{"title":"Exploring bacterial metabolites in microbe-human host dialogue and their therapeutic potential in Alzheimer's diseases.","authors":"Sarangthem Dinamani Singh, Pankaj Bharali, Selvaraman Nagamani","doi":"10.1007/s11030-024-11028-y","DOIUrl":null,"url":null,"abstract":"<p><p>Neurological dysfunction in association with aging, dementia, and cognitive impairment is the major cause of Alzheimer's disease (AD). Current AD therapies often yield unsatisfactory results due to their poor mechanism in treating the underlying mechanism of the disease. Recent studies suggested that metabolites from the gut microbiota facilitate brain-gut communication. A systematic network pharmacology study and the structure- and analog-based approaches are employed to investigate the metabolites produced by gut microbiota to treat AD. The microbiota metabolites available in the gutMGene database were considered in this study. Two servers, namely Swiss Target Prediction (STP) and Similarity Ensemble Approach (SEA), were used to identify the possible AD targets for the selected metabolites. Detailed KEGG pathway and Gene Ontology (GO) analysis on identified hub genes highlighted the importance of IL6, AKT1, and GSK3B in AD pathophysiology. MMTSp (Microbiota Metabolites Target Signaling pathways) network analysis elucidated that there is a strong relationship with microbiota (Paraprevotella xylaniphila YIT 11841, Bifidobacterium dentium, Paraprevotella clara YIT 11840, Enterococcus sp. 45, Bacteroides sp. 45, Bacillus sp. 46, Escherichia sp. 33, Enterococcus casseliflavus, Bacteroides uniformis, Alistipes indistinctus YIT 12060, Bacteroides ovatus, Escherichia sp. 12, and Odoribacter laneus YIT 12061) and AD pathogenesis. In addition to this, we performed molecular docking to study the metabolite interactions in the AD drug targets. The ADME/T properties of these metabolites were also calculated and the results are discussed in detail.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Diversity","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s11030-024-11028-y","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
Neurological dysfunction in association with aging, dementia, and cognitive impairment is the major cause of Alzheimer's disease (AD). Current AD therapies often yield unsatisfactory results due to their poor mechanism in treating the underlying mechanism of the disease. Recent studies suggested that metabolites from the gut microbiota facilitate brain-gut communication. A systematic network pharmacology study and the structure- and analog-based approaches are employed to investigate the metabolites produced by gut microbiota to treat AD. The microbiota metabolites available in the gutMGene database were considered in this study. Two servers, namely Swiss Target Prediction (STP) and Similarity Ensemble Approach (SEA), were used to identify the possible AD targets for the selected metabolites. Detailed KEGG pathway and Gene Ontology (GO) analysis on identified hub genes highlighted the importance of IL6, AKT1, and GSK3B in AD pathophysiology. MMTSp (Microbiota Metabolites Target Signaling pathways) network analysis elucidated that there is a strong relationship with microbiota (Paraprevotella xylaniphila YIT 11841, Bifidobacterium dentium, Paraprevotella clara YIT 11840, Enterococcus sp. 45, Bacteroides sp. 45, Bacillus sp. 46, Escherichia sp. 33, Enterococcus casseliflavus, Bacteroides uniformis, Alistipes indistinctus YIT 12060, Bacteroides ovatus, Escherichia sp. 12, and Odoribacter laneus YIT 12061) and AD pathogenesis. In addition to this, we performed molecular docking to study the metabolite interactions in the AD drug targets. The ADME/T properties of these metabolites were also calculated and the results are discussed in detail.
期刊介绍：
Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including:
combinatorial chemistry and parallel synthesis;
small molecule libraries;
microwave synthesis;
flow synthesis;
fluorous synthesis;
diversity oriented synthesis (DOS);
nanoreactors;
click chemistry;
multiplex technologies;
fragment- and ligand-based design;
structure/function/SAR;
computational chemistry and molecular design;
chemoinformatics;
screening techniques and screening interfaces;
analytical and purification methods;
robotics, automation and miniaturization;
targeted libraries;
display libraries;
peptides and peptoids;
proteins;
oligonucleotides;
carbohydrates;
natural diversity;
new methods of library formulation and deconvolution;
directed evolution, origin of life and recombination;
search techniques, landscapes, random chemistry and more;
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