提高含金属的配体-受体复合物的FMO结合亲和力预测的准确性。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2023-09-25 DOI:10.1007/s10822-023-00532-2
R. Paciotti, A. Marrone, C. Coletti, N. Re
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引用次数: 0

摘要

对于Au(I)-双卡宾/DNA G-四链体复合物,当存在金属原子时,极化和电荷转移强烈地表征了配体-受体的相互作用。在之前的工作中(J Comput Aided Mol Des2022,36851-866),我们使用RI-MP2/6-31G*理论水平的从头计算FMO2方法和PCM[1]溶剂化方法来计算两种Au(I)-双卡宾衍生物[Au(9-甲基咖啡因-8-亚基)2]+和[Au(1,3-二甲基苯并咪唑-2-亚基)2]+的结合能(ΔEFMO),它们能够与DNA G-四链体基序相互作用。我们发现ΔEFMO和配体-受体对相互作用能(EINT)显示出非常大的负值,这使得与实验数据的直接比较变得困难,并将此问题与高估含有金属原子的片段之间的嵌入电荷转移能有关。在这项工作中,为了提高FMO方法预测金属基配体与DNA G-四链体(Gq)相互作用的结合亲和力的准确性,我们评估了以下计算特征的影响:(i)电子相关性,考虑Hartree-Fock(HF)和后HF方法,即RI-MP2;(ii)二体(FMO2)和三体(FMO3)方法;(iii)基集大小(极化函数和双ζ与三ζ)和(iv)嵌入静电势(ESP)。此外,系统地采用部分筛选方法来模拟每次计算的溶剂筛选效果。我们发现,使用所有原子的屏蔽点电荷计算的ESP(ESP-SPTC)对ΔEFMO和EINT的准确性都有关键影响,消除了对电荷转移能的高估,并导致能量值的大小与典型的实验结合能相当。通过这种计算方法,EINT值比ΔEFMO更准确地描述了金属基粘合剂与DNA Gq的结合效率。因此,要用FMO方法研究含金属体系的结合过程,应考虑采用部分筛选溶剂法结合ESP-SPCT。该计算协议被建议用于含金属的生物系统的FMO计算,特别是当采用默认ESP处理导致可疑结果时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals

Polarization and charge transfer strongly characterize the ligand-receptor interaction when metal atoms are present, as for the Au(I)-biscarbene/DNA G-quadruplex complexes. In a previous work (J Comput Aided Mol Des2022, 36, 851–866) we used the ab initio FMO2 method at the RI-MP2/6-31G* level of theory with the PCM [1] solvation approach to calculate the binding energy (ΔEFMO) of two Au(I)-biscarbene derivatives, [Au(9-methylcaffein-8-ylidene)2]+ and [Au(1,3-dimethylbenzimidazole-2-ylidene)2]+, able to interact with DNA G-quadruplex motif. We found that ΔEFMO and ligand-receptor pair interaction energies (EINT) show very large negative values making the direct comparison with experimental data difficult and related this issue to the overestimation of the embedded charge transfer energy between fragments containing metal atoms. In this work, to improve the accuracy of the FMO method for predicting the binding affinity of metal-based ligands interacting with DNA G-quadruplex (Gq), we assess the effect of the following computational features: (i) the electron correlation, considering the Hartree–Fock (HF) and a post-HF method, namely RI-MP2; (ii) the two (FMO2) and three-body (FMO3) approaches; (iii) the basis set size (polarization functions and double-ζ vs. triple-ζ) and (iv) the embedding electrostatic potential (ESP). Moreover, the partial screening method was systematically adopted to simulate the solvent screening effect for each calculation. We found that the use of the ESP computed using the screened point charges for all atoms (ESP-SPTC) has a critical impact on the accuracy of both ΔEFMO and EINT, eliminating the overestimation of charge transfer energy and leading to energy values with magnitude comparable with typical experimental binding energies. With this computational approach, EINT values describe the binding efficiency of metal-based binders to DNA Gq more accurately than ΔEFMO. Therefore, to study the binding process of metal containing systems with the FMO method, the adoption of partial screening solvent method combined with ESP-SPCT should be considered. This computational protocol is suggested for FMO calculations on biological systems containing metals, especially when the adoption of the default ESP treatment leads to questionable results.

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