• Title/Summary/Keyword: decoy databases

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Evaluation of the Redundancy in Decoy Database Generation for Tandem Mass Analysis (탠덤 질량 분석을 위한 디코이 데이터베이스 생성 방법의 중복성 관점에서의 성능 평가)

  • Li, Honglan;Liu, Duanhui;Lee, Kiwook;Hwang, Kyu-Baek
    • KIISE Transactions on Computing Practices
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    • v.22 no.1
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    • pp.56-60
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    • 2016
  • Peptide identification in tandem mass spectrometry is usually done by searching the spectra against target databases consisting of reference protein sequences. To control false discovery rates for high-confidence peptide identification, spectra are also searched against decoy databases constructed by permuting reference protein sequences. In this case, a peptide of the same sequence could be included in both the target and the decoy databases or multiple entries of a same peptide could exist in the decoy database. These phenomena make the protein identification problem complicated. Thus, it is important to minimize the number of such redundant peptides for accurate protein identification. In this regard, we examined two popular methods for decoy database generation: 'pseudo-shuffling' and 'pseudo-reversing'. We experimented with target databases of varying sizes and investigated the effect of the maximum number of missed cleavage sites allowed in a peptide (MC), which is one of the parameters for target and decoy database generation. In our experiments, the level of redundancy in decoy databases was proportional to the target database size and the value of MC, due to the increase in the number of short peptides (7 to 10 AA). Moreover, 'pseudo-reversing' always generated decoy databases with lower levels of redundancy compared to 'pseudo-shuffling'.

Pharmacophore Design for Anti-inflammatory Agent Targeting Interleukin-2 Inducible Tyrosine Kinase (Itk)

  • Chandrasekaran, Meganathan;Sakkiah, Sugunadevi;Thangapandian, Sundarapandian;Namadevan, Sundaraganesan;Kim, Hyong-Ha;Kim, Yong-Seong;Lee, Keun-Woo
    • Bulletin of the Korean Chemical Society
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    • v.31 no.11
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    • pp.3333-3340
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    • 2010
  • A three dimensional pharmacophore model was generated for the molecules which are responsible for anti-inflammatory activities targeting Interleukin-2 inducible tyrosine kinase (Itk). 16 structurally diverse molecules were selected as training set to generate the hypotheses using Discovery Studio v2.1. The best hypothesis, Hypo1, comprises two hydrogen bond acceptor (HBA), one hydrophobic aromatic (HA), one ring aromatic (RA) and shows high cost difference (63.71), high correlation coefficient (0.97) as well as low RMS deviation (0.81). Hypo1 has been further validated toward a test set, decoy set and Fischer's randomization method. Furthermore, Hypo1 was used to screen NCI and Maybridge databases. Finally, 2 hit molecules were identified as potential leads against Itk, which may be useful for future drug development.