Durbin Kenneth R, Robey Matthew T, Greer Joseph B, Fellers Ryan T, Bailey Aaron O
Proteinaceous, Inc., Evanston, Illinois 60201, United States.
AbCellera Biologics, Inc., Vancouver, British Columbia V5Y 1G6, Canada.
Anal Chem. 2025 Jul 22;97(28):14964-14973. doi: 10.1021/acs.analchem.5c00288. Epub 2025 Jul 7.
Charge state deconvolution is essential for efficient and effective protein mass spectrometry analysis. High-quality mass profiling is necessary to determine which proteoforms are present in protein samples and their relative abundances. In the pursuit of a well-rounded deconvolution solution, we detail an iterative charge state deconvolution algorithm named kDecon that has been tuned to provide high accuracy in its mass results while also delivering superb sensitivity toward lower abundance proteoforms in complex spectra. Here, the performance of kDecon as a mass determination algorithm for both targeted antibody and high-throughput proteomics analysis was benchmarked against existing deconvolution solutions. While the different deconvolution routines all proved robust for detecting the highest abundance protein species, kDecon ultimately showcased best-in-class precision for lower abundance proteoform mass profiling. Furthermore, kDecon results had up to 7-fold fewer false positives and simultaneously exhibited at least 20-fold speed improvements over the other algorithms. Overall, these deconvolution advances will contribute to enabling both routine and thorough intact mass profiling studies for biotherapeutics as well as improving the proteome coverage of top-down proteomics experiments.
电荷态去卷积对于高效且有效的蛋白质质谱分析至关重要。高质量的质谱剖析对于确定蛋白质样品中存在哪些蛋白质异构体及其相对丰度是必要的。在寻求全面的去卷积解决方案的过程中，我们详细介绍了一种名为kDecon的迭代电荷态去卷积算法，该算法经过调整，在质量结果上具有高精度，同时对复杂光谱中较低丰度的蛋白质异构体也具有出色的灵敏度。在此，将kDecon作为靶向抗体和高通量蛋白质组学分析的质量测定算法的性能与现有的去卷积解决方案进行了基准测试。虽然不同的去卷积程序在检测最高丰度蛋白质种类方面都证明是可靠的，但kDecon最终在较低丰度蛋白质异构体的质谱剖析方面展现出一流的精度。此外，kDecon的结果假阳性减少了多达7倍，同时与其他算法相比，速度提高了至少20倍。总体而言，这些去卷积方面的进展将有助于实现生物治疗药物的常规和全面完整质谱剖析研究，并提高自上而下蛋白质组学实验的蛋白质组覆盖率。
