Recent Trends in Structure‐Based Drug Design and Energetics

A. Andricopulo, R. Guido, D. Trivella, I. Polikarpov, A. Leitão, C. Montanari
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引用次数: 2

Abstract

The integration of cheminformatics tools, thermodynamic data, and structural information play a major role in the drug discovery process. Altogether, these methods can describe the molecular forces that govern the affinity and selectivity of bioactive molecules for their macromolecular targets. By being able to uncover the relationships between structure and energetics when using high-resolution structural information and modern biophysical methods, one can fulfill the challenge of correctly interpreting drug–macromolecular interactions. These interactions are prone to be unveiled and scrutinized when structure-based drug design is applied to a known three-dimensional (3D) structure of a given protein. If fully integrated with structure-based ligand design in an iterative way, computational methods can be of invaluable help to describe the ligand–target (cocomplex) formation. Structure-based virtual screening can be used to rapid cherry-pick the best candidates from a large pool of compounds in a chemical library after docking into the active sites of 3D protein structures. To pursue this, the quantification of favorable and unfavorable interactions requires knowledge of the thermodynamics of the interactions. Docking algorithms and molecular dynamics simulations can be used to predict binding energies for positioning ligands in target binding sites, but they only provide information regarded to the prediction of the change in the Gibbs free energy change, which hampers the thoroughly dissection of all other very important thermodynamic parameters—enthalpy, entropy, and heat capacity change. The major goal of this chapter is to show the integration of structure-based drug design with the energetic. Microcalorimetric measurement of the drug–macromolecular interaction is an effective way to enhance the power, the medicinal chemists have on hand, to pursue a knowledge-based approach toward the description of all of the noncovalent bond terms that take place in the cocomplex formation. Keywords: structure-based virtual screening; isothermal titration calorimetry; drug–macromolecular interaction energetics, nuclear receptors; transthyretin amyloidosis inhibitors
基于结构的药物设计和能量学的最新趋势
化学信息学工具、热力学数据和结构信息的集成在药物发现过程中起着重要作用。总之,这些方法可以描述控制生物活性分子对其大分子靶标的亲和力和选择性的分子力。通过使用高分辨率结构信息和现代生物物理方法揭示结构和能量学之间的关系,人们可以完成正确解释药物-大分子相互作用的挑战。当基于结构的药物设计应用于给定蛋白质的已知三维(3D)结构时,这些相互作用很容易被揭示和仔细研究。如果以迭代的方式与基于结构的配体设计完全集成,计算方法可以为描述配体-靶标(共络合物)的形成提供宝贵的帮助。基于结构的虚拟筛选可以在对接到3D蛋白质结构的活性位点后,从化学文库中的大量化合物中快速挑选出最佳候选化合物。为了实现这一点,有利和不利相互作用的量化需要相互作用的热力学知识。对接算法和分子动力学模拟可以用来预测配体在目标结合位点上的结合能,但它们只提供了关于吉布斯自由能变化的预测信息,这阻碍了对所有其他非常重要的热力学参数——焓、熵和热容变化的彻底分析。本章的主要目的是展示基于结构的药物设计与能量的整合。对药物-大分子相互作用的微量热测量是一种有效的方法,可以提高药物化学家的能力,以追求一种基于知识的方法来描述发生在络合物形成中的所有非共价键项。关键词:基于结构的虚拟筛选;等温滴定量热法;药物-大分子相互作用能量学;核受体;转甲状腺素淀粉样变性抑制剂
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