San Juan Amor A
Life Sciences Research Division, Korea Institute of Science and Technology, PO Box 131, Cheongryang, Seoul 130-650, South Korea.
Bioorg Med Chem Lett. 2008 Feb 1;18(3):1181-94. doi: 10.1016/j.bmcl.2007.11.134. Epub 2007 Dec 8.
Clinically relevant Lys103Asn (K103N) mutant frequently observed in HIV-1 reverse transcriptase (RT) confers drug resistance. To obtain useful structural information necessary for targeted-inhibitor design, molecular docking combined with 3D-QSAR CoMFA and CoMSIA was applied to a set of 53 structurally diverse HIV-RT inhibitors. Two strategies were applied to generate 3D-QSAR models. The first strategy is the flexibility-based molecular alignment (FMA), similar to receptor-based alignment, which samples the biological space of K103N mutant HIV-RT. FMA was conducted by docking the compounds to four structural data of mutant HIV-RT with PDB codes: 1SV5, 2IC3, 1FKP and 1FKO, which are co-crystallized according to NNRTI inhibitors such as etravirine, HBY-097, nevirapine, and efavirenz. The best superposition of the compounds to the active site of 1FKP structure suggests specific inhibition of nevirapine-resistance. The second strategy is the dataset division which employs the principal component analysis (PCA) to classify the dataset into training and test sets that yields statistically significant and robust models. The PCA design selection tool by the most descriptive compounds (MDC) outperforms the largest minimum distance (LMD) for the present dataset. Overall, the results demonstrated the feasibility of the two strategies to the present case and hold a promise for its general applicability to future QSAR studies. The generated models are predictive based on reproducible values of the predicted compared with experimental activities. Further, the complementary analysis of contour maps to the mutant HIV-RT binding site suggested the anchor points for binding affinity. The present study introduced the concept 'clamp-flex' for the rational design of targeted-inhibitor to overcome the K103N pan-class resistance mutation. The predictive models offer new insights into binding modes involving the hydrophobicity and flexibility of the active site.
在HIV-1逆转录酶（RT）中经常观察到的具有临床相关性的Lys103Asn（K103N）突变会导致耐药性。为了获得靶向抑制剂设计所需的有用结构信息，将分子对接与3D-QSAR CoMFA和CoMSIA相结合，应用于一组53种结构多样的HIV-RT抑制剂。采用两种策略生成3D-QSAR模型。第一种策略是基于柔性的分子比对（FMA），类似于基于受体的比对，它对K103N突变型HIV-RT的生物空间进行采样。FMA是通过将化合物与具有PDB编码的突变型HIV-RT的四个结构数据进行对接来进行的：1SV5、2IC3、1FKP和1FKO，这些数据是根据依曲韦林、HBY-097、奈韦拉平和依非韦伦等非核苷类逆转录酶抑制剂共结晶得到的。化合物与1FKP结构活性位点的最佳叠加表明对奈韦拉平耐药性有特异性抑制作用。第二种策略是数据集划分，它采用主成分分析（PCA）将数据集分为训练集和测试集，从而生成具有统计学意义和稳健性的模型。对于当前数据集，由最具描述性化合物（MDC）的PCA设计选择工具优于最大最小距离（LMD）。总体而言，结果证明了这两种策略在当前案例中的可行性，并有望在未来的QSAR研究中得到广泛应用。生成的模型基于预测值与实验活性的可重复性值具有预测性。此外，对突变型HIV-RT结合位点的等高线图进行的互补分析表明了结合亲和力的锚定点。本研究引入了“钳夹-柔性”概念，用于合理设计靶向抑制剂以克服K103N泛类耐药突变。这些预测模型为涉及活性位点疏水性和柔性的结合模式提供了新的见解。
