Journal of Computer-Aided Molecular Design

, Volume 26, Issue 11, pp 1267–1275 | Cite as

Identification of tissue-specific targeting peptide

  • Eunkyoung Jung
  • Nam Kyung Lee
  • Sang-Kee Kang
  • Seung-Hoon Choi
  • Daejin Kim
  • Kisoo Park
  • Kihang Choi
  • Yun-Jaie Choi
  • Dong Hyun Jung


Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide “DKNLQLH” was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.


Machine learning Partial least squares Artificial neural network Bayesian Support vector machine Tissue-specific targeting peptide ROC score 



This research is supported by National Research Foundation of Korea (NRF), Korea government (MEST) (Project No. 2011-0029416). We thank Accelrys Korea for the support of SciTegic Pipeline Pilot and Discovery Studio software, and acknowledge the assistance of BioMedES (

Supplementary material

10822_2012_9614_MOESM1_ESM.docx (104 kb)
Supplementary material 1 (DOCX 103 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Eunkyoung Jung
    • 1
  • Nam Kyung Lee
    • 2
  • Sang-Kee Kang
    • 2
  • Seung-Hoon Choi
    • 1
  • Daejin Kim
    • 1
  • Kisoo Park
    • 1
  • Kihang Choi
    • 3
  • Yun-Jaie Choi
    • 2
  • Dong Hyun Jung
    • 1
  1. 1.Insilicotech Co. Ltd.Bundang-Gu, Seongnam-ShiKorea
  2. 2.School of Agriculture BiotechnologySeoul National UniversityKwanak-gu, SeoulKorea
  3. 3.Department of ChemistryKorea UniversitySeongbuk-Gu, SeoulKorea

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