Small molecule modulation of microbiota: a systems pharmacology perspective.

TitleSmall molecule modulation of microbiota: a systems pharmacology perspective.
Publication TypeJournal Article
Year of Publication2022
AuthorsLiu Q, Lee B, Xie L
JournalBMC Bioinformatics
Volume23
IssueSuppl 3
Pagination403
Date Published2022 Sep 29
ISSN1471-2105
KeywordsDrug Discovery, Humans, Membrane Proteins, Microbial Interactions, Microbiota, Network Pharmacology
Abstract

BACKGROUND: Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional "one-drug-one-target-one-disease" process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution.

RESULTS: We construct a disease-centric signed microbe-microbe interaction network using curated microbe metabolite information and their effects on host. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of effect of microbes on human health and diseases. With a survey on the druggable and evolutionary space of microbe proteins, we find that 8-10% of them can be targeted by existing drugs or drug-like chemicals and that 25% of them have homologs to human proteins. We demonstrate that drugs for diabetes can be the lead compounds for development of microbiota-targeted therapeutics. We further show that the potential drug targets that specifically exist in pathogenic microbes are periplasmic and cellular outer membrane proteins.

CONCLUSION: The systematic studies of the polypharmacological landscape of the microbiome network may open a new avenue for the small-molecule drug discovery of the microbiome. We believe that the application of systematic method on the polypharmacological investigation could lead to the discovery of novel drug therapies.

DOI10.1186/s12859-022-04941-2
Alternate JournalBMC Bioinformatics
PubMed ID36175827
PubMed Central IDPMC9523894
Grant ListR01 AG057555 / AG / NIA NIH HHS / United States
R01 GM122845 / GM / NIGMS NIH HHS / United States
R01GM122845 / GM / NIGMS NIH HHS / United States
R01AD057555 / AG / NIA NIH HHS / United States