Mulakala Chandrika, Kaznessis Yiannis N
Department of Chemical Engineering and Materials Science, 151 Amundson Hall, 421 Washington Avenue SE, University of Minnesota, Minneapolis, Minnesota 55455, USA.
J Am Chem Soc. 2009 Apr 1;131(12):4521-8. doi: 10.1021/ja807460s.
We present a novel approach for computing biomolecular interaction binding affinities based on a simple path integral solution of the Fokker-Planck equation. Computing the free energy of protein-ligand interactions can expedite structure-based drug design. Traditionally, the problem is seen through the lens of statistical thermodynamics. The computations can become, however, prohibitively long for the change in the free energy upon binding to be determined accurately. In this work, we present a different approach based on a stochastic kinetic formalism. Inspired by Feynman's path integral formulation, we extend the theory to classical interacting systems. The ligand is modeled as a Brownian particle subjected to the effective nonbonding interaction potential of the receptor. This allows the calculation of the relative binding affinities of interacting biomolecules in water to be computed as a function of the ligand's diffusivity and the curvature of the potential surface in the vicinity of the binding minimum. The calculation is thus exceedingly rapid. In test cases, the correlation coefficient between actual and computed free energies is >0.93 for accurate data sets.
我们提出了一种基于福克-普朗克方程的简单路径积分解来计算生物分子相互作用结合亲和力的新方法。计算蛋白质-配体相互作用的自由能可以加速基于结构的药物设计。传统上,这个问题是从统计热力学的角度来看待的。然而,要准确确定结合时自由能的变化,计算可能会变得长得令人望而却步。在这项工作中,我们提出了一种基于随机动力学形式的不同方法。受费曼路径积分公式的启发,我们将该理论扩展到经典相互作用系统。配体被建模为一个受到受体有效非键相互作用势作用的布朗粒子。这使得能够将水中相互作用生物分子的相对结合亲和力计算为配体扩散率和结合最小值附近势表面曲率的函数。因此,计算速度极快。在测试案例中,对于准确的数据集,实际自由能与计算自由能之间的相关系数大于0.93。