Title | Small molecule modulation of microbiota: a systems pharmacology perspective. |
Publication Type | Journal Article |
Year of Publication | 2022 |
Authors | Liu Q, Lee B, Xie L |
Journal | BMC Bioinformatics |
Volume | 23 |
Issue | Suppl 3 |
Pagination | 403 |
Date Published | 2022 Sep 29 |
ISSN | 1471-2105 |
Keywords | Drug 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. |
DOI | 10.1186/s12859-022-04941-2 |
Alternate Journal | BMC Bioinformatics |
PubMed ID | 36175827 |
PubMed Central ID | PMC9523894 |
Grant List | R01 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 |