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Design of Novel JNK3 Inhibitors Based on 3D-QSAR In Silico Model

원문정보

초록

영어

c-Jun N-terminal kinase-3 (JNK-3) has been identified as a promising target for neuronal apoptosis and has the effective therapeutic for neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and other CNS disorders. Herein, we report the essential structural and chemical parameters for JNK-3 inhibitors utilizing comparative molecular field similarity indices analysis (CoMSIA) using the derivatives of 3,5-disubstituted quinolines. The best predictions were obtained CoMSIA model (q2=0.834, r2=0.987) and the statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The resulting contour map from 3D-QSAR models might be helpful to design novel and more potent JNK3 derivatives.

목차

Abstract
 1. Introduction
 2. Experimental
  2.1. Inhibitor Data Set
  2.2. Ligand-based Alignment Method
  2.3. Generation of CoMSIA Field
  2.4. Partial Least Square (PLS) Analysis
 3. Results and Discussion
  3.1. CoMSIA Analysis
  3.2. CoMSIA Contour Map
 4. Conclusion
 References

키워드

저자정보

  • Thirumurthy Madhavan Centre for Bioinformatics, Department of Biochemistry, School of life sciences, University of Madras, Guindy campus, Chennai-600025, India.

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