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The structural variability data of drug transporter (DT) are key for research on precision medicine and rational drug use. However, these valuable data are not sufficiently covered by the available databases. In this study, a major update of VARIDT (a database previously constructed to provide DTs’ variability data) was thus described. First, the experimentally resolved structures of all DTs reported in the original VARIDT were discovered from PubMed and Protein Data Bank. Second, the structural variability data of each DT were collected by literature review, which included: (a) mutation-induced spatial variations in folded state, (b) difference among DT structures of human and model organisms, (c) outward/inward-facing DT conformations and (d) xenobiotics-driven alterations in the 3D complexes. Third, for those DTs without experimentally resolved structural variabilities, homology modeling was further applied as well-established protocol to enrich such valuable data. As a result, 145 mutation-induced spatial variations of 42 DTs, 1622 inter-species structures originating from 292 DTs, 118 outward/inward-facing conformations belonging to 59 DTs, and 822 xenobiotics-regulated structures in complex with 57 DTs were updated to VARIDT (https://idrblab.org/varidt/ and http://varidt.idrblab.net/). All in all, the newly collected structural variabilities will be indispensable for explaining drug sensitivity/selectivity, bridging preclinical research with clinical trial, revealing the mechanism underlying drug-drug interaction, and so on., Graphical Abstract Graphical AbstractStructural variability of drug transporter (VARIDT 2.0).

With the rapid progress in pharmaceutical experiments and clinical investigations, extensive knowledge of drug transporters (DTs) has accumulated, which is valuable data for the understanding of drug metabolism and disposition. However, such data are largely dispersed in the literature, which hampers its utility and significantly limits its possibility for comprehensive analysis. A variety of databases have, therefore, been constructed to provide DT-related data, and they were reviewed in this study. First, several knowledge bases providing data regarding clinically important drugs and their corresponding transporters were discussed, which constituted the most important resources of DT-centered data. Second, some databases describing the general transporters and their functional families were reviewed. Third, various databases offering transporter information as part of their entire data collection were described. Finally, customized database functions that are available to facilitate DT-related research were discussed. This review provided an overview of the whole collection of DT-related databases, which might facilitate research on precision medicine and rational drug use. SIGNIFICANCE STATEMENT: A collection of well established databases related to drug transporters were comprehensively reviewed, which were organized according to their importance in drug absorption, distribution, metabolism, and excretion research. These databases could collectively contribute to the research on rational drug use.

Besides the environmental factors having tremendous impacts on the composition of microbial community, the host factors have recently gained extensive attentions on their roles in shaping human microbiota. There are two major types of host factors: host genetic factors (HGFs) and host immune factors (HIFs). These factors of each type are essential for defining the chemical and physical landscapes inhabited by microbiota, and the collective consideration of both types have great implication to serve comprehensive health management. However, no database was available to provide the comprehensive factors of both types. Herein, a database entitled ‘Host Genetic and Immune Factors Shaping Human Microbiota (GIMICA)’ was constructed. Based on the 4257 microbes confirmed to inhabit nine sites of human body, 2851 HGFs (1368 single nucleotide polymorphisms (SNPs), 186 copy number variations (CNVs), and 1297 non-coding ribonucleic acids (RNAs)) modulating the expression of 370 microbes were collected, and 549 HIFs (126 lymphocytes and phagocytes, 387 immune proteins, and 36 immune pathways) regulating the abundance of 455 microbes were also provided. All in all, GIMICA enabled the collective consideration not only between different types of host factor but also between the host and environmental ones, which is freely accessible without login requirement at: https://idrblab.org/gimica/, Graphical Abstract Graphical AbstractGIMICA is unique in: (i) providing both host genetic and immune factors shaping human microbiota and (ii) enabling collective consideration not only among various host factors but also between the host and environmental ones.

Crimean-Congo hemorrhagic fever virus (CCHFV) is a causative agent of serious hemorrhagic diseases in humans with high mortality rates. CCHFV glycoprotein Gc plays critical roles in mediating virus-host membrane fusion and has been studied extensively as an immunogen. However, the molecular mechanisms involved in membrane fusion and Gc-specific antibody-antigen interactions remain unresolved largely because structural information of this glycoprotein is missing. We designed a trimeric protein including most of the ectodomain region of Gc from the prototype CCHFV strain, IbAr10200, which enabled the cryo-electron microscopy structure to be solved at a resolution of 2.8 ​Å. The structure confirms that CCHFV Gc is a class II fusion protein. Unexpectedly, structural comparisons with other solved Gc trimers in the postfusion conformation revealed that CCHFV Gc adopted hybrid architectural features of the fusion loops from hantaviruses and domain III from phenuiviruses, suggesting a complex evolutionary pathway among these bunyaviruses. Antigenic sites on CCHFV Gc that protective neutralizing antibodies target were mapped onto the CCHFV Gc structure, providing valuable information that improved our understanding of potential neutralization mechanisms of various antibodies.

Drug-metabolizing enzymes (DMEs) are critical determinant of drug safety and efficacy, and the interactome of DMEs has attracted extensive attention. There are 3 major interaction types in an interactome: microbiome–DME interaction (MICBIO), xenobiotics–DME interaction (XEOTIC) and host protein–DME interaction (HOSPPI). The interaction data of each type are essential for drug metabolism, and the collective consideration of multiple types has implication for the future practice of precision medicine. However, no database was designed to systematically provide the data of all types of DME interactions. Here, a database of the Interactome of Drug-Metabolizing Enzymes (INTEDE) was therefore constructed to offer these interaction data. First, 1047 unique DMEs (448 host and 599 microbial) were confirmed, for the first time, using their metabolizing drugs. Second, for these newly confirmed DMEs, all types of their interactions (3359 MICBIOs between 225 microbial species and 185 DMEs; 47 778 XEOTICs between 4150 xenobiotics and 501 DMEs; 7849 HOSPPIs between 565 human proteins and 566 DMEs) were comprehensively collected and then provided, which enabled the crosstalk analysis among multiple types. Because of the huge amount of accumulated data, the INTEDE made it possible to generalize key features for revealing disease etiology and optimizing clinical treatment. INTEDE is freely accessible at: https://idrblab.org/intede/, Graphical Abstract Graphical AbstractThe Interactome Database of Drug-Metabolizing Enzyme (INTEDE) provides the comprehensive interactome data from three perspectives for both human and microbial drug-metabolizing enzymes.

Pituitary adenoma (PA) is prevalent in the general population. Due to its severe complications and aggressive infiltration into the surrounding brain structure, the effective management of PA is required. Till now, no drug has been approved for treating non-functional PA, and the removal of cancerous cells from the pituitary is still under experimental investigation. Due to its superior specificity and safety profile, immunotherapy stands as one of the most promising strategies for dealing with PA refractory to the standard treatment, and various studies have been carried out to discover immune-related gene markers as target candidates. However, the lists of gene markers identified among different studies are reported to be highly inconsistent because of the greatly limited number of samples analyzed in each study. It is thus essential to substantially enlarge the sample size and comprehensively assess the robustness of the identified immune-related gene markers. Herein, a novel strategy of direct data integration (DDI) was proposed to combine available PA microarray datasets, which significantly enlarged the sample size. First, the robustness of the gene markers identified by DDI strategy was found to be substantially enhanced compared with that of previous studies. Then, the DDI of all reported PA-related microarray datasets were conducted to achieve a comprehensive identification of PA gene markers, and 66 immune-related genes were discovered as target candidates for PA immunotherapy. Finally, based on the analysis of human protein&ndash, protein interaction network, some promising target candidates (GAL, LMO4, STAT3, PD-L1, TGFB and TGFBR3) were proposed for PA immunotherapy. The strategy proposed together with the immune-related markers identified in this study provided a useful guidance for the development of novel immunotherapy for PA.

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant tumors. Upregulation of metastasis-associated protein 1 (MTA1) has been reported to contribute to the development of esophageal squamous cell carcinoma. Therefore, the objective of our study was to identify the molecular mechanisms of MTA1 underlying the invasion and metastasis of ESCC. We overexpressed MTA1 in ESCC cells to examine the role of MTA1 in the regulation of the cell invasion. In addition, using luciferase reporter assay and electrophoretic mobility shift assays, we evaluated the binding of MTA1 to the promoter of E-cadherin. We found that MTA1 overexpression promotes invasiveness of the human esophageal carcinoma cell line EC-9706. This effect was accompanied by downregulation of the epithelial cell marker E-cadherin and upregulation of vimentin and MMP-9 luciferase reporter assays showed that MTA1 inhibited the promoter activity of E-cadherin and that this was dependent on Snail, Slug and HDAC1. We also found that Snail and Slug bound the E-boxes in the promoter of E-cadherin and recruited MTA1 and HDAC1 to suppress E-cadherin expression, as confirmed by electrophoretic mobility shift and chromatin immunoprecipitation assays. MTA1 promotes tumor invasion by downregulation of E-cadherin. These results demonstrate a novel role for MTA1 in the regulation of esophageal squamous cell carcinoma invasion and provide insight into the mechanisms involved in this process.