A Network Enhancement Method to Identify Spurious Drug-Drug Interactions.

As medical safety and drug regulation gain heightened attention, the detection of spurious drug-drug interactions (DDI) has become key in healthcare. Although current research using graph neural networks (GNNs) to predict DDI has shown impressive results, it often fails to account for false DDI in the constructed DDI networks. Such inaccuracies caused by data errors, false alarms, or incorrect drug details can skew the network's structure and hinder the accuracy of GNN-based predictions. To tackle this challenge, we propose ANSM, a network-enhancement method specifically designed to identify and attenuate spurious links between drugs for ensuring the accuracy of DDI networks. ANSM integrates three key components: the feature extractor, the network optimizer, and the discriminative classifier. The feature extractor captures local structural features from drug node pairs, while the network optimizer leverages network information to improve feature extraction and reduce the impact of spurious DDI links. The discriminative classifier then identifies potential spurious links. Experimental results demonstrate that ANSM outperforms state-of-the-art methods in identifying spurious DDI.

Multitype Perception Method for Drug-Target Interaction Prediction.

With the growing popularity of artificial intelligence in drug discovery, many deep-learning technologies have been used to automatically predict unknown drug-target interactions (DTIs). A unique challenge in using these technologies to predict DTI is fully exploiting the knowledge diversity across different interaction types, such as drug-drug, drug-target, drug-enzyme, drug-path, and drug-structure types. Unfortunately, existing methods tend to learn the specifical knowledge on each interaction type and they usually ignore the knowledge diversity across different interaction types. Therefore, we propose a multitype perception method (MPM) for DTI prediction by exploiting knowledge diversity across different link types. The method consists of two main components: a type perceptor and a multitype predictor. The type perceptor learns distinguished edge representations by retaining the specifical features across different interaction types; this maximizes the prediction performance for each interaction type. The multitype predictor calculates the type similarity between the type perceptor and predicted interactions, and the domain gate module is reconstructed to assign an adaptive weight to each type perceptor. Extensive experiments demonstrate that our proposed MPM outperforms the state-of-the-art methods in DTI prediction.

Pan-genomic analysis provides novel insights into the association of E.coli with human host and its minimal genome.

MOTIVATION: Bacteria can usually acquire certain advantageous genes that enable the bacteria to adapt to rapidly changing niches, thereby leading to a wide range of intraspecific genome content and genetic redundancy. The minimal genome of Escherichia coli, which is the most important bacterial species, and the association between E.coli and its human host are worthy of further exploration. RESULTS: We used gene prediction and phylogenetic analysis to reveal a rich phylogenetic diversity among 491 E.coli strains and to reveal substantial differences between these strains with respect to gene number and genome length. We used pan-genomic analysis to accurately identify 867 core genes, in which only 243 genes are shared by essential genes. This analysis revealed that core genes mainly provide essential functions to the basic lifestyle of E.coli, and accessory genes are likely to confer selective advantages such as niche adaptation or the ability to colonize specific hosts. By association analysis, we found that E.coli strains in non-human hosts may more easily utilize foreign genetic materials to adapt to their surroundings, but the population in human hosts has higher demands for the control of population density, indicating that highly accurate quorum-sensing behavior is very important for harmony between E.coli and its human host. By considering core genes and previous deletions together, we proposed a potential direction for further reduction of the E.coli genome. AVAILABILITY AND IMPLEMENTATION: The data, analysis process and detailed information on software tools used in this study are all available in the supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Recombinational DSBs-intersected genes converge on specific disease- and adaptability-related pathways.

Motivation: The budding yeast Saccharomyces cerevisiae is a model species powerful for studying the recombination of eukaryotes. Although many recombination studies have been performed for this species by experimental methods, the population genomic study based on bioinformatics analyses is urgently needed to greatly increase the range and accuracy of recombination detection. Here, we carry out the population genomic analysis of recombination in S.cerevisiae to reveal the potential rules between recombination and evolution in eukaryotes. Results: By population genomic analysis, we discover significantly more and longer recombination events in clinical strains, which indicates that adverse environmental conditions create an obviously wider range of genetic combination in response to the selective pressure. Based on the analysis of recombinational double strand breaks (DSBs)-intersected genes (RDIGs), we find that RDIGs significantly converge on specific disease- and adaptability-related pathways, indicating that recombination plays a biologically key role in the repair of DSBs related to diseases and environmental adaptability, especially the human neurological disorders. By evolutionary analysis of RDIGs, we find that the RDIGs highly prevailing in populations of yeast tend to be more evolutionarily conserved, indicating the accurate repair of DSBs in these RDIGs is critical to ensure the eukaryotic survival or fitness. Supplementary information: Supplementary data are available at Bioinformatics online.

Recent progress on the structure of Ser/Thr protein phosphatases.

PP1, PP2A and PP2B, belonging to the PPP family of Ser/Thr protein phosphatases, participate in regulating many important physiological processes, such as cell cycle control, regulation of cell growth and division regulation, etc. The sequence homology between them is relatively high, and tertiary structure is conserved. Because of the complexity of the structure of PP2A and the diversity of its regulatory subunits, its structure is less well known than those of PP1 and PP2B. The PP2A holoenzyme consists of a heterodimeric core enzyme, comprising a scaffolding subunit and a catalytic subunit, as well as a variable regulatory subunit. In this study, the subunit compositions, similarities and differences between the Ser/Thr protein phosphatases structures are summarized.

[Advances of protein phosphatase-1--a review].

Protein phosphatase-1 (PP1) is a member of the Ser/Thr phosphatases and widely distributed in many organisms. The enzyme regulates many important physiological processes, including gene transcription, translation, metabolism, cell growth and division. Three grooves and beta12- beta13 loop in the molecular surface play important roles for binding inhibitors and substrates. Recent research found that beta12-beta13 loop is important for structure and character of the whole enzyme molecule, except for binding inhibitors. Functional research proves that PP1 also regulates transcription process of HIV-1, and relates with causes of many diseases, for example Alzheimer's Disease. This review summarized distribution, molecular structure, enzymatic character, catalytic mechanism and physiological function of the enzyme.

Overexpression and characterization of a lipase from Bacillus subtilis.

A novel plasmid, pBSR2, was constructed by incorporating a strong lipase promoter and a terminator into the original pBD64. A mature lipase gene from Bacillus subtilis strain IFFI10210, an existing strain for lipase expression, was cloned into the plasmid pBSR2 and transformed into B. subtilis A.S.1.1655. Thus, an overexpression strain, BSL2, was obtained. The yield of lipase is about 8.6 mg protein/g of wet weight of cell mass and 100-fold higher than that in B. subtilis strain IFFI10210. The recombinant lipase was purified in a three-step procedure involving ammonium sulfate fractionation, ion exchange, and gel filtration chromatography. Characterizations of the purified enzyme revealed a molecular mass of 24 kDa in sodium dodecyl sulfate-polyacrylamide gel electrophoresis, maximum activity at 43 degrees C and pH 8.5 for hydrolysis of p-nitrophenyl caprylate. The values of Km and Vm were found to be 0.37 mM and 303 micromol mg-1 min-1, respectively. The substrate specificity study showed that p-nitrophenyl caprylate is a preference of the enzyme. The metal ions Ca2+, K+, and Mg2+ can activate the lipase, whereas Fe2+, Cu2+, and Co2+ inhibited it. The activity of the lipase can be increased about 48% by sodium taurocholate at the concentration of 7 mM and inhibited at concentrations over 10 mM.

A novel phospholipase A2/esterase from hyperthermophilic archaeon Aeropyrum pernix K1.

An open reading frame of the hyperthermophilic archaeon Aeropyrum pernix K1 APE2325, which composed of 474 bases, was cloned and expressed in Escherichia coli BL21 (DE3) Codon Plus-RIL. The recombinant protein was purified by Ni-chelation affinity chromatography. It showed a single band with a molecular mass of 18kDa in SDS-PAGE. The purified enzyme exhibited both phospholipase A(2) and esterase activities with the optimal catalytic temperature at 90 degrees C. The enzyme activity was Ca(2+)-independent. Kinetic analysis revealed its Km, k cat, and Vm for the p-nitrophenyl propionate substrate were 103microM, 39s(-1), and 249micromol/min/mg, respectively. The recombinant protein was thermostable and its half-life at 100 degrees C was about 1h.