Molecular Modeling Study of JNK1 inhibitors

Abstract

c-Jun N 말단 카이네이즈 (JNK)는 세린, 쓰레오닌 카이네이즈이며 마이토젠에의하여 활성화되는 단백질 카이네이즈의 일종이다 (MAPK). JNK 유사체의 X선 결정구조가 알려져있다. JNK의 대략적인 구성은 MAP 카이네이즈와 유사하다. 특히 ATP가 결합하는 장소의 아미노산 서열은 상동성 90% 이상, 호몰로지 98%이상이다. 따라서 호몰로지 모델링이 유력하다. 이러한 상황에서는 선택성이 대단히 중요하기 때문에, 활성자리를 자세히 연구하는 것이 필요하다. 본 연구에서는 다양한 방법으로 분자를 배열한 다음, CoMFA (Comparative Molecular Filed Analysis)와 CoMSIA (Comparative Molecular Similarity Indices Analysis) 연구를 하였다. 원자-원자의 중접을 이용한 방법으로는 CoMFA의 경우 (q2=0.646 and r2=0.983)를 얻었으며, 파머코포아를 이용한 경우에는 CoMFA의 경우 (q2 = 0.568, r2 = 0.938) 그리고 CoMSIA의 경우 (q2=0.670, r2 = 0.982)의 결과를 얻었다. 또한 x선 결정구조를 이용한 수용체를 template로 활용한 경우에는 리간드의 구조가 수용체속에서 최적화되었다. 이결과, q2 = 0.605, r2 = 0.944 (CoMFA) 그리고, q2 = 0.587, r2 = 0.863 (CoMSIA)의 결과를 얻었다. CoMFA와 CoMSIA의 contour 지도를 분석해 보면, 페닐 그룹의 양전하를 띈 치환제가 유리하고 피리미딘 고리에는 소수성 그룹이 필요하다고 생각된다. 더구나 NCI 데이다베이스를 활용한 가상검색으로 가능성이 있는 화합물의 구조정보를 얻을 수 있었다. 이는 선택적이고 강력한 JNK1 억제제의 유도체를 얻는데 대단히 중요하다.|c-Jun N-terminal Kinases (JNK) are serine threonine protein kinases and members of the mitogen activated protein kinase family (MAPK). The X-ray crystal structures of all three JNK isoforms have been reported. The overall architecture of JNKs is highly similar to that of other MAP kinases. The amino acid sequence identity of the JNK kinases is higher than 90%, with over 98% homology within the ATP binding site. The high homology of the ATP-binding site within JNK’s makes it challenging to design isoform specific ATP-site directed inhibitors. Therefore, designing selective ATP, competitive JNK (1, 2, and 3) inhibitors is still a challenging task. As selectivity is the major issue, our in silico analysis might be the starting point for the synthesis of highly potent and selective JNK1 analogs, and this prompted us to initiate the analysis. The main aim of our study was to optimize the reported selective JNK1 inhibitors (4-anilinopyrimidine derivatives), using three-dimensional quantitative structure activity relationship (3D-QSAR) methods, and also to identify new lead compounds using the receptor based pharmacophore. Selectivity is the key issue, pharmacophore generation using receptor-ligand information could be more realistic and selective. In this work, the most popular 3D-QSAR methods such as, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed using different alignment methods. The ligand-based atom-by atom matching alignment has produced better values for CoMFA (q2=0.646 and r2=0.983), while in CoMSIA it has achieved only lower statistical values. The pharmacophore-based model has produced (q2 = 0.568, r2 = 0.938) and (q2=0.670, r2 = 0.982) for CoMFA and CoMSIA models, respectively. As the model was based on the receptor-guided alignment, all the compounds were optimized within the receptor, resulting in q2 = 0.605 and r2 = 0.944 for CoMFA, and q2 = 0.587 and r2 = 0.863 for CoMSIA. Molecular Dynamic simulation studies suggested that the generated models were consistent with the low energy protein ligand conformation. The CoMFA and CoMSIA contour maps indicated that the substitutions of the electropositive groups in the phenyl ring, and an addition of hydrophobic groups in the pyrimidine ring, are important to enhance the activity of this series. Moreover, the virtual screening analysis against NCI database yields potentials hits and the results obtained would be useful to synthesize selective and highly potent JNK1 analogs.