinated DNAs. In the cis-Pt-DNA-HMGB1a complex, the phenyl ring of Phe37 intercalates into a hydrophobic notch created by the two platinated guanines, while in the trans-PtTz-DNA-HMGB1a complex the phenyl ring appears to intercalate into a hydrophobic crevice formed by the platinated guanine and the opposite adenine in the complementary strand, forming a penta-layer π–π stacking associated with the adjacent thymine and the thiazole ligand. This work demonstrates that HDX-MS associated with docking simulation is a powerful tool to elucidate the interactions between platinated DNAs and proteins

Enhanced cycling stability of Li–O2 batteries by using a polyurethane/SiO2/glass fiber nanocomposite separator

A considerable improvement in the cycle performance of aprotic Li–O2 batteries was achieved by using a polyurethane/SiO2 gel nanoparticles/glass fiber (PU/SiO2/GF) nanocomposite separator, where a persistent capability of 1000 mA h g−1 was maintained for at least 300 charge/discharge cycles in a DMSO electrolyte with 1 M LiClO4 and 0.05 M LiI. In comparison, the cell with a conventional GF separator in the same experimental setup only run for 60 cycles. SEM, XRD and FT-IR analyses indicate that the corrosion and dendritic growth of the Li anode were significantly inhibited during the charge/discharge cycling, and the eventual failure of the Li–O2 batteries was attributed to the cathode passivation caused by the accumulation of the discharge product, which blocked the transfer of oxygen and electrolyte to the MWNTs cathode

Pseudo almost automorphic behavior of solutions to a semi-linear fractional differential equation

In this paper, we shall deal with $mu$-pseudo almost automorphic solutions to a semi-linear fractional differential equation by new concept of $mu$-pseudo almost automorphic functions presented recently. We first establish some new properties of $mu$-pseudo almost automorphic functions, and then we apply the results obtained to prove some existence theorems combined with the Leray-Schauder alternative theorem

2-Methyl­carbamoyl-4-{4-[3-(trifluoro­meth­yl)benzamido]phen­oxy}pyridinium 4-methyl­benzene­sulfonate monohydrate

The asymmetric unit of the title compound, C21H17F3N3O3 +·C7H7O3S−·H2O, contains two formula units. In one of the cations, the pyridinium and trifluoro­methyl benzene rings form dihedral angles of 87.42 (8) and 45.92 (8)°, respectively, with the central benzene ring [79.56 (8) and 43.52 (8)° in the other cation]. In the crystal structure, N—H⋯O, O—H⋯O and C—H⋯O hydrogen bonds link the ions and water mol­ecules, forming a three-dimensional network

3,3′-Dibromo-1,1′-[ethyl­enedioxy­bis(nitrilo­methyl­idyne)]dibenzene

In the centrosymmetric title compound, C16H14Br2N2O2, the intra­molecular interplanar distance between the parallel benzene rings is 1.305 (3) Å, while the inter­molecular interplanar distance (between neighbouring mol­ecules) is 3.463 (3) Å, exhibiting obvious strong inter­molecular π–π stacking inter­actions

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