The author would like to acknowledge the initial support of Dr Cesar Ramirez during initial method developments.

1. Sample preparation
<ol>
	<li>Store the fentanyl analog screening kit at -20 &#176;C once they have been received. Resuspend each sample to a final concentration of 400 &#181;g/mL by the addition of 500 &#181;L of pure LC/MS grade methanol.</li>
	<li>Mix using a plate mixer or vortexer at 400 rpm for 1 h or vortex at medium speed for 15 min. After resuspension store the vials at -20 &#176;C.</li>
	<li>Dilute each standard to a final concentration of 1 ng/mL using pure LC/MS grade methanol.</li>
	<li>Group the standards into groups, such that each group does not contain any isomeric standards. See Supplementary Table 1 for the breakdown of the 14 groups of fentanyl standards.</li>
</ol>
2. HPLC mobile phases preparation
<ol>
	<li>Prepare mobile phase A (MPA) using 5 mM/L ammonium formate (NH4HCO2) in H2O with 0.05% formic acid (85%).
	<ol>
		<li>Weigh out 0.078 g of NH4HCO2, pour into a 250 mL volumetric flask and fill with water to about 2/3rd. Swirl to mix well.</li>
		<li>Once fully dissolved, add 0.125 mL of formic acid (85%). Fill with water to the fill line (250 mL) and mix.</li>
	</ol>
	</li>
	<li>Prepare mobile phase B (MPB) using 0.05% formic acid in a 1:1 methanol acetonitrile mixture.
	<ol>
		<li>Pour 125 mL of acetonitrile into a volumetric flask and add methanol until it reaches the fill line.</li>
		<li>Swirl to mix well. Add 0.125 mL of 0.05% formic acid to the flask and mix to homogenize.</li>
	</ol>
	</li>
</ol>
3. HPLC method development
<ol>
	<li>Open the LC software to the home screen. In the sample table, located at the center of the window, create a new protocol.
	<ol>
		<li>Annotate the vial column with the sample location. Annotate the sample ID column using the format YYYYMMDD_NAME (representative descriptor). Annotate the volume column with the desired the injection volume (15 &#181;L).</li>
	</ol>
	</li>
	<li>Annotate the data path column with the location where the data will be saved to.</li>
	<li>HPLC method input
	<ol>
		<li>Select New from the bar in the sample table located in the middle of the screen. Under the separation method, select the Drop-down Arrow and click New Method in the pop-up window.</li>
		<li>A new window will pop up labeled separation method, here edit the acquisition time or the instrument control framework (ICF) system method.</li>
		<li>Double click the Edit Method button for the ICF system to open up the popup to edit the binary gradient, as seen in Figure 1.</li>
		<li>Under the binary gradient tab, a visual representation of the gradient is on the left and the breakdown of the gradient is on the right, set the time stamps, the flow rate and the MPA and MPB concentrations.</li>
		<li>Ensure the stop time is set to 18 min, the flow rate to 0.400 mL/min, and pressure limit min and max at 0 psi and 6000 psi.</li>
		<li>Set the time stamp concentrations as following: 
		At 0.00 min, set B concentration to 20.0. 
		At 1.50 min, set B concentration to 25.0. 
		At 3.00 min, set B concentration to 27.0. 
		At 6.00 min, set B concentration to 27.0. 
		At 6.50 min, set B concentration to 30.0. 
		At 7.00 min, set B concentration to 95.0. 
		At 16.00 min, set B concentration to 95.0. 
		At 16.50 min, set B concentration to 20.0.</li>
	</ol>
	</li>
</ol>
4. Initialization of the HPLC
<ol>
	<li>In the HPLC column section, insert the LC column (monolithic C18 HPLC column 100 mm x 4.6 mm) and column guards (guard column 5 mm x 4.6 mm). Pay attention to the minimum and maximum column pressure.</li>
	<li>Run a sample blank (same buffer solution) to test for any leaks and create a baseline. Look for leaks. Leaks could be observed by column pressure fluctuations. If there are leaks determine where they might be coming from and tighten the connections.</li>
	<li>Run a sample blank (same buffer solution) using the desired LC program to precondition the column.</li>
</ol>
5. timsTOF MS/MS method development
<ol>
	<li>Open the timsControl application. On the left side of the window are the MS and TIMS Settings.
	<ol>
		<li>Under MS settings set the scan beginning and ending to 50 m/z and 1800 m/z, respectively. Select positive mode for the ion polarity and select parallel accumulation-serial fragmentation for the scan mode.</li>
		<li>Under TIMS Settings set the Mode to custom, 1/K0 start to 0.40 Vs/cm2, 1/K0 end to 1.85 Vs/cm2, ramp time set to 150.0 ms, and MS averaging set to 1.</li>
	</ol>
	</li>
	<li>In the lower selection of tabs under Source perform the following changes in the two setting boxes.
	<ol>
		<li>In the source, set the end plate offset to 500 V, capillary to 4500 V, nebulizer to 3.0 bar, dry gas to 10.0 L/min, and dry temp to 200 &#176;C.</li>
		<li>In the syringe pump settings, ensure the syringe is Hamilton 1 mL, active is enabled, and the flow rate set to 80.0 &#181;L/h.</li>
	</ol>
	</li>
	<li>In the Tune tab perform the following changes in the setting tabs for General, Processing, and TIMS.
	<ol>
		<li>Under general settings tab, setup the following sections: transfer, collision cell, quadrupole, focus pre TOF, and detection.
		<ol>
			<li>Under the transfer settings, set the deflection 1 delta to 70.0 V, funnel 1 RF to 341.0 Vpp, CID energy to 0.0 eV, funnel 2 RF to 300.0 Vpp, multipole RF to 300.0 Vpp.</li>
			<li>Under the collision cell settings, ensure that the collision energy is set to 6.0 eV and the collision RF to 1200.0 Vpp.</li>
			<li>Under the quadrupole settings, ensure ion energy is set to 6.0 eV and low mass to 250.00 m/z.</li>
			<li>Under the focus pre TOF settings, set transfer time to 75.0 &#181;s and pre-pulse storage to 5.0 &#181;s.</li>
		</ol>
		</li>
		<li>Under the processing settings tab, set up the following sections: mass spectra peak detection and mobility peak detection.
		<ol>
			<li>In the mass spectra peak settings, unselect sum of intensities (area) and set the absolute threshold to 667.</li>
		</ol>
		</li>
		<li>Under the TIMS tab, set up the following sections: offsets, ion change control, and advanced parameters.
		<ol>
			<li>Under the offsets setting set &#916;t1 to -20.0 V, &#916;t2 to -100.0 V, &#916;t3 to 40.0 V, &#916;t4 to 80.0 V, &#916;t5 to 0.0 V, &#916;t6 to 120.0, and collision cell in to 250.0 V.</li>
			<li>Under the ion charge control settings, click the box to enable and set the target intensity to 5.00 M.</li>
			<li>Under the advanced parameters, enable the lock accumulation to mobility range.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>In the MS/MS tab set the Scan mode to parallel accumulation-serial fragmentation and set up the following sections: precursor ions, scheduling, active exclusion, collision energy settings, isolation width settings, and TIMS stepping.
	<ol>
		<li>Under precursor ions, set the number of parallel accumulation-serial fragmentation ramps to 8, charge minimum to 1, and charge maximum to 5.</li>
		<li>Under scheduling settings, enable the precursor repetitions. Under active exclusion, check the box to enable and set the release to 0.40 min after.</li>
		<li>Do not adjust the collision energy settings and isolation width settings. Click the TIMS Stepping Box to enable.</li>
	</ol>
	</li>
</ol>
6. Mobility and mass calibration
<ol>
	<li>Perform calibration for both m/z and mobility domains. Under the m/z calibration settings, select one of the preloaded tuning mix profiles in the reference list box that appear in the drop-down menu.</li>
	<li>To calibrate, load the syringe for the TOF with a tuning mix solution. On the right side of the window, use the settings titled calibration mode for the various calibration types to be set to achieve the highest score.</li>
	<li>Ensure that the score is as close to 100% as possible. Switch between linear, quadradic and enhanced quadratic to achieve the best score.</li>
	<li>Calibrate for mobility following steps 6.1-6.3 used for calibrating m/z.</li>
	<li>Once calibrated, save the MS method by selecting the Method tab on the top bar. In the drop-down menu, select Save As to generate a new MS method file.</li>
</ol>
7. Creating data independent acquisition (dia) parallel accumulation-serial fragmentation method
<ol>
	<li>Once a data set has been collected in data dependent acquisition (dda) parallel accumulation-serial fragmentation, run the experiments in dia. Open the ion mobility software application and load the dda method saved in step 6.5.</li>
	<li>Leave all the settings the same expect for the MS setting, change this from parallel accumulation-serial fragmentation to dia- parallel accumulation-serial fragmentation.</li>
	<li>On the bottom of the panel, select the MSMS tab and then click on Window Editor to open the dia window popup shown in Figure 2.</li>
	<li>Load the previously saved dda data set (.m file) using the open analysis button located at the top of the popup window.</li>
	<li>A heat map appears at the bottom left displaying windows with a polygon of windows running diagonally across the graph. Click and drag to resize the polygon so that it fits the data in the heat map (corners are selectable by double clicking on the lateral lines a point will appear that can be dragged and resized).</li>
	<li>To the right of the windows are the window settings. Set the mass width (50 is go to) and set the horizontal overlap, both in Da.</li>
	<li>Set the number of mobility windows in per mass width and the vertical overlap.</li>
	<li>Click Calculate Windows on the bottom right of the popup to see the windows displayed with the new settings. Once suitable, click Apply dia-PASEF Windows to Method. This will close the popup bringing it back to the home screen.</li>
</ol>
8. HPLC ion mobility TOF data processing
<ol>
	<li>Open the data analysis software. At the top left corner click on the File tab and select Open from the drop down. In the new files window select the files of choice and click Open.</li>
	<li>Check the calibration. Right click on the file name under the analysis box and select Properties. A window labeled file name_analysis properties will appear. Select Calibration Status.</li>
	<li>From the drop-down box, select Instrument Calibration for the Mass Spectrometer. Confirm that the error is no greater than 1 &#181;g/mL. Select Initial Mobility Calibration and confirm that the error is no greater than 1 &#181;g/mL.</li>
	<li>Prepare a chromatogram in the data analysis software as described below.
	<ol>
		<li>Right click on Chromatogram under the file name, select Edit Chromatogram. In type, click the drop-down box and select Extracted Ion Chromatogram.</li>
		<li>Under filter, select All MS and with scan mode select All. This is to view the peaks for the molecule of interest rather than only its fragments.</li>
		<li>Below this, look for the two filter options for molecule selection: masses or formula highlighted in blue.</li>
		<li>If using masses to extract an ion, insert the theoretical m/z of the molecule of interest. For this case select (mass for representative result) m/z.</li>
		<li>If using formula to extract an ion, insert the formula for the molecule as well as the ion forms of interest for the chromatogram. In this case, select the protonated ion, [M+H]+.</li>
		<li>Set the polarity to positive mode.</li>
	</ol>
	</li>
	<li>Mass spectrum
	<ol>
		<li>Right click at the baseline of the peak of the compound and drag to the other edge of the peak. This will create a mass spectrum of fragments within that retention time.</li>
	</ol>
	</li>
	<li>Generation of Mobilogram
	<ol>
		<li>Right click on the left tab titled mobilogram and select Edit Mobilogram. A window titled edit mobilogram traces will appear. Follow steps 8.4.2-8.4.7 for editing the chromatogram.</li>
		<li>In the retention time input, add the retention time range of the peak of interest.</li>
		<li>Once the parameters are selected, click Add followed by Ok at the top right of the edit mobilogram traces window.</li>
		<li>After a short amount of time, the software will process the desired selections and output a chromatogram. Repeat steps 8.6.1-8.6.3 for all ions in the mixture.</li>
		<li>Generating the compound spectra
		<ol>
			<li>At the bottom of the spectrum view window, select Profile MS and Fragment MS. This will allow to include ions from full scan and PASEF.</li>
			<li>At spectrum view, right click and select Copy Compound Spectra. With the spectrum data that appears at the right, find more information on the compound such as resolution resolving power, intensity, and signal to noise ratio (S/N).</li>
		</ol>
		</li>
		<li>Data processing
		<ol>
			<li>To process the data, manually integrate the chromatogram and mobility peaks to yield important information on the molecule of interest.</li>
			<li>Right click Find and select Integrate only chromatogram or mobilogram. Left click and drag to highlight the desired peak. The information will be displayed which includes retention time, area, S/N, and mobility.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

Harvesting the Orthogonality of LC and TIMS&#45;TOF MS&#47;MS to Screen Fentanyl Analogs

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K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+fentanyl+analogs+and+novel+synthetic+opioids+in+blood,+serum/plasma,+and+urine+in+forensic+casework.">Analysis of fentanyl analogs and novel synthetic opioids in blood, serum/plasma, and urine in forensic casework.</a> Drug Testing and Analysis. 10 (9), 1358-1367 (2018).</li><li>Seither, J., Reidy, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Confirmation+of+Carfentanil,+U-47700+and+Other+Synthetic+Opioids+in+a+Human+Performance+Case+by+LC-MS-MS.">Confirmation of Carfentanil, U-47700 and Other Synthetic Opioids in a Human Performance Case by LC-MS-MS.</a> Journal of Analytical Toxicology. 41 (6), 493-497 (2017).</li><li>Strayer, K. E., Antonides, H. M., Juhascik, M. P., Daniulaityte, R., Sizemore, I. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LC-MS/MS-Based+Method+for+the+Multiplex+Detection+of+24+Fentanyl+Analogues+and+Metabolites+in+Whole+Blood+at+Sub+ng+mL(-1)+Concentrations.">LC-MS/MS-Based Method for the Multiplex Detection of 24 Fentanyl Analogues and Metabolites in Whole Blood at Sub ng mL(-1) Concentrations.</a> ACS Omega. 3 (-1), 514-523 (2018).</li><li>Kahl, J. H., Gonyea, J., Humphrey, S. M., Hime, G. W., Boland, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Analysis+of+Fentanyl+and+Six+Fentanyl+Analogs+in+Postmortem+Specimens+by+UHPLC-MS-MS.">Quantitative Analysis of Fentanyl and Six Fentanyl Analogs in Postmortem Specimens by UHPLC-MS-MS.</a> Journal of Analytical Toxicology. 42 (8), 570-580 (2018).</li><li>Fogarty, M. F., Papsun, D. M., Logan, B. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+Fentanyl+and+18+Novel+Fentanyl+Analogs+and+Metabolites+by+LC-MS-MS,+and+report+of+Fatalities+Associated+with+Methoxyacetylfentanyl+and+Cyclopropylfentanyl.">Analysis of Fentanyl and 18 Novel Fentanyl Analogs and Metabolites by LC-MS-MS, and report of Fatalities Associated with Methoxyacetylfentanyl and Cyclopropylfentanyl.</a> Journal of Analytical Toxicology. 42 (9), 592-604 (2018).</li><li>Lurie, I. S., Berrier, A. L., Casale, J. F., Iio, R., Bozenko, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Profiling+of+illicit+fentanyl+using+UHPLC-MS/MS.">Profiling of illicit fentanyl using UHPLC-MS/MS.</a> Forensic Science International. 220 (1-3), 191-196 (2012).</li><li>Krajewski, L. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+the+fentanyl+analog+screening+kit+toward+the+identification+of+emerging+synthetic+opioids+in+human+plasma+and+urine+by+LC-QTOF.">Application of the fentanyl analog screening kit toward the identification of emerging synthetic opioids in human plasma and urine by LC-QTOF.</a> Toxicology Letters. 320, 87-94 (2020).</li><li>Pirok, B. W. J., Stoll, D. R., Schoenmakers, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+Developments+in+Two-Dimensional+Liquid+Chromatography:+Fundamental+Improvements+for+Practical+Applications.">Recent Developments in Two-Dimensional Liquid Chromatography: Fundamental Improvements for Practical Applications.</a> Analytical Chemistry. 91 (1), 240-263 (2018).</li><li>Keller, T., Keller, A., Tutsch-Bauer, E., Monticelli, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+ion+mobility+spectrometry+in+cases+of+forensic+interest.">Application of ion mobility spectrometry in cases of forensic interest.</a> Forensic Science International. 161 (2-3), 130-140 (2006).</li><li>Klingberg, J., Keen, B., Cawley, A., Pasin, D., Fu, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Developments+in+high-resolution+mass+spectrometric+analyses+of+new+psychoactive+substances.">Developments in high-resolution mass spectrometric analyses of new psychoactive substances.</a> Archives of Toxicology. 96 (4), 949-967 (2022).</li><li>Fleming, S. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+U-47700,+a+Novel+Synthetic+Opioid,+in+Human+Urine+by+LC-MS-MS+and+LC-QToF.">Analysis of U-47700, a Novel Synthetic Opioid, in Human Urine by LC-MS-MS and LC-QToF.</a> Journal of Analytical Toxicology. 41 (3), 173-180 (2017).</li><li>Guale, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validation+of+LC-TOF-MS+screening+for+drugs,+metabolites,+and+collateral+compounds+in+forensic+toxicology+specimens.">Validation of LC-TOF-MS screening for drugs, metabolites, and collateral compounds in forensic toxicology specimens.</a> Journal of Analytical Toxicology. 37 (1), 17-24 (2013).</li><li>Palmquist, K. B., Swortwood, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Data-independent+screening+method+for+14+fentanyl+analogs+in+whole+blood+and+oral+fluid+using+LC-QTOF-MS.">Data-independent screening method for 14 fentanyl analogs in whole blood and oral fluid using LC-QTOF-MS.</a> Forensic Science International. 297, 189-197 (2019).</li><li>Adams, K. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+isomeric+opioids+in+urine+using+LC-TIMS-TOF+MS.">Analysis of isomeric opioids in urine using LC-TIMS-TOF MS.</a> Talanta. 183, 177-183 (2018).</li></ol>

Matthew Willetts and Melvin A. Park are employees of Bruker Daltonics Inc, the manufacturer of the timsTOF Pro2 commercial instrument. All the other authors declare no conflicts of interest.

The analytical separation of biological samples containing high isomeric content can be analytically challenging. In this paper, the method described aims to characterize 29 isomer sets, for a total of 185 analogs from a 250 opioid standard kit. During the test group preparation, it is important to ensure that there are no two analogs with m/z that cannot be experimentally distinguished. The data described here uses standards not from a human-based matrix, if this method is to be used in a field experiment; additional tr...

Fentanyl and its analogs are the major contributors to fatal and nonfatal overdoses in the United States1,2. The Center for Disease Control and Prevention (CDC) reported that the number of synthetic opioid-related overdose deaths from 2013 through 2021 was over 258,000. In 2021 alone, over 68,000 overdose deaths could be attributed to synthetic opioids, totaling 82% of all overdose-related deaths in the nation3. Since 2013, hundreds of fentanyl analogs have been identified, with varying potency4. With the emergence of illicitly manufactured fentanyl analogs, the schedule II synthetic opioid itself remains the most popular synthetic opioid available in the United States3. According to the Center for Forensic Science Research and Education (CFSRE), the top reported fentanyl analog in 2022 was fluorofentanyl, with additional non-fentanyl related synthetic opioids now being introduced into the volatile drug market supply at a rapid rate5.
Due to the overwhelming volume of fentanyl and fentanyl-related analogs circulating in the drug market, the DEA has implemented a fentanyl signature profiling program entitled Operation Death Dragon, in order to track the methodology used to synthesize these compounds with hopes of linking drug seizures back to their origin6. In 2018, 94% of the drug seizures were identified as being synthesized by the Janssen method, while the remaining 6% were synthesized with the Siegfried method6. The primary difference between the two methods is the presence of the fentanyl analog, benzyl fentanyl, detected as an impurity in the Janssen method, while the presence of despropionyl fentanyl (4-ANPP), a metabolite/precursor of fentanyl, is an impurity detected when synthesizing with the Siegfried method7.
The use of gas and liquid chromatography in tandem with mass spectrometry (GC-MS and LC-MS, respectively) for the targeted screening and quantification of synthetic opioids is regularly implemented in toxicology laboratories. GC-MS has been considered the gold standard for the detection of drugs of abuse in biological specimens. Access to publicly available mass spectral libraries8 and instrumentation marketed as plug and play systems9 are some reasons why GC-MS has remained an integral part in laboratories for both comprehensive screening as well as targeted quantification9,10. However, current GC-MS quantification methods in the literature tend to have a limited scope of analytes11 and quickly become outdated and not applicable to current casework. More importantly, the limits of detection and quantification are not comparable to LC-MS methods (&#60; 1 ng/mL)12, therefore increasing the potential for false-negative results. One such comparison between GC-MS and LC-MS which looked at postmortem specimens, noted that out of 134 positively identified cases of carfentanil, one of the most potent synthetic opioids to date, 104 of those cases screened negative for carfentanil utilizing GC-MS13. In drug analysis laboratories, GC-MS is more frequently used and amendable for synthetic opioids due to the high concentration of the analyzed samples. Yet, GC-MS is still utilized in conjunction with additional techniques such as Fourier transform-infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) for the confirmation of these compounds14. The application of GC-MS to the analysis of biological specimens in forensic toxicology requires sample preparation methods that include the extraction of these compounds using either liquid-liquid extraction (LLE) or solid-phase extraction (SPE)15. LLE can be conducted with a variety of solvents, however in a high-production lab, LLE may not be cost-efficient or timely. LLE consumes large quantities of solvents as well as sample volume, while the alternative, SPE, can be automated and requires minimum sample volume16. A recent GC-MS study reported the separation of 20 different isomeric fentanyl analogs using three separate GC thermal programs17. While baseline separation among isomers was successful, the applicability of this method to relevant forensic casework and workflows is limited.
LC-MS has gained popularity in forensic testing, especially due to the limitations of GC-MS when it comes to non-volatile and heat-sensitive compounds18,19. LC-MS screening utilizing triple quadrupoles (QQQ) and ion trap instrumentation have been successful in detecting synthetic opioids at low concentrations (&#60;1 ng/mL)12,20,21,22,23,24. Typically, these LC-MS methods are used as secondary confirmation methods to complement immunoassay and/or GC-MS results. In 2017, Shoff et al. at the Miami-Dade County medical examiner department (MDME) toxicology laboratory developed a comprehensive screening method for 44 opioid-related compounds using ultra high pressure liquid chromatography (UHPLC)-ion trap-MSn 13. Similar to targeted MRM methods, this ion trap method utilized a scheduled precursor list (SPL) containing retention times, precursor target ions, as well as primary daughter ions for MS3 spectral fragmentation when possible. What separates this screening method from methods developed on triple quadrupoles and linear quadrupole ion traps is the additional detail provided in the spectral data. What this screening method cannot provide is quantitative analysis, which is rarely developed on ion trap instrumentation, as well as the identification of unknowns13. LC-QQQ methods for synthetic opioids can simultaneously screen and quantify a predefined target list. The use of multiple reaction monitoring (MRM) transitions for the identification and quantification of compounds is a trusted data acquisition technique and is the most common technique utilized in the literature for the detection of synthetic opioids12,20.&#160;Reported linear ranges for the quantification of an array of synthetic opioids span from 0.01-100 ng/mL, with more potent synthetic opioids, such as carfentanil, detected at the sub-ng/mL range11,24,25,26,27.
The separation of isomeric synthetic opioids has been addressed in LC-MS methods. One such method separated 174 isomeric fentanyl analogs within a 16 min runtime using a biphenyl column28. In addition, fluctuations in LC-dependent parameters such as column efficiency, mobile phase pH, and pressure changes create retention time shifts that must be accounted for in targeted assays with consistent monitoring and larger collection windows (&#62;0.4 min), which may result in potential overlap of these once resolved isomers. Additional chromatographic techniques for the separation of isomers have been explored, including the use of 2-dimensional liquid chromatography (2D-LC)29; and while this technique does have the ability to provide orthogonal separation of compounds, the disadvantages outweigh the advantages including excessive run-times, cost, difficulty in method development, and usefulness compared to alternative separations30.
High resolution mass spectrometry (HRMS) is becoming increasingly reliable for the identification of synthetic opioids. Several instrumentation companies have marketed targeted methods developed for the purposes of identifying a broad range of synthetic opioids in complex biological matrices19,28,31. These methods, unlike previously discussed methods, can store analytical data for retroactive analysis. Thus, specimens that were previously analyzed with undetermined results can be revisited later for discovery of newly identified compounds. What separates HRMS from QQQ is accurate mass identification. While both MS techniques can accurately quantitate at low concentrations, HRMS has been proven to be more effective for initial screening and discovery of unknown compounds32,33,34. HRMS, specifically with time-of-flight (TOF) MS analyzers, has been at the forefront of NPS discovery, allowing forensic testing laboratories to deliver time-sensitive data on new compounds to both law enforcement and the scientific community to scale the spread of some of these compounds while increasing awareness and education33. The use of TOF for the detection of drugs of abuse has become extremely comprehensive, with methods containing an upwards of 600 compounds separated within a 10 min chromatographic program. Previous studies have been reported the advantages of trapped ion mobility spectroscopy (TIMS) coupled to TOF for detection and separation of isomeric opioids35.
Taking advantage of the orthogonality between liquid chromatography, trapped ion mobility spectrometry and mass spectrometry, the presented method provides a broad characterization of fentanyl analogs based on the retention time, isotopic pattern, mobility, and fragmentation pattern.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Ammonium formate for HPLC</td>
			<td>Fluka</td>
			<td>17843-50G</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf&#160;Snap-Cap Microcentrifuge Safe-Lock Tubes</td>
			<td>Fisher</td>
			<td>05-402-25</td>
			<td></td>
		</tr>
		<tr>
			<td>ESI-L Low Concentration Tuning mix</td>
			<td>Agilent</td>
			<td>G1969-85000</td>
			<td></td>
		</tr>
		<tr>
			<td>Fentanyl Analog Screening (FAS) Kit&#160;</td>
			<td>Cayman Chemical</td>
			<td>9003237, 9003286, 9003380, 9003381</td>
			<td>kit of 250 snthetic opioids, 210 fentanyl analogs, broken up into one kit and emergent panel versions 1-4</td>
		</tr>
		<tr>
			<td>Formic acid Optima LC/MS</td>
			<td>Fisher</td>
			<td>A117-50</td>
			<td></td>
		</tr>
		<tr>
			<td>Onyx guard column (5 x 4.6 mm)&#160;</td>
			<td>Phenomenex</td>
			<td>CHO-7649</td>
			<td>guard column for C18 columns</td>
		</tr>
		<tr>
			<td>Onyx monolithic C18 HPLC column (100 x 4.6 mm)</td>
			<td>Phenomenex</td>
			<td>CHO-7643</td>
			<td>reverse phase C18 LC column</td>
		</tr>
		<tr>
			<td>Optima grade acetonitrile&#160;</td>
			<td>Fisher</td>
			<td>A996-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Optima grade methanol</td>
			<td>Fisher</td>
			<td>A454-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Optima grade water</td>
			<td>Fisher</td>
			<td>W7-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette</td>
			<td>Fisher</td>
			<td>05-719-510</td>
			<td>kit of 1-10 &#181;L, 10-100 &#181;L, and 100-1000 &#181;L pipette</td>
		</tr>
		<tr>
			<td>Pipette tips 10&#181;L</td>
			<td>Fisher</td>
			<td>94060100</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 1000&#181;L</td>
			<td>Fisher</td>
			<td>94056710</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 200&#181;L</td>
			<td>Fisher</td>
			<td>94060310</td>
			<td></td>
		</tr>
		<tr>
			<td>Plate mixer</td>
			<td>IKA&#160;</td>
			<td>MS 3 D S1</td>
			<td>IKA MS 3 digtital</td>
		</tr>
		<tr>
			<td>Prominence LC-20 CE ultrafast liquid chromatograph</td>
			<td>Shimadzu, Japan</td>
			<td></td>
			<td>equiped with DGU-20A5, LC-20AD, SIL-20AC, CTO-20A, SPD-M20A, CBM-20A, SPD-20A</td>
		</tr>
		<tr>
			<td>timsTOF Pro</td>
			<td>Bruker Daltonics Inc., Billerica, MA</td>
			<td></td>
			<td>timsTOF instrument with PASEF&#160;</td>
		</tr>
	</tbody>
</table>

fentanyl analog screening using lc-tims-tof ms/ms

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its analogs are the major contributors to fatal and nonfatal overdoses in the United States. Most recent cases of fentanyl-related overdose are linked to illicitly manufactured fentanyl and its associated extreme potency. In the present work, we describe a high-throughput analytical protocol for the screening of fentanyl analogs. The use of complementary liquid chromatography, trapped ion mobility spectrometry, and tandem mass spectrometry allow for the separation and assignment of hundreds of fentanyl analogs from a single sample in a single scan. The described approach takes advantage of the recent development of data-dependent acquisition and data-independent acquisition using parallel accumulation in the mobility trap followed by sequential fragmentation using collision-induced dissociation. The fentanyl analogs are confidently assigned based on their retention time, mobility, and MS fragmentation pattern.

The fentanyl analog screening kit of 250 analogs standards were divided into 14 groups: 12 groups of 17 analogs and 2 groups of 16 analogs, to avoid m/z interferences. Each analog is further characterized by their m/z, retention time (RT), mobility (K), and MS/MS fragmentation pattern.
Examples of isomeric separations are shown in Figure 3 and Figure 4 for the C22H28N2O2 and...

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs 

A method for the screening of fentanyl analogs based on their retention time, mobility, and mass spectrometry fragmentation pattern.

Fentanyl Analog Screening using LC-TIMS-TOF MS/MS

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its ...

fentanyl-analog-screening-using-lc-tims-tof-msms

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Chemistry

1.8K Views.  Florida International University. A method for the screening of fentanyl analogs based on their retention time, mobility, and mass spectrometry fragmentation pattern.

Video: Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs 

A Guided Materials Screening Approach for Developing Quantitative Sol-gel Derived Protein Microarrays

Microarrays have found use in the development of high-throughput assays for new materials and discovery of small-molecule drug leads. Herein we describe a guided material screening approach to identify sol-gel based materials that are suitable for producing three-dimensional protein microarrays. The approach first identifies materials that can be printed as microarrays, narrows down the number of materials by identifying those that are compatible with a given enzyme assay, and then hones in on optimal materials based on retention of maximum enzyme activity. This approach is applied to develop microarrays suitable for two different enzyme assays, one using acetylcholinesterase and the other using a set of four key kinases involved in cancer. In each case, it was possible to produce microarrays that could be used for quantitative small-molecule screening assays and production of dose-dependent inhibitor response curves. Importantly, the ability to screen many materials produced information on the types of materials that best suited both microarray production and retention of enzyme activity. The materials data provide insight into basic material requirements necessary for tailoring optimal, high-density sol-gel derived microarrays.

A guided material screening approach to develop sol-gel derived protein doped microarrays using an emerging pin-printing method of fabrication is described. This methodology is demonstrated through the development of acetylcholinesterase and multikinase microarrays, which are used for cost-effective small-molecule screening.

Microarrays have found use in the development of high-throughput assays for new materials and discovery of small-molecule drug leads. Herein we describe a ...

Fluorescence-based Monitoring of PAD4 Activity via a Pro-fluorescence Substrate Analog

Post-translational modifications may lead to altered protein functional states by increasing the covalent variations on the side chains of many protein substrates. The histone tails represent one of the most heavily modified stretches within all human proteins. Peptidyl-arginine deiminase 4 (PAD4) has been shown to convert arginine residues into the non-genetically encoded citrulline residue. Few assays described to date have been operationally facile with satisfactory sensitivity. Thus, the lack of adequate assays has likely contributed to the absence of potent non-covalent PAD4 inhibitors. Herein a novel fluorescence-based assay that allows for the monitoring of PAD4 activity is described. A pro-fluorescent substrate analog was designed to link PAD4 enzymatic activity to fluorescence liberation upon the addition of the protease trypsin. It was shown that the assay is compatible with high-throughput screening conditions and has a strong signal-to-noise ratio. Furthermore, the assay can also be performed with crude cell lysates containing over-expressed PAD4.

PAD4 is an enzyme responsible for the conversion of peptidyl-arginine to peptidyl-citrulline. Dysregulation of PAD4 has been implicated in a number of human diseases. A facile and high-throughput compatible fluorescence based PAD4 assay is described.

Post-translational modifications may lead to altered protein functional states by increasing the covalent variations on the side chains of many protein ...

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that belongs to the Direct-Injection Mass Spectrometric (DIMS) technologies. These techniques allow the rapid determination of volatile organic compounds (VOCs), assuring high sensitivity and accuracy. In general, PTR-MS requires neither sample preparation nor sample destruction, allowing real time and non-invasive analysis of samples. PTR-MS are exploited in many fields, from environmental and atmospheric chemistry to medical and biological sciences. More recently, we developed a methodology based on coupling PTR-ToF-MS with an automated sampler and tailored data analysis tools, to increase the degree of automation and, consequently, to enhance the potential of the technique. This approach allowed us to monitor bioprocesses (e.g. enzymatic oxidation, alcoholic fermentation), to screen large sample sets (e.g. different origins, entire germoplasms) and to analyze several experimental modes (e.g. different concentrations of a given ingredient, different intensities of a specific technological parameter) in terms of VOC content. Here, we report the experimental protocols exemplifying different possible applications of our methodology: i.e. the detection of VOCs released during lactic acid fermentation of yogurt (on-line bioprocess monitoring), the monitoring of VOCs associated with different apple cultivars (large-scale screening), and the in vivo study of retronasal VOC release during coffee drinking (nosespace analysis).

Proton Transfer Reaction Time of Flight Mass Spectrometry allows high-sensitivity, rapid and non-invasive analysis of volatile organic compounds. To demonstrate its potential, we give three examples: lactic acid fermentation of yogurt (on-line bioprocess monitoring), different apple genotypes (large-scale screening), and retronasal space after drinking coffee (nosespace analysis).

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that ...

Preparation of Biopolymer Aerogels Using Green Solvents

Although the first reports on aerogels made by Kistler1 in the 1930s dealt with aerogels from both inorganic oxides (silica and others) and biopolymers (gelatin, agar, cellulose), only recently have biomasses been recognized as an abundant source of chemically diverse macromolecules for functional aerogel materials. Biopolymer aerogels (pectin, alginate, chitosan, cellulose, etc.) exhibit both specific inheritable functions of starting biopolymers and distinctive features of aerogels (80-99% porosity and specific surface up to 800 m2/g). This synergy of properties makes biopolymer aerogels promising candidates for a wide gamut of applications such as thermal insulation, tissue engineering and regenerative medicine, drug delivery systems, functional foods, catalysts, adsorbents and sensors. This work demonstrates the use of pressurized carbon dioxide (5 MPa) for the ionic cross linking of amidated pectin into hydrogels. Initially a biopolymer/salt dispersion is prepared in water. Under pressurized CO2 conditions, the pH of the biopolymer solution is lowered to 3 which releases the crosslinking cations from the salt to bind with the biopolymer yielding hydrogels. Solvent exchange to ethanol and further supercritical CO2 drying (10 - 12 MPa) yield aerogels. Obtained aerogels are ultra-porous with low density (as low as 0.02 g/cm3), high specific surface area (350 - 500 m2/g) and pore volume (3 - 7 cm3/g for pore sizes less than 150 nm).

A new way for the production of biopolymer-based aerogels by carbon dioxide (CO2) induced gelation is shown. The technique utilizes pressurized carbon dioxide (5 MPa) for the production of biopolymer hydrogels and supercritical CO2 (12 MPa) to convert gels into aerogels. The only solvents needed besides CO2 are water and ethanol.

Although the first reports on aerogels made by Kistler1 in the 1930s dealt with aerogels from both inorganic oxides (silica and others) and biopolymers ...

Integration of Miniaturized Solid Phase Extraction and LC-MS/MS Detection of 3-Nitrotyrosine in Human Urine for Clinical Applications

Free 3-nitrotyrosine (3-NT) has been extensively used as a possible biomarker for oxidative stress. Increased levels of 3-NT have been reported in a wide variety of pathological conditions. However, existing methods lack the sufficient sensitivity and/or specificity necessary to measure the low endogenous level of 3-NT reliably and are too cumbersome for clinical applications. Hence, analytical improvement is urgently needed to accurately quantify the levels of 3-NT and verify the role of 3-NT in pathological conditions. This protocol presents the development of a novel liquid chromatography tandem mass spectrometry (LC-MS/MS) detection combined with a miniaturized solid phase extraction (SPE) for the rapid and accurate measurement of 3-NT in human urine as a non-invasive biomarker for oxidative stress. SPE using a 96-well plate markedly simplified the process by combining sample cleanup and analyte enrichment without tedious derivatization and evaporation steps, reducing solvent consumption, waste disposal, risk of contamination and overall processing time. The employment of 25 mM ammonium acetate (NH4OAc) at pH 9 as the SPE elution solution substantially enhanced the selectivity. Mass spectrometry signal response was improved through adjustment of the multiple reaction monitoring (MRM) transitions. Use of 0.01% HCOOH as additive on a pentafluorophenyl (PFP) column (150 mm x 2.1 mm, 3 &#181;m) improved signal response another 2.5-fold and shortened the overall run time to 7 min. A lower limit of quantitation (LLOQ) of 10 pg/mL (0.044 nM) was achieved, representing a significant sensitivity improvement over the reported assays. This simplified, rapid, selective and sensitive method allows two plates of urine samples (n = 192) to be processed in a 24 h time-period. Considering the markedly improved analytical performance, and non-invasive and inexpensive urine sampling, the proposed assay is beneficial for pre-clinical and clinical studies.

A selective and sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) method coupled with an efficient solid phase extraction on a mixed-mode cation-exchange (MCX) 96-well microplate was developed for the measurement of free 3-nitrotyrosine (3-NT) in human urine with high throughput, which is suitable for clinical applications.

Free 3-nitrotyrosine (3-NT) has been extensively used as a possible biomarker for oxidative stress. Increased levels of 3-NT have been reported in a wide ...

Quantifying X-Ray Fluorescence Data Using MAPS

The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical composition and elemental distribution within a material. Synchrotron-based XRF has become an integral characterization technique for a variety of research topics, particularly due to its non-destructive nature and its high sensitivity. Today, synchrotrons can acquire fluorescence data at spatial resolutions well below a micron, allowing for the evaluation of compositional variations at the nanoscale. Through proper quantification, it is then possible to obtain an in-depth, high-resolution understanding of elemental segregation, stoichiometric relationships, and clustering behavior.
This article explains how to use the MAPS fitting software developed by Argonne National Laboratory for the quantification of full 2-D XRF maps. We use as an example results from a Cu(In,Ga)Se2 solar cell, taken at the Advanced Photon Source beamline 2-ID-D at Argonne National Laboratory. We show the standard procedure for fitting raw data, demonstrate how to evaluate the quality of a fit and present the typical outputs generated by the program. In addition, we discuss in this manuscript certain software limitations and offer suggestions for how to further correct the data to be numerically accurate and representative of spatially resolved, elemental concentrations.

Here, we demonstrate the use of the X-ray fluorescence fitting software, MAPS, created by Argonne National Laboratory for the quantification of fluorescence microscopy data. The quantified data that results is useful for understanding the elemental distribution and stoichiometric ratios within a sample of interest.

The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical ...

Preparation of Functional Silica Using a Bioinspired Method

The goal of the protocols described herein is to synthesize bioinspired silica materials, perform enzyme encapsulation therein, and partially or totally purify the same by acid elution. By combining sodium silicate with a polyfunctional bioinspired additive, silica is rapidly formed at ambient conditions upon neutralization. 
The effect of neutralization rate and biomolecule addition point on silica yield are investigated, and biomolecule immobilization efficiency is reported for varying addition point. In contrast to other porous silica synthesis methods, it is shown that the mild conditions required for bioinspired silica synthesis are fully compatible with the encapsulation of delicate biomolecules. Additionally, mild conditions are used across all synthesis and modification steps, making bioinspired silica a promising target for the scale-up and commercialization as both a bare material and active support medium.
The synthesis is shown to be highly sensitive to conditions, i.e., the neutralization rate and final synthesis pH, however tight control over these parameters is demonstrated through the use of auto titration methods, leading to high reproducibility in reaction progression pathway and yield. 
Therefore, bioinspired silica is an excellent active material support choice, showing versatility towards many current applications, not limited to those demonstrated here, and potency in future applications.

Here, we present a protocol to synthesize bioinspired silica materials and immobilize enzymes therein. Silica is synthesized by combining sodium silicate and an amine &#39;additive&#39;, which neutralize at a controlled rate. Material properties and function can be altered either by in situ enzyme immobilization or post-synthetic acid elution of encapsulated additives.

The goal of the protocols described herein is to synthesize bioinspired silica materials, perform enzyme encapsulation therein, and partially or totally ...

Natural Product Discovery with LC-MS/MS Diagnostic Fragmentation Filtering: Application for Microcystin Analysis

Natural products are often biosynthesized as mixtures of structurally similar compounds, rather than a single compound. Due to their common structural features, many compounds within the same class undergo similar MS/MS fragmentation and have several identical product ions and/or neutral losses. The purpose of diagnostic fragmentation filtering (DFF) is to efficiently detect all compounds of a given class in a complex extract by screening non-targeted LC-MS/MS datasets for MS/MS spectra that contain class specific product ions and/or neutral losses. This method is based on a DFF module implemented within the open-source MZmine platform that requires sample extracts be analyzed by data-dependent acquisition on a high-resolution mass spectrometer such as quadrupole Orbitrap or quadrupole time-of-flight mass analyzers. The main limitation of this approach is the analyst must first define which product ions and/or neutral losses are specific for the targeted class of natural products. DFF allows for the subsequent discovery of all related natural products within a complex sample, including new compounds. In this work, we demonstrate the effectiveness of DFF by screening extracts of Microcystis aeruginosa, a prominent harmful algal bloom causing cyanobacteria, for the production of microcystins.

Diagnostic fragmentation filtering, implemented into MZmine, is an elegant, post-acquisition approach to screen LC-MS/MS datasets for entire classes of both known and unknown natural products. This tool searches MS/MS spectra for product ions and/or neutral losses that the analyst has defined as being diagnostic for the entire class of compounds.

Natural products are often biosynthesized as mixtures of structurally similar compounds, rather than a single compound. Due to their common structural ...

Optimization of Radiochemical Reactions using Droplet Arrays

Current automated radiosynthesizers are designed to produce large clinical batches of radiopharmaceuticals. They are not well suited for reaction optimization or novel radiopharmaceutical development since each data point involves significant reagent consumption, and contamination of the apparatus requires time for radioactive decay before the next use. To address these limitations, a platform for performing arrays of miniature droplet-based reactions in parallel, each confined within a surface-tension trap on a patterned polytetrafluoroethylene-coated silicon "chip", was developed. These chips enable rapid and convenient studies of reaction parameters including reagent concentrations, reaction solvent, reaction temperature and time. This platform permits the completion of hundreds of reactions in a few days with minimal reagent consumption, instead of taking months using a conventional radiosynthesizer.

This method describes the use of a novel high-throughput methodology, based on droplet chemical reactions, for the rapid and economical optimization of radiopharmaceuticals using nanomole amounts of reagents.

Current automated radiosynthesizers are designed to produce large clinical batches of radiopharmaceuticals. They are not well suited for reaction ...

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

In fragment-based drug discovery, hundreds or often thousands of compounds smaller than ~300 Da are tested against the protein of interest to identify chemical entities that can be developed into potent drug candidates. Since the compounds are small, interactions are weak, and the screening method must therefore be highly sensitive; moreover, structural information tends to be crucial for elaborating these hits into lead-like compounds. Therefore, protein crystallography has always been a gold-standard technique, yet historically too challenging to find widespread use as a primary screen.
Initial XChem experiments were demonstrated in 2014 and then trialed with academic and industrial collaborators to validate the process. Since then, a large research effort and significant beamtime have streamlined sample preparation, developed a fragment library with rapid follow-up possibilities, automated and improved the capability of I04-1 beamline for unattended data collection, and implemented new tools for data management, analysis and hit identification.
XChem is now a facility for large-scale crystallographic fragment screening, supporting the entire crystals-to-deposition process, and accessible to academic and industrial users worldwide. The peer-reviewed academic user program has been actively developed since 2016, to accommodate projects from as broad a scientific scope as possible, including well-validated as well as exploratory projects. Academic access is allocated through biannual calls for peer-reviewed proposals, and proprietary work is arranged by Diamond's Industrial Liaison group. This workflow has already been routinely applied to over a hundred targets from diverse therapeutic areas, and effectively identifies weak binders (1%-30% hit rate), which both serve as high-quality starting points for compound design and provide extensive structural information on binding sites. The resilience of the process was demonstrated by continued screening of SARS-CoV-2 targets during the COVID-19 pandemic, including a 3-week turn-around for the main protease.

This paper describes the complete XChem process for crystal-based fragment screening, starting from applying for access and all subsequent steps to data dissemination.

In fragment-based drug discovery, hundreds or often thousands of compounds smaller than ~300 Da are tested against the protein of interest to identify ...