RESUMO
Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug discovery, but there is still an urgent need for user-friendly interfaces that bridge the gap between these sophisticated tools and scientists, particularly those who are less computer savvy. Herein, we present DrugFlow, an AI-driven one-stop platform that offers a clean, convenient, and cloud-based interface to streamline early drug discovery workflows. By seamlessly integrating a range of innovative AI algorithms, covering molecular docking, quantitative structure-activity relationship modeling, molecular generation, ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction, and virtual screening, DrugFlow can offer effective AI solutions for almost all crucial stages in early drug discovery, including hit identification and hit/lead optimization. We hope that the platform can provide sufficiently valuable guidance to aid real-word drug design and discovery. The platform is available at https://drugflow.com.
Assuntos
Inteligência Artificial , Descoberta de Drogas , Descoberta de Drogas/métodos , Simulação de Acoplamento Molecular , Relação Quantitativa Estrutura-Atividade , Algoritmos , Desenho de Fármacos , Software , Humanos , Computação em NuvemRESUMO
BACKGROUND: Antibiotic exposure can occur in medical settings and from environmental sources. Long-term effects of brief antibiotic exposure in early life are largely unknown. RESULTS: Post a short-term treatment by ceftriaxone to C57BL/6 mice in early life, a 14-month observation was performed using 16S rRNA gene-sequencing technique, metabolomics analysis, and metagenomics analysis on the effects of ceftriaxone exposure. Firstly, the results showed that antibiotic pre-treatment significantly disturbed gut microbial α and ß diversities (P < 0.05). Both Chao1 indices and Shannon indices manifested recovery trends over time, but they didn't entirely recover to the baseline of control throughout the experiment. Secondly, antibiotic pre-treatment reduced the complexity of gut molecular ecological networks (MENs). Various network parameters were affected and manifested recovery trends over time with different degrees, such as nodes (P < 0.001, R2 = 0.6563), links (P < 0.01, R2 = 0.4543), number of modules (P = 0.0672, R2 = 0.2523), relative modularity (P = 0.6714, R2 = 0.0155), number of keystones (P = 0.1003, R2 = 0.2090), robustness_random (P = 0.79, R2 = 0.0063), and vulnerability (P = 0.0528, R2 = 0.28). The network parameters didn't entirely recover. Antibiotic exposure obviously reduced the number of key species in gut MENs. Interestingly, new keystones appeared during the recovery process of network complexity. Changes in network stability might be caused by variations in network complexity, which supports the ecological theory that complexity begets stability. Besides, the metabolism profiles of the antibiotic group and control were significantly different. Correlation analysis showed that antibiotic-induced differences in gut microbial metabolism were related to MEN changes. Antibiotic exposure also caused long-term effects on gut microbial functional networks in mice. CONCLUSIONS: These results suggest that short-term antibiotic exposure in early life will cause long-term negative impacts on gut microbial diversity, MENs, and microbial metabolism. Therefore, great concern should be raised about children's brief exposure to antibiotics if the results observed in mice are applicable to humans. Video Abstract.
Assuntos
Antibacterianos , Bactérias , Microbioma Gastrointestinal , Camundongos Endogâmicos C57BL , RNA Ribossômico 16S , Microbioma Gastrointestinal/efeitos dos fármacos , Animais , Antibacterianos/farmacologia , Antibacterianos/efeitos adversos , Camundongos , RNA Ribossômico 16S/genética , Bactérias/genética , Bactérias/classificação , Bactérias/metabolismo , Bactérias/efeitos dos fármacos , Ceftriaxona/farmacologia , Metagenômica/métodos , Masculino , Metabolômica , Fezes/microbiologiaRESUMO
Both the gut microbiome and their host participate in arsenic (As) biotransformation, while their exact roles and mechanisms in vivo remain unclear and unquantified. In this study, as3mt-/- zebrafish were treated with tetracycline (TET, 100 mg/L) and arsenite (iAsIII) exposure for 30 days and treated with probiotic Lactobacillus rhamnosus GG (LGG, 1 × 108 cfu/g) and iAsIII exposure for 15 days, respectively. Structural equation modeling analysis revealed that the contribution rates of the intestinal microbiome to the total arsenic (tAs) and inorganic As (iAs) metabolism approached 44.0 and 18.4%, respectively. Compared with wild-type, in as3mt-/- zebrafish, microbial richness and structure were more significantly correlated with tAs and iAs, and more differential microbes and microbial metabolic pathways significantly correlated with arsenic metabolites (P < 0.05). LGG supplement influenced the microbial communities, significantly up-regulated the expressions of genes related to As biotransformation (gss and gst) in the liver, down-regulated the expressions of oxidative stress genes (sod1, sod2, and cat) in the intestine, and increased arsenobetaine concentration (P < 0.05). Therefore, gut microbiome promotes As transformation and relieves As accumulation, playing more active roles under iAs stress when the host lacks key arsenic detoxification enzymes. LGG can promote As biotransformation and relieve oxidative stress under As exposure.
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Arsênio , Microbioma Gastrointestinal , Animais , Peixe-Zebra , Fígado/metabolismo , Biotransformação , Metiltransferases/genética , Metiltransferases/metabolismoRESUMO
Ceftriaxone is an emerging contaminant due to its potential harm, while its effects on liver are still need to be clarified. In this study, we first pretreated the 8-week-old C57BL/6J mice with high dose ceftriaxone sodium (Cef, 400 mg/mL, 0.2 mL per dose) for 8 days to prepare a gut dysbiosis model, then treated with normal feed for a two-month recovery period, and applied non-targeted metabolomics (including lipidomics) to investigate the variations of fecal and liver metabolome, and coupled with targeted determination of fecal short-chain fatty acids (SCFAs) and bile acids (BAs). Lastly, the correlations and mediation analysis between the liver metabolism and gut metabolism/microbes were carried, and the potential mechanisms of the mal-effects on gut-liver axis induced by Cef pretreatment were accordingly discussed. Compared to the control group, Cef pretreatment reduced the rate of weight gain and hepatosomatic index, induced bile duct epithelial cells proliferated around the central vein and appearance of binucleated hepatocytes, decreased the ratio of total branching chains amino acids (BCAAs) to total aromatic amino acids (AAAs) in liver metabolome. In fecal metabolome, the total fecal SCFAs and BAs did not change significantly while butyric acid decreased and the primary BAs increased after Cef pretreatment. Correlation and mediation analysis revealed one potential mechanism that Cef may first change the intestinal microbiota (such as destroying its normal structure, reducing its abundance and the stability of the microbial network or certain microbe abundance like Alistipes), and then change the intestinal metabolism (such as acetate, caproate, propionate), leading to liver metabolic disorder (such as spermidine, inosine, cinnamaldehyde). This study proved the possibility of Cef-induced liver damage, displayed the overall metabolic profile of the liver following Cef pretreatment and provided a theoretical framework for further research into the mechanism of Cef-induced liver damage.
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Ceftriaxona , Fígado , Camundongos , Animais , Ceftriaxona/toxicidade , Camundongos Endogâmicos C57BL , Ácidos Graxos Voláteis , MetabolomaRESUMO
Gut microbiome can participate in arsenic metabolism. However, its efficacy in the host under arsenic stress is still controversial. To clarify their roles in fecal arsenic excretion, tissue arsenic accumulation, host physiological states and metabolism, in this study, ninety-six C57BL/6 male mice were randomly divided to four groups, groups A and B were given sterile water, and groups C and D were given the third generation of broad-spectrum antibiotic (ceftriaxone) to erase the background gut microbiome. Subsequently, groups B and D were subchronicly exposed to arsenic containing feed prepared by adding arsenical mixture (rice arsenic composition) into control feed. In group D, the fecal total arsenic (CtAs) decreased by 25.5 %, iAsIII composition increased by 46.9 %, unclarified As (uAs) composition decreased by 92.4 %, and the liver CtAs increased by 26.7 %; the fecal CtAs was positively correlated with microbial richness and some metabolites (organic acids, amino acids, carbohydrates, SCFAs, hydrophilic bile acids and their derivatives); and fecal DMA was positively correlated with microbial richness and some metabolites (ferulic acid, benzenepropanoic acid and pentanoic acid); network analysis showed that the numbers of modules, nodes, links were decreased and vulnerability was increased; some SCFAs and hydrophilic bile acid decreased, and hydrophobic bile acids increased (Ps < 0.05). In the tissue samples of group D, Il-18 and Ifn-γ gene expression increased and intestinal barrier-related genes Muc2, Occludin and Zo-1 expression decreased (Ps < 0.05); serum glutathione and urine malondialdehyde significantly increased (Ps < 0.05); urine metabolome significantly changed and the variation was correlated with six SCFAs-producing bacteria, and some SCFAs including isobutyric acid, valeric acid and heptanoic acid decreased (Ps < 0.05). Therefore, the normal gut microbiome increases fecal arsenic excretion and biotransformation, which can maintain a healthier microbiome and metabolic functions, and alleviate the metabolic disorder for their mammal host under arsenic exposure.
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Arsênio , Microbioma Gastrointestinal , Masculino , Animais , Camundongos , Arsênio/toxicidade , Camundongos Endogâmicos C57BL , Metaboloma , Fezes/microbiologia , Mamíferos , Ácidos e Sais BiliaresRESUMO
Arsenic can be specifically enriched by rice, and the health hazards caused by high arsenic rice are gradually attracting attention. This study aimed to explore the potential of microbial detoxification via gut microbiome in the treatment of sub-chronic arsenic poisoning. We first exposed mice to high-dose arsenic feed (30 mg/kg, rice arsenic composition) for 60 days to promote arsenic-induced microbes in situ in the gastrointestinal tract, then transplanted their fecal microbiota (FMT) into another batch of healthy recipient mice, and dynamically monitored the microbial colonization by 16S rRNA sequencing and ITS sequencing. The results showed that in situ arsenic-induced fecal microbiome can stably colonized and interact with indigenous microbes in the recipient mice in two weeks, and established a more stable network of gut microbiome. Then, the recipient mice continued to receive high-dose arsenic exposure for 52 days. After above sub-chronic arsenic exposure, compared with the non-FMT group, fecal arsenic excretion, liver and plasma arsenic accumulation were significantly lower (P < 0.05), and that in kidney, hair, and thighbone present no significant differences. Metabolomics of feces- plasma-brain axis were also disturbed, some up-regulated metabolites in feces, plasma, and cerebral cortex may play positive roles for the host. Therefore, microbial detoxification has potential in the treatment of sub-chronic arsenic poisoning. However, gut flora is an extremely complex community with different microorganisms have different arsenic metabolizing abilities, and various microbial metabolites. Coupled with the matrix effects, these factors will have various effects on the efflux and accumulation of arsenic. The definite effects (detoxification or non-detoxification) could be not assured based on the current study, and more systematic and rigorous studies are needed in the future.
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Intoxicação por Arsênico , Arsênio , Camundongos , Animais , Transplante de Microbiota Fecal , Arsênio/toxicidade , RNA Ribossômico 16S/genética , FezesRESUMO
Soil microorganism is an important indicator of soil health and plays a critical role in biogeochemical processes. We collected soil samples from a multi-year in-situ field experiment with two cropping modes (maize monocropping and maize-potato intercropping) subjected to four nitrogen (N) levels (N0, 0 kg·hm-2; N125, 125 kg·hm-2; N250, 250 kg·hm-2; N375, 375 kg·hm-2). By using the Biolog-ECO microplate method, soil microbial metabolic activity, diversity and utilization of six carbon groups were analyzed. The results showed that N application significantly increased the average well color development (AWCD) values, Simpson and Shannon indices, with the highest value at N250 in mono- and inter-cropped soils. Moreover, N application promoted the utilization of amino acids, amines and phenolic compounds, but decreased the utilization of polymers. Compared with monocropping at the same N level, intercropping improved the AWCD values, Simpson and Shannon indices, with a maximal improvement at N250. Intercropping and nitrogen application significantly affected the metabolic activities of the six carbon-source groups. In addition, intercropping improved the utilization of labile carbon sources, such as amino acids and carbohydrates. Results of the redundancy analysis and linear regression showed that intercropping and N application elevated AWCD values by increasing soil temperature, water content, and soil organic carbon content. Therefore, the changes in soil physicochemical properties after intercropping were the main reason for the enhancement of microbial metabolic activity under N application.
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Nitrogênio , Solo , Agricultura/métodos , Aminoácidos/metabolismo , Carbono/metabolismo , Nitrogênio/análise , Solo/química , Microbiologia do Solo , Zea maysRESUMO
In situ-based studies on microbiome-host interactions after arsenic exposure are few. In this study, the variations in arsenics, microbiota, and host genes along murine intestinal tracts were determined after arsenic exposure for two months. There was a gradual increase in the concentration of total As (CtAs) in feces from ileum to colon, whereas CtAs in the corresponding tissues were relatively stable. Differences in arsenic levels between feces and tissues were significantly different. The proportion of arsenite (iAsâ ¢) in feces gradually decreased, however, it gradually increased in tissues. After arsenic exposure, the diversity and abundance of microbial community and networks in each segment were significantly dysregulated. Notably, 328, 579 and 90 differently expressed genes were detected in ileum, cecum, and colon, respectively. In addition, microbiome and transcriptome analyses showed a significant correlation between the abundance of Faecalibaculum and expressions of Plb1, Hspa1b, Areg and Duoxa2 genes. This implies that they may be involved in arsenic biotransformation. In vitro experiments using Biofidobactrium and Lactobacillus showed that probiotics have arsenic transformation abilities. Therefore, gut microbiome may modulate arsenic accumulation, excretion and detoxification along the digestive tract. Moreover, the abundance and diversity of gut microbiome may be related to the changes in host health.
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Arsênio , Arsenicais , Microbioma Gastrointestinal , Microbiota , Animais , Arsênio/toxicidade , Microbioma Gastrointestinal/genética , Camundongos , TranscriptomaRESUMO
Long-term consumption of arsenic-contaminated rice has become a public health issue that urgently needs to be addressed. In this study, mice were exposed to arsenic in rice (low dose, 0.91 mg/kg; medium dose, 9.1 mg/kg) for 30 days and 60 days, respectively, and the effects on pathological structures of spleen and skin, as well as the structure of the fecal microbiome were examined. The findings revealed dose/time cumulative effects on pathological changes, with even a low dose exposure for 30 days causing destruction of splenic follicular structure and thickening of dermal keratinized and epidermal layers. The Firmicutes/Bacteroidetes ratio in the community and the positive/negative ratio in network links were higher in arsenic groups, suggesting that arsenic resulted in a less healthy and unstable microbiome for the host. Thus lifetime consumption of arsenic in rice may have potential health effects on humans and must be carefully assessed to safeguard human health. Furthermore, in arsenic groups, arsenic-resistant bacteria or arsenic hazards remediation bacteria changed to be the dominant bacteria and acted as the core bacteria in the network modules. Some microbial arsenic transforming genes (arsC, arsR, arsA, ACR3, and aoxB) differed, indicating that the gut microbiome changed to withstand arsenic stress. Furthermore, Faecalibaculum, Lachnospiraceae_NK4A136_group, Angelakisella, Ruminiclostridium, and Desulfovibrionaceae are positively associated with arsenic dosage and may be useful in the early detection of arsenicals.