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绝对结合自由能计算:关于计算蛋白配体相互作用的评分准确性。

Absolute binding free energy calculations: on the accuracy of computational scoring of protein-ligand interactions.

机构信息

Department of Chemistry, University of Southern California, Los Angeles, California 90089-1062, USA.

出版信息

Proteins. 2010 May 15;78(7):1705-23. doi: 10.1002/prot.22687.

Abstract

Calculating the absolute binding free energies is a challenging task. Reliable estimates of binding free energies should provide a guide for rational drug design. It should also provide us with deeper understanding of the correlation between protein structure and its function. Further applications may include identifying novel molecular scaffolds and optimizing lead compounds in computer-aided drug design. Available options to evaluate the absolute binding free energies range from the rigorous but expensive free energy perturbation to the microscopic linear response approximation (LRA/beta version) and related approaches including the linear interaction energy (LIE) to the more approximated and considerably faster scaled protein dipoles Langevin dipoles (PDLD/S-LRA version) as well as the less rigorous molecular mechanics Poisson-Boltzmann/surface area (MM/PBSA) and generalized born/surface area (MM/GBSA) to the less accurate scoring functions. There is a need for an assessment of the performance of different approaches in terms of computer time and reliability. We present a comparative study of the LRA/beta, the LIE, the PDLD/S-LRA/beta, and the more widely used MM/PBSA and assess their abilities to estimate the absolute binding energies. The LRA and LIE methods perform reasonably well but require specialized parameterization for the nonelectrostatic term. The PDLD/S-LRA/beta performs effectively without the need of reparameterization. Our assessment of the MM/PBSA is less optimistic. This approach appears to provide erroneous estimates of the absolute binding energies because of its incorrect entropies and the problematic treatment of electrostatic energies. Overall, the PDLD/S-LRA/beta appears to offer an appealing option for the final stages of massive screening approaches.

摘要

计算绝对结合自由能是一项具有挑战性的任务。可靠的结合自由能估计值应该为合理药物设计提供指导。它还应该为我们提供对蛋白质结构与其功能之间相关性的更深入理解。进一步的应用可能包括识别新的分子支架和优化计算机辅助药物设计中的先导化合物。评估绝对结合自由能的可用选项范围从严格但昂贵的自由能微扰到微观线性响应近似(LRA/beta 版本)和相关方法,包括线性相互作用能(LIE)到更近似且快得多的缩放蛋白偶极 Langevin 偶极子(PDLD/S-LRA 版本)以及不太严格的分子力学泊松-玻尔兹曼/表面积(MM/PBSA)和广义 Born/表面积(MM/GBSA)到不太准确的评分函数。需要评估不同方法在计算机时间和可靠性方面的性能。我们对 LRA/beta、LIE、PDLD/S-LRA/beta 以及更广泛使用的 MM/PBSA 进行了比较研究,并评估了它们估计绝对结合能的能力。LRA 和 LIE 方法表现相当不错,但需要对非静电项进行专门的参数化。PDLD/S-LRA/beta 无需重新参数化即可有效执行。我们对 MM/PBSA 的评估不那么乐观。由于其不正确的熵和静电能的问题处理,该方法似乎提供了绝对结合能的错误估计。总体而言,PDLD/S-LRA/beta 似乎为大规模筛选方法的最后阶段提供了一个有吸引力的选择。

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Angew Chem Int Ed Engl. 2008;47(4):697-700. doi: 10.1002/anie.200704178.

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