Summary of Study ST003160

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001965. The data can be accessed directly via it's Project DOI: 10.21228/M8QQ8P This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Study ID	ST003160
Study Title	New class of heterospirocyclic compounds present strong and rapid activity against artemisinin- and multidrug-resistant P. falciparum parasites
Study Summary	Malaria remains a significant health burden and a leading contributor to global mortality rates. Increasing drug resistance creates an urgent demand for novel treatment options. We have synthesised a new class of heterospirocyclic compounds with novel chemical connectivities. Compounds 25 and 26 display antimalarial activity within 24 h and have similar potency against a panel of drug-resistant strains of Plasmodium falciparum, the most virulent of human malaria parasites, including parasites resistant to the frontline artemisinin antimalarials. C25 and C26 do not induce major toxicity in kidney- and hepatic-derived human cell lines, highlighting their specificity. Untargeted metabolomics analysis of P. falciparum infected red blood cells revealed that the mechanism of action of C25 involves disruption of the pyrimidine biosynthesis pathway and haemoglobin catabolism. These heterospirocyclic compounds represent a promising opportunity for antimalarial drug development and could prove relevant against drug resistant malaria.
Institute	Monash University
Last Name	Giannangelo
First Name	Carlo
Address	381 Royal Parade, Parkville, Victoria, 3052, Australia
Email	carlo.giannangelo@monash.edu
Phone	99039282
Submit Date	2024-04-06
Raw Data Available	Yes
Raw Data File Type(s)	raw(Thermo)
Analysis Type Detail	LC-MS
Release Date	2024-04-29
Release Version	1

Select appropriate tab below to view additional metadata details:

Combined analysis:

Analysis ID	AN005184	AN005185
Analysis type	MS	MS
Chromatography type	HILIC	HILIC
Chromatography system	Thermo Dionex Ultimate 3000 RS	Thermo Dionex Ultimate 3000 RS
Column	Merck SeQuant ZIC-HILIC (150 x 4.6mm,5um)	Merck SeQuant ZIC-HILIC (150 x 4.6mm,5um)
MS Type	ESI	ESI
MS instrument type	Orbitrap	Orbitrap
MS instrument name	Thermo Q Exactive Orbitrap	Thermo Q Exactive Orbitrap
Ion Mode	POSITIVE	NEGATIVE
Units	Peak height	Peak height

MS:

MS ID:	MS004917
Analysis ID:	AN005184
Instrument Name:	Thermo Q Exactive Orbitrap
Instrument Type:	Orbitrap
MS Type:	ESI
MS Comments:	Liquid chromatography-mass spectrometry (LC-MS) data was acquired on a Q-Exactive Orbitrap mass spectrometer (Thermo Scientific) coupled with high-performance liquid chromatography system (HPLC, Dionex Ultimate 3000 RS, Thermo Scientific) as described previously (Creek et al. 2016). Samples within the LC-MS batch were sorted according to blocks of replicates and randomized. To facilitate metabolite identification, approximately 350 authentic metabolite standards were analysed prior to the LC-MS batch and their peaks and retention time manually checked using the MZmine software. Pooled biological quality control samples and extraction solvent blanks were analysed periodically throughout the batch to monitor LC-MS signal reproducibility and aid downstream metabolite identification procedures. Raw LC-MS metabolomics data were analysed using the open source software, IDEOM (http://mzmatch.sourceforge.net/ideom.php). Briefly, the IDEOM workflow uses msconvert to convert raw files to mzXML format, XCMS (Centwave) to pick LC-MS peak signals and MZmatch for alignment and annotation of related metabolite peaks. Default IDEOM parameters were used to eliminate unwanted noise and artefact peaks. Confident metabolite identification was made by matching accurate masses to retention time of the ~350 authentic standards. When these authentic standards were unavailable, putative metabolite identification used accurate mass and predicted retention times. Metabolite abundance was represented by LC-MS peak height.
Ion Mode:	POSITIVE

MS ID:	MS004918
Analysis ID:	AN005185
Instrument Name:	Thermo Q Exactive Orbitrap
Instrument Type:	Orbitrap
MS Type:	ESI
MS Comments:	Liquid chromatography-mass spectrometry (LC-MS) data was acquired on a Q-Exactive Orbitrap mass spectrometer (Thermo Scientific) coupled with high-performance liquid chromatography system (HPLC, Dionex Ultimate 3000 RS, Thermo Scientific) as described previously (Creek et al. 2016). Samples within the LC-MS batch were sorted according to blocks of replicates and randomized. To facilitate metabolite identification, approximately 350 authentic metabolite standards were analysed prior to the LC-MS batch and their peaks and retention time manually checked using the MZmine software. Pooled biological quality control samples and extraction solvent blanks were analysed periodically throughout the batch to monitor LC-MS signal reproducibility and aid downstream metabolite identification procedures. Raw LC-MS metabolomics data were analysed using the open source software, IDEOM (http://mzmatch.sourceforge.net/ideom.php). Briefly, the IDEOM workflow uses msconvert to convert raw files to mzXML format, XCMS (Centwave) to pick LC-MS peak signals and MZmatch for alignment and annotation of related metabolite peaks. Default IDEOM parameters were used to eliminate unwanted noise and artefact peaks. Confident metabolite identification was made by matching accurate masses to retention time of the ~350 authentic standards. When these authentic standards were unavailable, putative metabolite identification used accurate mass and predicted retention times. Metabolite abundance was represented by LC-MS peak height.
Ion Mode:	NEGATIVE