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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한약학회 Archives of pharmacal research : a publication of the Pharmaceutical Society of Korea Archives of pharmacal research : a publication of the Pharmaceutical Society of Korea 제30권 제5호
- 발행연도
- 2007.1
- 수록면
- 533 - 542 (10page)
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초록· 키워드
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A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTPIB) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 ${\mu}$M, was selected as a training set. Hypo1, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and ore ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.945, 0.840 and 65.731 , respectively. The best hypothesis (Hypo1) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Caf-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypo1 performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical Companies. The Hypo1 model Correctly Predicted these compounds as being highly active. Finally, decking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the birding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this phar-macophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors.
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