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QSAR Study for β Carboline Derivatives as Inhibitors of Mitogen Activated Protein Kinase-activated Protein Kinase2

Author: HaoMing
Tutor: CongLiNa
School: Dalian University of Technology
Course: Fermentation Engineering
Keywords: QSAR HM SVM SoMFA
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Type: Master's thesis
Year: 2009
Downloads: 1
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Abstract


Rheumatoid arthritis is a kind of chronically systemic autoimmune disease. With furtherstudy, the proinflammatory cytokine TNF-α was originally described as the main factor thatinduced inflammation and led to the damage to cartilage and bone and played a key role inRA. Anti-TNF-α biological therapies have been described and been shown to be effective indiseases such as RA. More recently, many other biological targets have been identified for theinhibition of TNF-α production. The most notable of the target is the kinase p38MAPK.Several papers have demonstrated the effect of P38inhibitors, as well as demonstratingefficacy in RA patients in a clinical study. At present, MK-2has only received a significantdegree of interest for its potential as a target for treatment of RA. It is because MK-2is adirect substrate of the p38α/β kinases and has been linked to TNF-α, IL-6and IFN-γ. At thesame time, a series of β-carboline derivatives have been described as modest inhibitors withhigh activity and good selectivity.33β-carboline derivatives were studied by both2D-QSAR and3D-QSAR methods andthe satisfactory QSAR models were obtained:(1)2D-QSAR: The HM and SVM were utilizedto construct the linear and nonlinear prediction models. The HM statistical result, containing7descriptors, showed that the standard deviation (s), the square of correlation coefficient (r2)and cross-validated square of correlation coefficient (q2) were0.076,0.882and0.771,respectively. The non-linear model by SVM gave better results: for the training set r2=0.949,and for the test set r2=0.855. By comparison the stability with prediction ability of the models,it was found that SVM was a better method for predicting the β-carboline derivatives inhibitoractivity to MK-2.(2)3D-QSAR: The model was built by SoMFA method with r2=0.731,q2=0.686and s=0.388as well as showed a good predictive ability.By discussion the two results of2D-QSAR and3D-QSAR, it is observed that they havegood uniformity, which may offer valuable reference information for designing MK-2inhibitors with high activity and selectivity.

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