On the accuracy and limits of peptide fragmentation spectrum prediction.
On the accuracy and limits of peptide fragmentation spectrum prediction.
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DOI：
10.1021/ac102272r
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发表时间：
2011-02-01
影响因子：
7.4
通讯作者：
Radivojac, Predrag
中科院分区：
文献类型：
--
作者：
Li, Sujun;Arnold, Randy J.;Tang, Haixu;Radivojac, Predrag
我们估计了广泛使用的碰撞诱导解离（CID）仪器的串联质谱的重现性。使用皮尔逊相关系数作为光谱相似性的度量，我们发现碎片离子强度的实验内重现性非常高（约0.85）。然而，在不同的实验和仪器类型/设置中，相关性降低超过15%（至约0.70）。我们进一步研究了肽片段化光谱的当前预测因子的准确性，发现它们比搜索引擎（例如SEQUEST）通常使用的ad-hoc模型更准确，并且令人惊讶地接近由平均跨实验光谱再现性设定的经验上限（特别是对于电荷+1和电荷+2前体离子）。这些结果提供的证据表明，在建模的准确性方面，预测的肽片段化光谱提供了一个可行的替代光谱库肽鉴定，具有较高的肽覆盖率和较低的存储要求。此外，使用两种不同蛋白酶消化的蛋白质组的五个数据集，我们发现PeptideART（一种数据驱动的机器学习方法）在预测片段化谱方面通常比MassAnalyzer（一种基于肽片段化动力学模型的方法）更准确，但这两种模型都比临时模型更准确。可用性：PeptideART可在www.informatics.indiana.edu/predrag免费获得。
We estimated the reproducibility of tandem mass fragmentation spectra for the widely-used collision-induced dissociation (CID) instruments. Using the Pearson correlation coefficient as a measure of spectral similarity, we found that the within-experiment reproducibility of fragment ion intensities is very high (about 0.85). However, across different experiments and instrument types/setups, the correlation decreases by more than 15% (to about 0.70). We further investigated the accuracy of current predictors of peptide fragmentation spectra and found that they are more accurate than the ad-hoc models generally used by search engines (e.g. SEQUEST) and, surprisingly, approaching the empirical upper limit set by the average across-experiment spectral reproducibility (especially for charge +1 and charge +2 precursor ions). These results provide evidence that, in terms of accuracy of modeling, predicted peptide fragmentation spectra provide a viable alternative to spectral libraries for peptide identification, with a higher coverage of peptides and lower storage requirements. Furthermore, using five data sets of proteome digests by two different proteases, we find that PeptideART (a data-driven machine learning approach) is generally more accurate than MassAnalyzer (an approach based on a kinetic model for peptide fragmentation) in predicting fragmentation spectra, but that both models are significantly more accurate than the ad-hoc models. Availability: PeptideART is freely available at www.informatics.indiana.edu/predrag.
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影响因子：
2.9
作者：
Radivojac, Predrag;Vacic, Vladimir;Haynes, Chad;Cocklin, Ross R.;Mohan, Amrita;Heyen, Joshua W.;Goebl, Mark G.;Iakoucheva, Lilia M.
通讯作者：
Iakoucheva, Lilia M.
DOI：
10.1093/bioinformatics/btn189
发表时间：
2008-07-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Klammer AA;Reynolds SM;Bilmes JA;MacCoss MJ;Noble WS
通讯作者：
Noble WS
影响因子：
4.4
作者：
Li, Yong Fuga;Arnold, Randy J.;Radivojac, Predrag
通讯作者：
Radivojac, Predrag
影响因子：
2
作者：
Liu J;Bell AW;Bergeron JJ;Yanofsky CM;Carrillo B;Beaudrie CE;Kearney RE
通讯作者：
Kearney RE
影响因子：
4.8
作者：
Johnson, RS;Davis, MT;Patterson, SD
通讯作者：
Patterson, SD