Gilson Michael K, Zhou Huan-Xiang
Center for Advanced Research in Biotechnology, University of Maryland Biotechnology Institute, Rockville, Maryland 20850, USA.
Annu Rev Biophys Biomol Struct. 2007;36:21-42. doi: 10.1146/annurev.biophys.36.040306.132550.
Accurate methods of computing the affinity of a small molecule with a protein are needed to speed the discovery of new medications and biological probes. This paper reviews physics-based models of binding, beginning with a summary of the changes in potential energy, solvation energy, and configurational entropy that influence affinity, and a theoretical overview to frame the discussion of specific computational approaches. Important advances are reported in modeling protein-ligand energetics, such as the incorporation of electronic polarization and the use of quantum mechanical methods. Recent calculations suggest that changes in configurational entropy strongly oppose binding and must be included if accurate affinities are to be obtained. The linear interaction energy (LIE) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods are analyzed, as are free energy pathway methods, which show promise and may be ready for more extensive testing. Ultimately, major improvements in modeling accuracy will likely require advances on multiple fronts, as well as continued validation against experiment.
为加速新型药物和生物探针的发现，需要精确计算小分子与蛋白质亲和力的方法。本文回顾了基于物理的结合模型，首先总结了影响亲和力的势能、溶剂化能和构象熵的变化，并进行了理论概述以构建对特定计算方法的讨论框架。报告了在蛋白质-配体能量学建模方面的重要进展，例如电子极化的纳入和量子力学方法的使用。最近的计算表明，构象熵的变化强烈阻碍结合，如果要获得准确的亲和力则必须予以考虑。分析了线性相互作用能（LIE）和分子力学泊松-玻尔兹曼表面积（MM-PBSA）方法，以及自由能路径方法，这些方法显示出前景并且可能已准备好进行更广泛的测试。最终，建模精度的重大提高可能需要在多个方面取得进展，以及持续对照实验进行验证。
