دورية أكاديمية
High-throughput functional annotation of natural products by integrated activity profiling.
| العنوان: | High-throughput functional annotation of natural products by integrated activity profiling. |
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| المؤلفون: | Hight SK; Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390., Clark TN; Department of Chemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada., Kurita KL; Department of Chemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada., McMillan EA; Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390., Bray W; Department of Chemistry, University of California Santa Cruz, Santa Cruz, CA 95064., Shaikh AF; Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390., Khadilkar A; Department of Chemistry, University of California Santa Cruz, Santa Cruz, CA 95064., Haeckl FPJ; Department of Chemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada., Carnevale-Neto F; Department of Chemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada., La S; Department of Chemistry, University of California Santa Cruz, Santa Cruz, CA 95064., Lohith A; Department of Chemistry, University of California Santa Cruz, Santa Cruz, CA 95064., Vaden RM; Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390., Lee J; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390., Wei S; Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390., Lokey RS; Department of Chemistry, University of California Santa Cruz, Santa Cruz, CA 95064., White MA; Department of Cell Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390., Linington RG; Department of Chemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada., MacMillan JB; Department of Chemistry, University of California Santa Cruz, Santa Cruz, CA 95064.; Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390. |
| المصدر: | Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2022 Dec 06; Vol. 119 (49), pp. e2208458119. Date of Electronic Publication: 2022 Nov 30. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: National Academy of Sciences Country of Publication: United States NLM ID: 7505876 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1091-6490 (Electronic) Linking ISSN: 00278424 NLM ISO Abbreviation: Proc Natl Acad Sci U S A Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Washington, DC : National Academy of Sciences |
| مواضيع طبية MeSH: | Biological Products*/pharmacology, Metabolomics ; Benchmarking ; Gene Fusion ; Gene Library |
| مستخلص: | Determining mechanism of action (MOA) is one of the biggest challenges in natural products discovery. Here, we report a comprehensive platform that uses Similarity Network Fusion (SNF) to improve MOA predictions by integrating data from the cytological profiling high-content imaging platform and the gene expression platform Functional Signature Ontology, and pairs these data with untargeted metabolomics analysis for de novo bioactive compound discovery. The predictive value of the integrative approach was assessed using a library of target-annotated small molecules as benchmarks. Using Kolmogorov-Smirnov (KS) tests to compare in-class to out-of-class similarity, we found that SNF retains the ability to identify significant in-class similarity across a diverse set of target classes, and could find target classes not detectable in either platform alone. This confirmed that integration of expression-based and image-based phenotypes can accurately report on MOA. Furthermore, we integrated untargeted metabolomics of complex natural product fractions with the SNF network to map biological signatures to specific metabolites. Three examples are presented where SNF coupled with metabolomics was used to directly functionally characterize natural products and accelerate identification of bioactive metabolites, including the discovery of the azoxy-containing biaryl compounds parkamycins A and B. Our results support SNF integration of multiple phenotypic screening approaches along with untargeted metabolomics as a powerful approach for advancing natural products drug discovery. |
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| معلومات مُعتمدة: | R01 CA149833 United States CA NCI NIH HHS; U41 AT008718 United States AT NCCIH NIH HHS; R01 CA225960 United States CA NCI NIH HHS; T32 GM008203 United States GM NIGMS NIH HHS; T32 CA124334 United States CA NCI NIH HHS |
| فهرسة مساهمة: | Keywords: metabolomics; natural products; pharmacology |
| المشرفين على المادة: | 0 (Biological Products) |
| تواريخ الأحداث: | Date Created: 20221130 Date Completed: 20221202 Latest Revision: 20240409 |
| رمز التحديث: | 20240409 |
| مُعرف محوري في PubMed: | PMC9894231 |
| DOI: | 10.1073/pnas.2208458119 |
| PMID: | 36449542 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1091-6490 |
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| DOI: | 10.1073/pnas.2208458119 |