The authors thank Robert Schuster for assistance with data verification.

The high-level workflow for mAbScale is shown in Figure 2. Each step has more sophisticated inner decision branches, loops, and combinatorics. A detailed algorithmic workflow describing the calculation process is presented in Supplementary Figure 1. The application output is saved in a spreadsheet format in the user-selected folder. The output file consists of multiple separate worksheets, which can be categorized as the user input, molecular weight calculations, and references for the average isotopic mass derivations (example output is provided in supplemental tables). The user input worksheets include the protein amino acid sequences and other information entered by the user, averaged elemental masses, and glycan masses, which are used to calculate the elemental composition and different molecular weights. The molecular weight calculation sheets include the chemical composition of various forms, the reduced mass with and without glycosylation and chemical modification, and the intact mass with and without glycosylation and chemical modification. Sheets containing half-antibody masses will be generated automatically if the user enters two different HCs and/or two different LCs in the user input page, since half-antibodies are primary impurities that need to be identified and quantified relative to the desired heterodimer. The source code for mAbScale can be accessed through the following repository:&#160;https://github.com/kkhatri99/mAbScale.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65298/65298fig02.jpg" /> 
Figure 2: Overview of the steps involved in the calculation of elemental compositions and masses using the application. Color coding can be used to link to the process flow described in Supplementary Figure 1. <a href="https://www.jove.com/files/ftp_upload/65298/65298fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
1. Opening the mAbscale application
<ol>
	<li>Open the software application by double-clicking on the icon for the executable file.</li>
</ol>
2. Sequence entry
<ol>
	<li>Enter the heavy-chain and light-chain sequences in the respective text boxes marked with 1 without any spaces.
	<ol>
		<li>For bsAbs, add additional heavy or light chains in the second set of text boxes marked 2. Leave 2 blank for mAbs with identical heavy chains and light chains.</li>
		<li>Check the N-Terminal Cyclization and/or C-Terminal Clipping check boxes, if these heavy chain terminal variants are applicable.</li>
		<li>Add any chemical modifications, including linker and payload for ADC molecules, to the Heavy Chain Chem Mod and/or Light Chain Chem Mod text boxes.
		<ol>
			<li>Specify modifications as elemental compositions, such as CaCl2. The modification will be added to the respective protein subunit or chain. 
			&#8203;NOTE: A chemical composition may also be subtracted from a subunit or chain by prefixing the elemental composition with a - sign. For example, -H2O will subtract a water molecule from the subunit composition and mass.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
3. Specifying the number of disulfide bonds
<ol>
	<li>Specify the number of disulfide bonds in the protein molecules in the text box marked Total Number of Disulfides.</li>
	<li>Enter the number of unreduced HC disulfides into the Unreduced HC Disulfides text box and the number of unreduced LC disulfides into the Unreduced LC Disulfides text box, depending on the extent of reduction (complete vs. partial). 
	NOTE: The reduced mass analysis of mAb subunits involves the reduction/separation of the disulfide-linked heavy and light chains.</li>
	<li>If glycosylation is present on the mAb light chain, check the Light Chain is Glycosylated check box.</li>
</ol>
4. Setting the output folder and running the application
<ol>
	<li>Click on the Browse button to select an output folder for the Output Folder text box.</li>
	<li>Enter the output file name without a file extension (automatically saves as .xlsx) into the Excel File (no ext) text box.</li>
	<li>Click on the Submit button to start the application. The output file can be found in the designated folder. 
	&#8203;NOTE: The elemental masses and the list of glycans can be customized by editing the delimited text files Element_Mass.csv (Supplementary Coding File 1) and Glycan.csv (Supplementary Coding File 2), respectively. These files must be placed in the same folder as the mAbScale.exe (Supplementary Coding File 3) executable file for the application to execute. The application will be closed automatically after one execution. The user will have to start the app again if a second calculation is needed.</li>
</ol>

A Python-Based Tool for Accurate Mass Calculation of Biotherapeutic Entities

<ol>
	<li>Reichert, J. M., Valge-Archer, V. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+trends+for+monoclonal+antibody+cancer+therapeutics.">Development trends for monoclonal antibody cancer therapeutics.</a> Nature Reviews Drug Discovery. 6 (5), 349-356 (2007).</li><li>Kintzing, J. R., Filsinger Interrante, M. V., Cochran, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emerging+strategies+for+developing+next-generation+protein+therapeutics+for+cancer+treatment.">Emerging strategies for developing next-generation protein therapeutics for cancer treatment.</a> Trends in Pharmacological Sciences. 37 (12), 993-1008 (2016).</li><li>Wang, M. -. Y., 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=SARS-CoV-2:+Structure,+biology,+and+structure-based+therapeutics+development.">SARS-CoV-2: Structure, biology, and structure-based therapeutics development.</a> Frontiers in Cellular and Infection Microbiology. 10, 587269 (2020).</li><li>ICH Q8 (R2) Pharmaceutical Development - Scientific Guideline. European Medicines Agency Available from: <a target="_blank" href="https://www.ema.europa.eu/en/ch-q8-r2-pharmaceutical-development-scientific-guideline">https://www.ema.europa.eu/en/ch-q8-r2-pharmaceutical-development-scientific-guideline</a> (2018)</li><li>Donnelly, D. P., 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=Best+practices+and+benchmarks+for+intact+protein+analysis+for+top-down+mass+spectrometry.">Best practices and benchmarks for intact protein analysis for top-down mass spectrometry.</a> Nature Methods. 16 (7), 587-594 (2019).</li><li>Gadgil, H. S., Pipes, G. D., Dillon, T. M., Treuheit, M. J., Bondarenko, P. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improving+mass+accuracy+of+high+performance+liquid+chromatography/electrospray+ionization+time-of-flight+mass+spectrometry+of+intact+antibodies.">Improving mass accuracy of high performance liquid chromatography/electrospray ionization time-of-flight mass spectrometry of intact antibodies.</a> Journal of the American Society for Mass Spectrometry. 17 (6), 867-872 (2006).</li><li>Beck, A., Sanglier-Cianf&#233;rani, S., Van Dorsselaer, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biosimilar,+biobetter,+and+next+generation+antibody+characterization+by+mass+spectrometry.">Biosimilar, biobetter, and next generation antibody characterization by mass spectrometry.</a> Analytical Chemistry. 84 (11), 4637-4646 (2012).</li><li>Camperi, J., Goyon, A., Guillarme, D., Zhang, K., Stella, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-dimensional+LC-MS:+the+next+generation+characterization+of+antibody-based+therapeutics+by+unified+online+bottom-up,+middle-up+and+intact+approaches.">Multi-dimensional LC-MS: the next generation characterization of antibody-based therapeutics by unified online bottom-up, middle-up and intact approaches.</a> Analyst. 146 (3), 747-769 (2021).</li><li>Liu, H., May, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Disulfide+bond+structures+of+IgG+molecules.">Disulfide bond structures of IgG molecules.</a> mAbs. 4 (1), 17-23 (2012).</li><li>Jakes, C., F&#252;ssl, F., Zaborowska, I., Bones, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+analysis+of+biotherapeutics+using+protein+a+chromatography+coupled+to+orbitrap+mass+spectrometry.">Rapid analysis of biotherapeutics using protein a chromatography coupled to orbitrap mass spectrometry.</a> Analytical Chemistry. 93 (40), 13505-13512 (2021).</li><li>Robotham, A. C., Kelly, J. F., Matte, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+1+-+LC-MS+characterization+of+antibody-based+therapeutics:+Recent+highlights+and+future+prospects.">Chapter 1 - LC-MS characterization of antibody-based therapeutics: Recent highlights and future prospects.</a> Approaches to the Purification, Analysis and Characterization of Antibody-Based Therapeutics. , 1-33 (2020).</li><li>Valeja, S. G., 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=Unit+mass+baseline+resolution+for+an+intact+148+kDa+therapeutic+monoclonal+antibody+by+fourier+transform+ion+cyclotron+resonance+mass+spectrometry.">Unit mass baseline resolution for an intact 148 kDa therapeutic monoclonal antibody by fourier transform ion cyclotron resonance mass spectrometry.</a> Analytical Chemistry. 83 (22), 8391-8395 (2011).</li><li>Fornelli, L., Ayoub, D., Aizikov, K., Beck, A., Tsybin, Y. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Middle-down+analysis+of+monoclonal+antibodies+with+electron+transfer+dissociation+orbitrap+fourier+transform+mass+spectrometry.">Middle-down analysis of monoclonal antibodies with electron transfer dissociation orbitrap fourier transform mass spectrometry.</a> Analytical Chemistry. 86 (6), 3005-3012 (2014).</li><li>Berglund, M., Wieser, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isotopic+compositions+of+the+elements+2009+(IUPAC+Technical+Report).">Isotopic compositions of the elements 2009 (IUPAC Technical Report).</a> Pure and Applied Chemistry. 83 (2), 397-410 (2011).</li><li>Wang, M., 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=The+Ame2012+atomic+mass+evaluation.">The Ame2012 atomic mass evaluation.</a> Chinese Physics C. 36 (12), 1603-2014 (2012).</li><li>Peri, S., Steen, H., Pandey, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GPMAW--A+software+tool+for+analyzing+proteins+and+peptides.">GPMAW--A software tool for analyzing proteins and peptides.</a> Trends in Biochemical Sciences. 26 (11), 687-689 (2001).</li><li>Tipton, J. D., 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+intact+protein+isoforms+by+mass+spectrometry.">Analysis of intact protein isoforms by mass spectrometry.</a> The Journal of Biological Chemistry. 286 (29), 25451-25458 (2011).</li><li>De Leoz, M. L. A., 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=interlaboratory+study+on+glycosylation+analysis+of+monoclonal+antibodies:+Comparison+of+results+from+diverse+analytical+methods.">interlaboratory study on glycosylation analysis of monoclonal antibodies: Comparison of results from diverse analytical methods.</a> Molecular &amp; Cellular Proteomics. 19 (1), 11-30 (2020).</li><li>Cymer, F., Beck, H., Rohde, A., Reusch, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Therapeutic+monoclonal+antibody+N-glycosylation+-+Structure,+function+and+therapeutic+potential.">Therapeutic monoclonal antibody N-glycosylation - Structure, function and therapeutic potential.</a> Biologicals. 52, 1-11 (2018).</li><li>Baker, P. R., Trinidad, J. C., Chalkley, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modification+site+localization+scoring+integrated+into+a+search+engine.">Modification site localization scoring integrated into a search engine.</a> Molecular &amp; Cellular Proteomics. 10 (7), (2011).</li><li>Chalkley, R. J., Clauser, K. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modification+site+localization+scoring:+Strategies+and+performance.">Modification site localization scoring: Strategies and performance.</a> Molecular &amp; Cellular Proteomics. 11 (5), 3-14 (2012).</li></ol>

This software is being released under the Apache 2.0 license. Copyright (2022) of GlaxoSmithKline Research &#38; Development Limited. All rights reserved. Licensed under the Apache License, Version 2.0 (the &#34;License&#34;); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an &#34;as is&#34; basis, without warranties or conditions of any kind, either expressed or implied. See the License for the specific language governing permissions and limitations under the License. L.C. is a GlaxoSmithKline (GSK) employee. T.H. and K.K. developed this software as employees of GSK and are now associates of Merck and Moderna, respectively.

mAbScale provides an intuitive user interface with the flexibility to alter the building blocks for mass and elemental calculations. The users are expected to have a basic understanding of the target molecule to use the application, derive correct masses, and interpret the results. For example, the intact or reduced mass output sheet can be overwhelming due to the numerous rows of intact or reduced masses, since the default glycan database contains 88 N-linked glycans that are commonly found in the Fc portion of therapeu...

Over the past two decades, biotherapeutics have evolved to become a mainstay of the modern pharmaceutical industry. The SARS-CoV2 pandemic and other life-threatening conditions have further increased the need for the faster and broader development of biopharmaceutical molecules1,2,3.
The biotherapeutic molecular weight is critical for the identification of the molecule, in combination with other analytical assays. The intact and reduced subunit masses are used throughout the discovery and development lifecycles as part of control strategies aimed at maintaining the quality, as described in the QTPP (Quality Target Product Profile)4.
Analytical development in the biopharmaceutical industry relies heavily on mass measurements for intact mass analysis and deep characterization using peptide mapping or multi-attribute method (MAM) monitoring. At the center of these techniques utilizing modern mass spectrometry (MS) platforms is the ability to provide high-resolution accurate mass (HR/AM) measurements. Most HR/AM instruments yield mass accuracies in the range of 0.5-5 ppm, which scale with the mass range. The ability to measure masses accurately for intact large molecules enables the quick and confident identification of large-molecule therapeutics. As isotopic resolution cannot be attained using typical experimental conditions for large molecules (&#62;10 kDa), average masses must be calculated for comparison and identification5,6.
A typical intact or subunit protein mass spectrum represents the overall proteoform profile, which contains composite information on the various molecular forms resulting from post-translational modifications (PTM) and any primary structure differences, such as clips or sequence variants. The relatively easy and high-throughput nature of these measurements make them attractive for characterization and as in-process monitoring controls7,8. Data analysis for these experiments usually requires the user to define the search space for molecular forms (range of PTMs or other molecular forms). For glycosylated proteins, this search space is largely driven by glycoform heterogeneity. Combinations of multiple PTMs, disulfide bond configurations, and other variations along the primary structure make calculating all the possible molecular forms a tedious task. Therefore, the manual calculation of the possible molecular forms is a time and resource-consuming process with a high potential for human error.
Here, we present a mass calculation tool that was developed considering the most important features of biotherapeutic molecules, such as mAbs, bsAbs, ADCs, etc. The tool allows the easy incorporation of search-space variables for the consistent calculation of masses and elemental compositions. The modular nature of this tool will enable it to be further developed and applied to mass calculation and mass matching for other modalities.
The GUI module allows the user to specify the input for the mass calculation, as shown in Figure 1; specifically, the user enters single-letter amino acid sequences for light and heavy antibody chains. Common modifications for heavy-chain N-terminal cyclization and C-terminal lysine clipping are included as check boxes. Further, the chemical formula/elemental composition can be added/subtracted from these protein chains through the respective Chem Mod text box. This allows the user the flexibility to add an elemental composition that includes multiple post-translational modifications or a small-molecule payload in the case of an ADC. As most therapeutic mAbs are engineered to remove the glycosylation sites in the light chain, glycosylation in the light chain is left optional and can be specified using a check box on the GUI.
A typical variation on intact mass analysis for antibodies is a reduced subunit mass analysis, where the light chain is detached from the heavy chain by reducing the interchain disulfide bonds. Depending on the strength of the reducing agent used, the intrachain disulfide bonds may or may not be cleaved. The users have the flexibility of entering the total number of disulfide bonds depending on the IgG subtype or in case of a cysteine-conjugated ADC9.
The application calculates masses in a bottom-up manner, in which the elemental compositions are first calculated for the individual heavy chains and light chains. Next, heavy chain (HC) N-terminal cyclization Lys-clipping is accounted for by adjusting the calculated elemental compositions. Any specified chemical modifications are then applied to the heavy and/or light chains. Depending on the type of analysis and the disulfide-bond patterns specified by the user, the number of hydrogens is adjusted for the two polypeptide chains. The glycosylated HC and light chain (LC) (optional) masses are calculated based on the user&#39;s input. Finally, multiple HC and LC masses are combined, and the disulfide bond numbers are automatically updated for the intact mass calculation.
With larger molecules such as intact proteins, monoisotopic masses cannot be measured due to the additive mass defect when using mass spectrometers with typical resolving power. Instead, nominal or average masses are measured or reported5,10,11,12,13. The average elemental masses can vary based on the source used for the curated masses14,15. While the differences in elemental masses may be small, they can add up to significant values for large-molecule molecular weight calculations. The average elemental masses used by default in the software application are shown in Supplementary Table 1. For regulated environments like the biopharmaceutical research and development (R&#38;D) field, it is important to maintain consistent molecular masses because changes in masses may imply changes to the molecular entity during regulatory filings. To enable consistency in the use of elemental masses, a dictionary of elemental masses is included with the software tool as a comma-separated value (csv) text file: Element_Mass.csv (Supplementary Coding File 1). Similarly, a curated list of glycan compositions typically seen on mAbs is included: Glycan.csv (Supplementary Coding File 2). Both files are saved in the same folder location as an executable application and can be modified by the user to use a specific elemental mass list or glycan library.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65298/65298fig01.jpg" /> 
Figure 1: GUI interface for the mAbScale application. The GUI module allows the user to specify the input for the mass calculation. The user enters single-letter amino acid sequences for the light and heavy antibody chains. Common modifications for the heavy-chain N-terminal cyclization and C-terminal lysine clipping are included as check boxes. Chemical formulas/elemental compositions can be added/subtracted through the respective Chem Mod text box. <a href="https://www.jove.com/files/ftp_upload/65298/65298fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Acquity UPLC system&#160;</td>
			<td>Waters Corp., Milford, MA</td>
			<td>N/A</td>
			<td>Modular system</td>
		</tr>
		<tr>
			<td>Antibody-drug conjugate (ADC)</td>
			<td>GlaxoSmithKline</td>
			<td>N/A</td>
			<td>Proprietory molecule</td>
		</tr>
		<tr>
			<td>BEH 200 SEC column&#160;</td>
			<td>Waters Corp., Milford, MA</td>
			<td>176003904</td>
			<td></td>
		</tr>
		<tr>
			<td>Bispecific mAb</td>
			<td>GlaxoSmithKline</td>
			<td>N/A</td>
			<td>Proprietory molecule</td>
		</tr>
		<tr>
			<td>Byos</td>
			<td>Protein Metrics, Cupertino, CA</td>
			<td>https://proteinmetrics.com/byos/ 
			Version 4.5</td>
			<td></td>
		</tr>
		<tr>
			<td>GPMAW</td>
			<td>GPMAW</td>
			<td>http://www.gpmaw.com/</td>
			<td></td>
		</tr>
		<tr>
			<td>LC-MS grade water&#160;</td>
			<td>Thermo Fisher Scientific, Waltham, MA</td>
			<td>W6-1</td>
			<td></td>
		</tr>
		<tr>
			<td>mAb standard&#160;</td>
			<td>Waters Corp., Milford, MA</td>
			<td>186009125</td>
			<td>Waters Humanized mAb Mass Check Standard</td>
		</tr>
		<tr>
			<td>mAbScale</td>
			<td>GlaxoSmithKline</td>
			<td>Apache License, Version 2.0&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>Xevo G2 Q-TOF mass spectrometer</td>
			<td>Waters Corp., Milford, MA</td>
			<td>N/A</td>
			<td>Modular system</td>
		</tr>
	</tbody>
</table>

an open-source framework for mass calculation of antibody-based therapeutic molecules

Biotherapeutic masses are a means of verifying identity and structural integrity. Mass spectrometry (MS) of intact proteins or protein subunits provides an easy analytical tool for different stages of biopharmaceutical development. The protein's identity is confirmed when the experimental mass from MS is within a pre-defined mass error range of the theoretical mass. While several computational tools exist for the calculation of protein and peptide molecular weights, they either were not designed for direct application to biotherapeutic entities, have access limitations due to paid licenses, or require uploading protein sequences to host servers. 
We have developed a modular mass calculation routine that enables the easy determination of the average or monoisotopic masses and elemental compositions of therapeutic glycoproteins, including monoclonal antibodies (mAb), bispecific antibodies (bsAb), and antibody-drug conjugates (ADC). The modular nature of this Python-based calculation framework will allow the extension of this platform to other modalities such as vaccines, fusion proteins, and oligonucleotides in the future, and this framework could also be useful for the interrogation of top-down mass spectrometry data. By creating an open-source standalone desktop application with a graphical user interface (GUI), we hope to overcome the restrictions around use in environments where proprietary information cannot be uploaded to web-based tools. This article describes the algorithms and application of this tool, mAbScale, to different antibody-based therapeutic modalities.

A variety of mAbs were selected to represent different types of mAbs. A commercially available mAb standard was selected to represent a conventional mAb with identical heavy chains, identical light chains, and one N-linked glycosylation site in the Fc region. A&#160;mAb with an additional light chain N-linked glycosylation, a bispecific mAb, and an antibody-drug conjugate (ADC) mAb were also chosen to widen the application usage. The chemical composition, calculated mass, measured mass, and mass error of these example mA...

Watch this Scientific Journal Video about Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application at JoVE.com

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

This article describes the use of a software application, mAbScale, for the calculation of masses for monoclonal antibody-based protein therapeutics.

An Open-Source Framework for Mass Calculation of Antibody-Based Therapeutic Molecules

Biotherapeutic masses are a means of verifying identity and structural integrity. Mass spectrometry (MS) of intact proteins or protein subunits provides ...

an-open-source-framework-for-mass-calculation-antibody-based

Research

JoVE Journal

Biochemistry

1.4K Views.  GlaxoSmithKline. This article describes the use of a software application, mAbScale, for the calculation of masses for monoclonal antibody-based protein therapeutics.

Video: Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. Hydrogen-Deuterium Exchange (HDX) measured at rapid time scales is uniquely suited to detect structures and hydrogen bonding networks that are briefly populated, allowing for the characterization of transient conformers in native ensembles. Coupling of HDX to mass spectrometry offers several key advantages, including high sensitivity, low sample consumption and no restriction on protein size. This technique has advanced greatly in the last several decades, including the ability to monitor HDX labeling times on the millisecond time scale. In addition, by incorporating the HDX workflow onto a microfluidic platform housing an acidic protease microreactor, we are able to localize dynamic properties at the peptide level. In this study, Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) coupled to HDX was used to provide a detailed picture of residual structure in the tau protein, as well as the conformational shifts induced upon hyperphosphorylation.

Conformational flexibility plays a critical role in protein function. Herein, we describe the use of time-resolved electrospray ionization mass spectrometry coupled to hydrogen-deuterium exchange for probing the rapid structural changes that drive function in ordered and disordered proteins.

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. ...

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological processes. Affinity purification coupled to mass spectrometry (AP-MS) has become the method of choice for identifying protein-protein interactions. However, conventional AP-MS studies provide information on protein interactions, but the organizational information is lost. To address this issue, we developed a strategy to unravel the distinct functional assemblies a protein might be involved in, by resolving affinity-purified protein complexes prior to their characterization by mass spectrometry. Protein complexes isolated through affinity purification of a bait protein using an epitope tag and competitive elution are separated through blue native electrophoresis. Comparison of protein migration profiles through correlation profiling using quantitative mass spectrometry allows assignment of interacting proteins to distinct molecular entities. This method is able to resolve protein complexes of close molecular weights that might not be resolved by traditional chromatographic techniques such as gel filtration. With little more work than conventional AP-geLC-MS/MS, we demonstrate this strategy may in many cases be adequate for obtaining protein complex topological information concomitantly to identifying protein interactions.

Here we present protocols for affinity purification of protein complexes and their separation by blue native PAGE, followed by protein correlation profiling using label free quantitative mass spectrometry. This method is useful to resolve interactomes into distinct protein complexes.

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological ...

Lipid Droplet Isolation for Quantitative Mass Spectrometry Analysis

Lipid droplets are vital to the replication of a variety of different pathogens, most prominently the Hepatitis C Virus (HCV), as the putative site of virion morphogenesis. Quantitative lipid droplet proteome analysis can be used to identify proteins that localize to or are displaced from lipid droplets under conditions such as virus infections. Here, we describe a protocol that has been successfully used to characterize the changes in the lipid droplet proteome following infection with HCV. We use Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) and thus label the complete proteome of one population of cells with &#34;heavy&#34; amino acids to quantitate the proteins by mass spectrometry. For lipid droplet isolation, the two cell populations (i.e.&#160;HCV-infected/&#34;light&#34; amino acids and uninfected control/&#34;heavy&#34; amino acids) are mixed 1:1 and lysed mechanically in hypotonic buffer. After removing the nuclei and cell debris by low speed centrifugation, lipid droplet-associated proteins are enriched by two subsequent ultracentrifugation steps followed by three washing steps in isotonic buffer. The purity of the lipid droplet fractions is analyzed by western blotting with antibodies recognizing different subcellular compartments. Lipid droplet-associated proteins are then separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) followed by Coomassie staining. After tryptic digest, the peptides are quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Using this method, we identified proteins recruited to lipid droplets upon HCV infection that might represent pro- or antiviral host factors. Our method can be applied to a variety of different cells and culture conditions, such as infection with pathogens, environmental stress, or drug treatment.

Lipid droplets are important organelles for the replication of several pathogens, including the Hepatitis C Virus (HCV). We describe a method to isolate lipid droplets for quantitative mass spectrometry of associated proteins; it can be used under a variety of conditions, such as virus infection, environmental stress, or drug treatment.

Lipid droplets are vital to the replication of a variety of different pathogens, most prominently the Hepatitis C Virus (HCV), as the putative site of ...

Force Spectroscopy of Single Protein Molecules Using an Atomic Force Microscope

The determination of the folding process of proteins from their amino acid sequence to their native 3D structure is an important problem in biology. Atomic force microscopy (AFM) can address this problem by enabling stretching and relaxation of single protein molecules, which gives direct evidence of specific unfolding and refolding characteristics. AFM-based single-molecule force-spectroscopy (AFM-SMFS) provides a means to consistently measure high-energy conformations in proteins that are not possible in traditional bulk (biochemical) measurements. Although numerous papers were published to show principles of AFM-SMFS, it is not easy to conduct SMFS experiments due to a lack of an exhaustively complete protocol. In this study, we briefly illustrate the principles of AFM and extensively detail the protocols, procedures, and data analysis as a guideline to achieve good results from SMFS experiments. We demonstrate representative SMFS results of single protein mechanical unfolding measurements and we provide troubleshooting strategies for some commonly encountered problems.

We describe the detailed procedures and strategies to measure the mechanical properties and mechanical unfolding pathways of single protein molecules using an atomic force microscope. We also show representative results as a reference for selection and justification of good single protein molecule recordings.

The determination of the folding process of proteins from their amino acid sequence to their native 3D structure is an important problem in biology. ...

Calibration-free In Vitro Quantification of Protein Homo-oligomerization Using Commercial Instrumentation and Free, Open Source Brightness Analysis Software

Number and brightness is a calibration-free fluorescence fluctuation spectroscopy (FFS) technique for detecting protein homo-oligomerization. It can be employed using a conventional confocal microscope equipped with digital detectors. A protocol for the use of the technique in vitro is shown by means of a use case where number and brightness can be seen to accurately quantify the oligomeric state of mVenus-labelled FKBP12F36V before and after the addition of the dimerizing drug AP20187. The importance of using the correct microscope acquisition parameters and the correct data preprocessing and analysis methods are discussed. In particular, the importance of the choice of photobleaching correction is stressed. This inexpensive method can be employed to study protein-protein interactions in many biological contexts.

Calibration-free In Vitro Quantification of Protein Homo-oligomerization Using Commercial Instrumentation and Free, Open Source Brightness Analysis Software

This protocol describes a calibration-free approach for quantifying protein homo-oligomerization in vitro based on fluorescence fluctuation spectroscopy using commercial light scanning microscopy. The correct acquisition settings and analysis methods are shown.

Number and brightness is a calibration-free fluorescence fluctuation spectroscopy (FFS) technique for detecting protein homo-oligomerization. It can be ...

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

In order to visualize the relationship between bacterial phylogeny and specialized metabolite production of bacterial colonies growing on nutrient agar, we developed IDBac&#8212;a low-cost and high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) bioinformatics pipeline. IDBac software is designed for non-experts, is freely available, and capable of analyzing a few to thousands of bacterial colonies. Here, we present procedures for the preparation of bacterial colonies for MALDI-TOF MS analysis, MS instrument operation, and data processing and visualization in IDBac. In particular, we instruct users how to cluster bacteria into dendrograms based on protein MS fingerprints and interactively create Metabolite Association Networks (MANs) from specialized metabolite data.

IDBac is an open-source mass spectrometry-based bioinformatics pipeline that integrates data from both intact protein and specialized metabolite spectra, collected on cell material scraped from bacterial colonies. The pipeline allows researchers to rapidly organize hundreds to thousands of bacterial colonies into putative taxonomic groups, and further differentiate them based on specialized metabolite production.

In order to visualize the relationship between bacterial phylogeny and specialized metabolite production of bacterial colonies growing on nutrient agar, ...

A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation

Sample preparation for mass spectrometry analysis in proteomics requires enzymatic cleavage of proteins into a peptide mixture. This process involves numerous incubation and liquid transfer steps in order to achieve denaturation, reduction, alkylation, and cleavage. Adapting this workflow onto an automated workstation can increase efficiency and reduce coefficients of variance, thereby providing more reliable data for statistical comparisons between sample types. We previously described an automated proteomic sample preparation workflow1. Here, we report the development of a more efficient and better controlled workflow with the following advantages: 1) The number of liquid transfer steps is reduced from nine to six by combining reagents; 2) Pipetting time is reduced by selective tip pipetting using a 96-position pipetting head with multiple channels; 3) Potential throughput is increased by the availability of up to 45 deck positions; 4) Complete enclosure of the system provides improved temperature and environmental control and reduces the potential for contamination of samples or reagents; and 5) The addition of stable isotope labeled peptides, as well as &#946;-galactosidase protein, to each sample makes monitoring and quality control possible throughout the entire process. These hardware and process improvements provide good reproducibility and improve intra-assay and inter-assay precision (CV of less than 20%) for LC-MS based protein and peptide quantification. The entire workflow for digesting 96 samples in a 96-well plate can be completed in approximately 5 hours.

Here, we present an automated plasma protein digestion method for mass spectrometry-based quantitative proteomic analysis. In this protocol, the liquid transferring and incubation steps for protein denaturation, reduction, alkylation, and trypsin digestion reactions are streamlined and automated. It takes approximately five hours to prepare a 96-well plate with desired precision.

Sample preparation for mass spectrometry analysis in proteomics requires enzymatic cleavage of proteins into a peptide mixture. This process involves ...

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of biological membranes, energy storage and production, cellular signaling, vesicular transport of proteins, organelle biogenesis, and regulated cell death. Because the budding yeast Saccharomyces cerevisiae is a unicellular eukaryote amenable to thorough molecular analyses, its use as a model organism helped uncover mechanisms linking lipid metabolism and intracellular transport to complex biological processes within eukaryotic cells. The availability of a versatile analytical method for the robust, sensitive, and accurate quantitative assessment of major classes of lipids within a yeast cell is crucial for getting deep insights into these mechanisms. Here we present a protocol to use liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of major cellular lipids of S. cerevisiae. The LC-MS/MS method described is versatile and robust. It enables the identification and quantification of numerous species (including different isobaric or isomeric forms) within each of the 10 lipid classes. This method is sensitive and allows identification and quantitation of some lipid species at concentrations as low as 0.2 pmol/&#181;L. The method has been successfully applied to assessing lipidomes of whole yeast cells and their purified organelles. The use of alternative mobile phase additives for electrospray ionization mass spectrometry in this method can increase the efficiency of ionization for some lipid species and can be therefore used to improve their identification and quantitation.

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol using liquid chromatography coupled with tandem mass spectrometry to identify and quantify major cellular lipids in Saccharomyces cerevisiae. The described method for a quantitative assessment of major lipid classes within a yeast cell is versatile, robust, and sensitive.

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of ...

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within a cell, tissue, organ, biological fluid, or organism. Metabolomics traditionally focuses on water-soluble metabolites. The water-soluble metabolome is the final product of a complex cellular network that integrates various genomic, epigenomic, transcriptomic, proteomic, and environmental factors. Hence, the metabolomic analysis directly assesses the outcome of the action for all these factors in a plethora of biological processes within various organisms. One of these organisms is the budding yeast Saccharomyces cerevisiae, a unicellular eukaryote with the fully sequenced genome. Because S. cerevisiae is amenable to comprehensive molecular analyses, it is used as a model for dissecting mechanisms underlying many biological processes within the eukaryotic cell. A versatile analytical method for the robust, sensitive, and accurate quantitative assessment of the water-soluble metabolome would provide the essential methodology for dissecting these mechanisms. Here we present a protocol for the optimized conditions of metabolic activity quenching in and water-soluble metabolite extraction from S. cerevisiae cells. The protocol also describes the use of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of the extracted water-soluble metabolites. The LC-MS/MS method of non-targeted metabolomics described here is versatile and robust. It enables the identification and quantification of more than 370 water-soluble metabolites with diverse structural, physical, and chemical properties, including different structural isomers and stereoisomeric forms of these metabolites. These metabolites include various energy carrier molecules, nucleotides, amino acids, monosaccharides, intermediates of glycolysis, and tricarboxylic cycle intermediates. The LC-MS/MS method of non-targeted metabolomics is sensitive and allows the identification and quantitation of some water-soluble metabolites at concentrations as low as 0.05 pmol/&#181;L. The method has been successfully used for assessing water-soluble metabolomes of wild-type and mutant yeast cells cultured under different conditions.

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol for the identification and quantitation of major classes of water-soluble metabolites in the yeast Saccharomyces cerevisiae. The described method is versatile, robust, and sensitive. It allows the separation of structural isomers and stereoisomeric forms of water-soluble metabolites from each other.

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within ...

Microcrystal Electron Diffraction of Small Molecules

A detailed protocol for preparing small molecule samples for microcrystal electron diffraction (MicroED) experiments is described. MicroED has been developed to solve structures of proteins and small molecules using standard electron cryo-microscopy (cryo-EM) equipment. In this way, small molecules, peptides, soluble proteins, and membrane proteins have recently been determined to high resolutions. Protocols are presented here for preparing grids of small-molecule pharmaceuticals using the drug carbamazepine as an example. Protocols for screening and collecting data are presented. Additional steps in the overall process, such as data integration, structure determination, and refinement are presented elsewhere. The time required to prepare the small-molecule grids is estimated to be less than 30 min.

Here, we describe the procedures developed in our laboratory for preparing powders of small molecule crystals for microcrystal electron diffraction (MicroED) experiments.

A detailed protocol for preparing small molecule samples for microcrystal electron diffraction (MicroED) experiments is described. MicroED has been ...

An Open-Source Framework for Mass Calculation of Antibody-Based Therapeutic Molecules

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Chapters in this video

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Lipid Droplet Isolation for Quantitative Mass Spectrometry Analysis

Force Spectroscopy of Single Protein Molecules Using an Atomic Force Microscope

Calibration-free In Vitro Quantification of Protein Homo-oligomerization Using Commercial Instrumentation and Free, Open Source Brightness Analysis Software

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Microcrystal Electron Diffraction of Small Molecules