Increasing evidence shows that Aβ oligomers are key pathogenic molecules in Alzheimer’s disease. Among Aβ oligomers, dimer is the smallest aggregate and toxic unit. Therefore, understanding its structural and dynamic properties is quite useful to prevent the formation and toxicity of the Aβ oligomers. In this study, we performed molecular dynamic simulations on four Aβ42 dimers, 2NCb, CNNC, NCNC and NCCN, within the hydrated DPPC membrane. Four Aβ42 dimers differ in the arrangements of two Aβ42 peptides. This study aims to investigate the impact of aggregation pattern of two Aβ peptides on the structural stability of the Aβ42 dimer and its disruption to the biological membrane. The MD results demonstrate that the NCCN, CNNC and NCNC have the larger structural fluctuation at the N-terminus of Aβ42 peptide, where the β-strand structure converts into the coil structure. The loss of the N-terminal β-strand further impairs the aggregate ability of Aβ42 dimer. In addition, inserting Aβ42 dimer into the membrane can considerably decrease the average APL of DPPC membrane. Moreover this decrease effect is largely dependent on the distance to the location of Aβ42 dimer and its secondary structure forms. Based on the results, the 2NCb is considered as a stable dimeric unit for aggregating the larger Aβ42 oligomer, and has a potent ability to disrupt the membrane.

The objective of this paper is to analyze the relationship among the interrelated gene sequences of Alzheimer's disease (AD). Further this paper will provide a study on genetic factor of the occurrence about Alzheimer's disease, so as to provide more information on the prevention of Alzheimer's disease, the clinical diagnosis and gene therapy for Alzheimer's disease. The respective alignment of the Alzheimer's disease interrelated gene sequences with those in The National Center for Biotechnology Information (NCBI) database was studied, and the measurement relationship of these sequences was identified and analyzed by the method of fuzzy cluster. The result of fuzzy cluster analysis indicates that the gene sequences interrelated within one group is consistently having closer relationship within the group other than in another group.

Background Hodgkin Lymphoma (HL) is a type of aggressive malignancy in lymphoma that has high incidence in young adults and elderly patients. Identification of reliable diagnostic markers and efficient therapeutic targets are especially important for the diagnosis and treatment of HL. Although many HL-related molecules have been identified, our understanding on the molecular mechanisms underlying the disease is still far from complete due to its complex and heterogeneous characteristics. In such situation, exploring the molecular mechanisms underlying HL via systems biology approaches provides a promising option. In this study, we try to elucidate the molecular mechanisms related to the disease and identify potential pharmaceutical targets from a network-based perspective. Results We constructed a series of network models. Based on the analysis of these networks, we attempted to identify the biomarkers and elucidate the molecular mechanisms underlying HL. Initially, we built three different but related protein networks, i.e., background network, HL-basic network and HL-specific network. By analyzing these three networks, we investigated the connection characteristic of the HL-related proteins. Subsequently, we explored the miRNA regulation on HL-specific network and analyzed three kinds of simple regulation patterns, i.e., co-regulation of protein pairs, as well as the direct and indirect regulation of triple proteins. Finally, we constructed a simplified protein network combined with the regulation of miRNAs on proteins to better understand the relation between HL-related proteins and miRNAs. Conclusions We find that the HL-related proteins are more likely to connect with each other compared to other proteins. Moreover, the HL-specific network can be further divided into five sub-networks and 49 proteins as the backbone of HL-specific network make up and connect these 5 sub-networks. Thus, they may be closely associated with HL. In addition, we find that the co-regulation of protein pairs is the main regulatory pattern of miRNAs on the protein network in the HL-specific network. According to the regulation of miRNA on protein network, we have identified 5 core miRNAs as the potential biomarkers for diagnostic of HL. Finally, several protein pathways have been identified to closely associated with HL, which provides deep insights into underlying mechanism of HL. Electronic supplementary material The online version of this article (10.1186/s12859-019-3041-9) contains supplementary material, which is available to authorized users.

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