Analytical Science and Technology (분석과학)

The Korean Society of Analytical Sciences (한국분석과학회)
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2D-QSAR analysis for hERG ion channel inhibitors

hERG 이온채널 저해제에 대한 2D-QSAR 분석

  • Received : 2011.12.06
  • Accepted : 2011.12.08
  • Published : 2011.12.25
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Abstract

The hERG (human ether-a-go-go related gene) ion channel is a main factor for cardiac repolarization, and the blockade of this channel could induce arrhythmia and sudden death. Therefore, potential hERG ion channel inhibitors are now a primary concern in the drug discovery process, and lots of efforts are focused on the minimizing the cardiotoxic side effect. In this study, $IC_{50}$ data of 202 organic compounds in HEK (human embryonic kidney) cell from literatures were used to develop predictive 2D-QSAR model. Multiple linear regression (MLR), Support Vector Machine (SVM), and artificial neural network (ANN) were utilized to predict inhibition concentration of hERG ion channel as machine learning methods. Population based-forward selection method with cross-validation procedure was combined with each learning method and used to select best subset descriptors for each learning algorithm. The best model was ANN model based on 14 descriptors ($R^2_{CV}$=0.617, RMSECV=0.762, MAECV=0.583) and the MLR model could describe the structural characteristics of inhibitors and interaction with hERG receptors. The validation of QSAR models was evaluated through the 5-fold cross-validation and Y-scrambling test.

hERG (human ether-a-go-go related gene) 이온채널은 심장 재분극의 중요 요소이며 이 채널의 저해제는 부정맥과 돌연사를 유발할 수 있다. 따라서, 신약개발과정에서 후보물질이 hERG 이온채널의 잠재적인 저해제일 경우에는 심장독성 부작용을 유발하므로, 이를 최소화하고자 많은 노력이 집중되고 있다. 본 연구는 HEK(인간 배아 신장)세포에서 얻은 202개 유기화합물의 $IC_{50}$ 데이터를 이용하여 2차원 구조-활성의 정량적 관계(2D-QSAR)방법으로 예측하는 모델을 개발하였다. hERG이온채널 저해제의 기계 학습방법으로는 다중선형회귀(Multiple Linear Regression), 서포트 벡터 머신(Support Vector Machine: SVM)방법과 인공신경망(Artificial Neural Network)방법이며, 교차검증을 적용한 모집단 기반 전진선택(forward selection)방법과 결합하여 각 학습모델에 적합한 최적의 표현자들을 결정하였다. 가장 우수한 방법은 14종의 표현자를 사용한 인공신경망방법($R^2_{CV}$=0.617, RMSECV=0.762, MAECV=0.583)이었고, 다중선형회귀방법을 통해서 hERG이온채널 저해물질의 구조적 특징과 수용체와의 상호작용을 설명할 수 있다. QSAR모델의 검증은 교차검증과 Y-scrambling test방법으로 수행하였다.

Keywords

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