Theoretical analyses of partition coefficient log P and its application to drug-protein interaction

本研究的目的是建立一种基于疏水能和电子能的药物-蛋白质相互作用能定量预测新方法，并将其作为一种新的基于三维结构的定量构效关系（QSAR）应用于合理药物设计领域。预测酶促反应是生物化学和制药科学的一个重要问题，目前已有许多方法用于估计蛋白质-配体复合物的结合特性。QSAR是其中应用最广泛的。然而，在QSAR分析中，靶受体的结构通常被视为“黑箱”。近年来，利用x射线和核磁共振技术已经解决了许多生物重要蛋白质的三维结构。在此背景下，利用分子计算和模拟，我们开发了基于药物及其靶蛋白之间复杂结构的新型QSAR方法。在成功地发现经典QSAR结果与抑制HIV-1蛋白酶和其他蛋白质的分子水平模拟之间的一些逻辑联系后，我们了解了经典QSAR描述子如何在详细的三维配体-蛋白质复合物中被解释。新的QSAR将使我们能够在原子和电子水平上显示在结合过程中发生的事情，并建议我们如何设计药物来控制它们的活动和功能。我们还利用化学信息学和生物通路方法进行了相关研究，以获得单独使用QSAR-分子模拟难以获得的信息。

The aim of this research is to develop a novel quantitative prediction method of drug-protein interaction energy based on the hydrophobic and electronic energies, and to apply it in the field of rational drug design as a novel three-dimensional structure based Quantitative Structure-Activity Relationship (QSAR). Predicting enzymatic reactions is a crucial problem of biochemistry and pharmaceutical sciences, many methods to estimate biding properties for protein-ligand complexes have been reported. QSAR is the most widely used among them. However, a structure of target receptor has been usually treated as a "black box" in QSAR analyses. Recently, many three-dimensional structures of biologically important proteins are been solved by means of X-ray and NMR techniques. In this context, using molecular calculations and simulations, we have developed the novel QSAR method based on a complex structure between a drug and its target protein. Being successful in finding some logical links between results of classical QSAR and molecular level simulation for the inhibition of HIV-1 protease and other proteins, we understand how the classical QSAR descriptors can be interpreted in a detailed three-dimensional ligand-protein complex. The novel QSAR will enable us to show what is occurring in the binding processes at atomic and electronic levels and suggest us how to design drugs to control their activities and functions. We have also carried out the related studies using chemo-informatics and bio-pathway methods to obtain information that is difficult to obtain with QSAR- molecular simulation alone.