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ProLuCID: An improved SEQUEST-like algorithm with enhanced sensitivity and specificity
Open accessAbstract
ProLuCID, a new algorithm for peptide identification using tandem mass spectrometry and protein sequence databases has been developed. This algorithm uses a three tier scoring scheme. First, a binomial probability is used as a preliminary scoring scheme to select candidate peptides. The binomial probability scores generated by ProLuCID minimize molecular weight bias and are independent of database size. A modified cross-correlation score is calculated for each candidate peptide identified by the binomial probability. This cross-correlation scoring function models the isotopic distributions of fragment ions of candidate peptides which ultimately results in higher sensitivity and specificity than that obtained with the SEQUEST XCorr. Finally, ProLuCID uses the distribution of XCorr values for all of the selected candidate peptides to compute a Z score for the peptide hit with the highest XCorr. The ProLuCID Z score combines the discriminative power of XCorr and DeltaCN, the standard parameters for assessing the quality of the peptide identification using SEQUEST, and displays significant improvement in specificity over ProLuCID XCorr alone. ProLuCID is also able to take advantage of high resolution MS/MS spectra leading to further improvements in specificity when compared to low resolution tandem MS data. A comparison of filtered data searched with SEQUEST and ProLuCID using the same false discovery rate as estimated by a target-decoy database strategy, shows that ProLuCID was able to identify as many as 25% more proteins than SEQUEST. ProLuCID is implemented in Java and can be easily installed on a single computer or a computer cluster. This article is part of a Special Issue entitled: Computational Proteomics.
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“Under serum-free survival conditions, we have previously observed that the cells do not proliferate, and thus we are measuring loss of viability in these cells under serum-free conditions with pharmacological treatment 49.”
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“Data analysis was performed using ProLuCID and DTASelect2 implemented in Integrated Proteomics Pipeline IP2 (Integrated Proteomics Applications) [79–81].”
Self-citationChou, A. C., Aslanian, A., Sun, H., & Hunter, T. R. (2019) · Journal of Biological Chemistry · doi:10.1074/jbc.ra118.006269 · Cited by 6
Multi-omics Quality Assessment in Personalized Medicine through EATRISPreprint
EATRIS Plus Multi-omics working group and stakeholders (in alphabetical order by last name), Alonso-Andrés, P., Baldazzi, D., Chen, Q., Conde, E., Crespo-Toro, L., Donner, K. M., Džubák, P., Ekberg, S., García‐Bermejo, L., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.25.563912 · Cited by 6
Keratinocyte-Derived Exosomes in Painful Diabetic NeuropathyPreprint
Coy-Dibley, J. S., Jayaraj, N. D., Ren, D., Pacifico, P., Belmadani, A. A., Wang, Y., Gebis, K. K., Savas, J. N., Paller, A. S., Miller, R. J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.21.608803 · Cited by 6
Tight regulation of a nuclear HAPSTR1-HUWE1 pathway essential for mammalian life
Amici, D. R., Alhayek, S., Klein, A. T., Wang, Y., Wilen, A. P., Song, W., Zhu, P., Thakkar, A. V., King, M. A., Steffeck, A. W. T., et al. (2024) · Life Science Alliance · doi:10.26508/lsa.202302370 · Cited by 6
Guo, X., Lu, J., Miao, L., & Shen, E.-Z. (2025) · Biology · doi:10.3390/biology14030279 · Cited by 11
“Tandem mass spectra were searched against the C. elegans protein database (wormpep 235) using the ProLuCID search algorithm [29] to identify 14 N-or 15 N-labeled peptides.”
Karunakaran, D. K. P., Ley, M. L., Guo, J., Khatri, A. W., Sadleir, K. R., Popović, J., Upadhyay, A. K., Savas, J. N., Procissi, D., Atwal, J. K., et al. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00850-z · Cited by 5
“3 .1) with 50 ppm peptide mass tolerance for precursor ions and 600 ppm for fragment ions [24].”
Bale, S., Gustchina, E., Guenaga, J., Ayala, V., Lee, W.-H., Ozorowski, G., Whitney, S., Wilson, R., Baboo, S., Diedrich, J. K., et al. (2025) · npj Vaccines · doi:10.1038/s41541-025-01218-6 · Cited by 5
Self-citationWood, J. I., Dulewicz, M., Szadziewska, A., Weiner, S., Ge, J., Stringer, K. M., Desai, S., Fenson, L., Piotrowska, D., Brinkmalm, G., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63328-y · Cited by 14
Zemke, N. R., Barshop, W., Sha, J., Hsu, E., Wohlschlegel, J. A., & Berk, A. J. (2023) · Journal of Virology · doi:10.1128/jvi.00993-23 · Cited by 6
Self-citationN6-methyladenosine in 28S rRNA promotes oncogenic mRNA translation and tyrosine catabolism
Chen, B., Li, L., Huang, Y., Ma, J., Ji, F., Chen, Y., Wu, L., & Peng, H. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.115139 · Cited by 5
Unconventional tonicity-regulated nuclear trafficking of NFAT5 mediated by KPNB1, XPOT and RUVBL2
Cheung, C., Huang, T., Chow, N., Zhang, S., Zhao, Y., Chau, M. P., Chan, W. C., Wong, C. C. L., Boassa, D., Phan, S., et al. (2022) · Journal of Cell Science · doi:10.1242/jcs.259280 · Cited by 5
Self-citationGPU-acceleration of the distributed-memory database peptide search of mass spectrometry data
Haseeb, M., & Saeed, F. (2023) · Scientific Reports · doi:10.1038/s41598-023-43033-w · Cited by 5
Chemoproteomic Profiling of Erastin-Interacting Proteins
Li, Z., Liu, D., Wang, Y., & Wang, C. (2024) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.3c00347 · Cited by 5
Yu, N., McClatchy, D. B., Diedrich, J. K., Romero, S. L., Choi, J., Martínez‐Bartolomé, S., Delahunty, C. M., Muotri, A. R., & Yates, J. R. (2020) · iScience · doi:10.1016/j.isci.2021.103321 · Cited by 5
Self-citationTran, N. H., Zhang, X., & Li, M. (2017) · PROTEOMICS · doi:10.1002/pmic.201700319 · Cited by 5
Ahsan, N., Chen, M., Salvato, F., Wilson, R. S., Rao, R. S. P., & Thelen, J. J. (2017) · Journal of Proteomics · doi:10.1016/j.jprot.2017.06.006 · Cited by 5
P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data
Bramer, L., Stratton, K. G., White, A. M., Bleeker, A. H., Kobold, M. A., Waters, K. M., Metz, T., Rodland, K., & Webb‐Robertson, B. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00840 · Cited by 5
Phosphorylation of Yun is required for stem cell proliferation and tumorigenesis
Ren, X., Zhao, H., Shi, L., Li, Z., Kong, R., Ma, R., Jia, L., Lu, S., Wang, J., Dong, M., et al. (2022) · Cell Proliferation · doi:10.1111/cpr.13230 · Cited by 4
Peripheral Neuronal Activation Shapes the Microbiome and Alters Gut PhysiologyPreprint
Griffiths, J. A., Yoo, B. B., Thuy-Boun, P., Cantu, V., Weldon, K. C., Challis, C., Sweredoski, M. J., Chan, K. Y., Thron, T., Sharon, G., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.12.439539 · Cited by 6
Chahine, Z. M., Gupta, M. K., Lenz, T., Hollin, T., Abel, S., Banks, C. A. S., Saraf, A., Prudhomme, J. G., Florens, L. A., & Roch, K. G. L. (2023) · eLife · doi:10.7554/elife.92499.1 · Cited by 5
Keratinocyte-derived extracellular vesicles in painful diabetic neuropathy
Coy-Dibley, J. S., Jayaraj, N. D., Ren, D., Pacifico, P., Belmadani, A. A., Wang, Y., Gebis, K. K., Savas, J. N., Paller, A. S., Miller, R. J., et al. (2024) · Neurobiology of Pain · doi:10.1016/j.ynpai.2024.100176 · Cited by 10
“…identification/quantification and analysis were performed with Integrated Proteomics Pipeline (cid:0) IP2 (Bruker, Madison, WI. https://www.integratedproteomics.com/) using ProLuCID (Eng et al., 1994; Xu, 2015), DTASelect2 (Cociorva, 2007; Tabb et al., 2002), Census and Quantitative Analysis.”
Redox regulation of neuroinflammatory pathways contributes to damage in Alzheimer’s disease brain
Carnevale, L. N., Banerjee, P., Zhang, X., Navarro, J., Raspur, C. K., Patel, P. R., Nakamura, T., Schahrer, E., Scott, H. R., Lang, N., et al. (2026) · Cell chemical biology · doi:10.1016/j.chembiol.2026.03.017 · Cited by 5
Self-citationPlucińska, K., Wayne, C. R., Sanford, H., Mathew, B., Ropek, N., Adaniya, S. M., Model, C., Gómez-Banoy, N., Morozova, K., Cao, X., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117507 · Cited by 7
Ma, R., Kang, M., Kim, G. H., Kang, H., Lee, S., Yang, Y., Lee, H. J., Choi, S., Kim, S., Kim, S., et al. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3003192 · Cited by 7
“The reversed sequences of all proteins were added to the database for calculation of FDR. ProLuCID [109] in Integrated Proteomics Pipeline software; IP2 (Integrated Proteomics Applications, San Diego, CA, USA) was used to identify the peptides, with a precursor mass tolerance of 20 ppm, and a…”
Self-citationLong-lived proteins and DNA as candidate predictive biomarkers for tissue associated diseases
Liu, X., Novak, B., Namendorf, C., Steigenberger, B. A., Zhang, Y., & Turck, C. W. (2024) · iScience · doi:10.1016/j.isci.2024.109642 · Cited by 6
Microprotein-encoding RNA regulation in cells treated with pro-inflammatory and pro-fibrotic stimuli
Pai, V. J., Lau, C. J., García‐Ruiz, A., Donaldson, C. J., Vaughan, J. M., Miller, B., de Souza, E. V., Pinto, A. F. M., Diedrich, J. K., Gavva, N. R., et al. (2024) · BMC Genomics · doi:10.1186/s12864-024-10948-1 · Cited by 4
“Tandem mass spectra were extracted from raw files using RawConverter [82] and searched with Pro-LuCID [83] against a nonredundant human Uniprot data-base appended with IEC smORF sequences.”
MethodSelf-citationRiffle, M. E., Zelter, A., Jaschob, D., Hoopmann, M. R., Faivre, D. A., Moritz, R. L., Davis, T. N., MacCoss, M. J., & Isoherranen, N. (2025) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00968 · Cited by 4
Reina, J., Vallmajó-Martín, Q., Ning, J., Michi, A. N., Yeung, K. T., Wahl, G. M., & Hunter, T. R. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2505653122 · Cited by 4
Luo, M., Spradlin, J. N., Brittain, S. M., McKenna, J. M., Tallarico, J. A., Schirle, M., Maimone, T. J., & Nomura, D. K. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.12.198150 · Cited by 4
“Data were extracted in the form of MS1 and MS2 files using Raw Extractor v.1.9.9.2 (Scripps Research Institute) and searched against the Uniprot human database using ProLuCID search methodology in IP2 v.3 (Integrated Proteomics Applications, Inc.) (Xu et al., 2015).”
MethodInfluentialProtein structure, a genetic constraint on glycosylationPreprint
Kellman, B. P., Sandoval, D. R., Zaytseva, O. O., Brock, K. P., Baboo, S., Nachmanson, D., Irvine, E. B., Schoffelen, S., Armingol, E., Mih, N., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.15.594261 · Cited by 4
Self-citationWestern diet exacerbates a murine model of Balkan nephropathy
Oe, Y., Kim, Y. C., Kanoo, S., Goodluck, H. A., Lopez, N., Diedrich, J. K., Pinto, A. F. M., Evensen, K. G., Currais, A. J. M., Maher, P. A., et al. (2024) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00185.2024 · Cited by 3
Self-citationMcClatchy, D. B., Garrett, P. T., Jung, T., Diedrich, J. K., & Yates, J. R. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00616 · Cited by 3
Self-citationKim, H., Jeon, Y., Kim, S., Guo, Y., Kim, D., Jang, G., Brasch, J., Um, J. W., & Ko, J. (2025) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2025.102772 · Cited by 3
“Peptides were identified using ProLuCID in the Integrated Proteomics Pipeline software (Xu et al., 2015) and IP2 (www.integratedproteomics.com), with the following parameters: precursor mass error, 25 ppm; fragment ion mass error, 200 ppm; protease, trypsin, with two potential missed cleavages;…”
Fantin, R. F., Abeijón, C., Pereira, D. B., Fujiwara, R. T., Bueno, L. L., & Campos‐Neto, A. (2022) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed7100314 · Cited by 3
Cho, U. H., & Hetzer, M. W. (2023) · eLife · doi:10.7554/elife.89066.2 · Cited by 3
Vitorino, F. N. D. L., Levy, M. J., Wailemann, R. A. M., Lopes, M. D. C., Silva, M. L., Sardiu, M. E., Garcia, B. A., Motta, M. C. M., Oliveira, C. C., Armelin, H. A., et al. (2023) · Journal of Cell Science · doi:10.1242/jcs.260989 · Cited by 3
Software Options for the Analysis of MS-Proteomic Data
Yadav, A., Marini, F., Cuomo, A., & Bonaldi, T. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1641-3_3 · Cited by 2
Huang, H., Ge, B., Zhang, S., Li, J., Sun, C., Yue, T., & Huang, F. L. (2019) · Materials · doi:10.3390/ma12030349 · Cited by 3
“After that, the TAMRA labeled bR was further characterized using uv-vis and fluorescence spectrophotometry and the labeling sites of bR were identified using tryptic-digested mass spectrum analysis [27].”
MethodNguyen, K. K., Thurmond, S., Hai, R., & Genereux, J. C. (2019) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-019-01921-z · Cited by 3
Metadata
- Authors
- Xu, T., Park, S. K., Venable, J. D., Wohlschlegel, J. A., Diedrich, J. K., Cociorva, D., Lu, B., Liao, L., Hewel, J., Han, X., Wong, C. C. L., Fonslow, B., Delahunty, C., Gao, Y., Shah, H., & Yates, J. R.
- Affiliations
- Scripps Research Institute (US)
- Corresponding author
- Yates, J.R.
- ORCID
- Venue
- Journal of Proteomics
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 129
- Pages
- 16-24
- ISSN
- 1874-3919 (ISSN-L)
- PMC
- PMC4630125
- OpenAlex
- W2182963873
- Cited by
- 511
- References
- 51
- Citations by year
- 2026: 23 · 2025: 41 · 2024: 65 · 2023: 45 · 2022: 51 · 2021: 56 · 2020: 56 · 2019: 60 · 2018: 43 · 2017: 46 · 2016: 22 · 2015: 3
- FWCI
- 16.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Proteomics (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- NIH (5U01 DE016267-04, 5R01 HL079442-04, R01 MH067880, P41 GM103533)
- NHLBI (HHSN268201000035C)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- peptide identification, tandem mass spectrometry, SEQUEST, Z-score
- MeSH terms
- Algorithms, Amino Acid Sequence, Molecular Sequence Data, Pattern Recognition, Automated, Peptide Mapping, Proteins, Sensitivity and Specificity, Software, Reproducibility of Results, Sequence Analysis, Protein, Databases, Protein, Tandem Mass Spectrometry, Data Mining
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