Evidence map›Paper›PMID 38826280›Full record

ArticlebioRxiv : the preprint server for biology2024

Rationally Minimizing Natural Product Libraries Using Mass Spectrometry.

Monica Ness, Thilini Peramuna, Karen L Wendt, Jennifer E Collins, Jarrod B King, Raphaella Paes, Natalia Mojica Santos, Crystal Okeke, Cameron R Miller, Debopam Chakrabarti and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Monica NessDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Thilini PeramunaDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Karen L WendtDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Jennifer E CollinsBurnett School of Biomedical Sciences, University of Central Florida, Orlando, Florida, 32826, United States.
Jarrod B KingDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Raphaella PaesBurnett School of Biomedical Sciences, University of Central Florida, Orlando, Florida, 32826, United States.
Natalia Mojica SantosBurnett School of Biomedical Sciences, University of Central Florida, Orlando, Florida, 32826, United States.
Crystal OkekeDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Cameron R MillerDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Debopam ChakrabartiBurnett School of Biomedical Sciences, University of Central Florida, Orlando, Florida, 32826, United States.
Robert H CichewiczDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Laura-Isobel McCallDepartment of Chemistry and Biochemistry, San Diego State University, San Diego, California, 92182, United States.

Funding

Novel Antimalarials from FungiR01AI154777 · NIAID · UNIVERSITY OF CENTRAL FLORIDA · PI CHAKRABARTI, DEBOPAM, CICHEWICZ, ROBERT HENRY · 2020 to 2024
$3.8M
An LCMS-guided bioanalytical approach for rational natural product library design and optimizationR01GM145649 · NIGMS · UNIVERSITY OF OKLAHOMA · PI CICHEWICZ, ROBERT HENRY, MCCALL, LAURA-ISOBEL · 2022 to 2025
$1.2M
NIAID NIH HHS R01 AI154777NIGMS NIH HHS R01 GM145649
6 · The paper itself

Abstract

Natural product libraries are crucial to drug development, but large libraries drastically increase the time and cost during initial high throughput screens. Here, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce library size, with minimal bioactive loss. This method offers a broadly applicable strategy for accelerated drug discovery with cost reductions, which enable implementation in resource-limited settings.

Identifiers

PMID38826280
PMCPMC11142144

What Socratic holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.