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碱基对和肽的相互作用能与极化率的密度泛函理论和信息论方法研究

A Density Functional Theory and Information-Theoretic Approach Study of Interaction Energy and Polarizability for Base Pairs and Peptides.

作者信息

Zhao Dongbo, Liu Shubin, Chen Dahua

机构信息

Institute of Biomedical Research, Yunnan University, Kunming 650500, China.

Research Computing Center, University of North Carolina, Chapel Hill, NC 27599-3420, USA.

出版信息

Pharmaceuticals (Basel). 2022 Jul 28;15(8):938. doi: 10.3390/ph15080938.

Abstract

Using density functional theory (DFT) and the information-theoretic approach (ITA) quantities to appreciate the energetics and properties of biopolymers is still an unaccomplished and ongoing task. To this end, we studied the building blocks of nucleic acid base pairs and small peptides. For base pairs, we have dissected the relative importance of energetic components by using two energy partition schemes in DFT. Our results convincingly show that the exchange-correlation effect predominantly governs the molecular stability of base pairs while the electrostatic potential plays a minor but indispensable role, and the steric effect is trivial. Furthermore, we have revealed that simple density-based ITA functions are in good relationships with molecular polarizabilities for a series of 30 hydrogen-bonded base pairs and all 20 natural -amino acids, 400 dipeptides, and 8000 tripeptides. Based on these lines, one can easily predict the molecular polarizabilities of larger peptides, even proteins as long as the total molecular wavefunction is available, rather than solving the computationally demanding coupled-perturbed Hartree-Fock (CPHF) equation or its DFT counterpart coupled-perturbed Kohn-Sham (CPKS) equation.

摘要

利用密度泛函理论(DFT)和信息论方法(ITA)的量来评估生物聚合物的能量学和性质仍然是一项未完成且仍在进行的任务。为此,我们研究了核酸碱基对和小肽的组成单元。对于碱基对,我们通过在DFT中使用两种能量划分方案剖析了能量成分的相对重要性。我们的结果令人信服地表明,交换相关效应主要决定碱基对的分子稳定性,而静电势起着次要但不可或缺的作用,空间效应微不足道。此外,我们发现基于简单密度的ITA函数与一系列30个氢键碱基对以及所有20种天然氨基酸、400种二肽和8000种三肽的分子极化率具有良好的关系。基于这些结果,只要有总分子波函数,人们就可以轻松预测更大肽甚至蛋白质的分子极化率,而无需求解计算量很大的耦合微扰哈特里 - 福克(CPHF)方程或其DFT对应方程耦合微扰科恩 - 沙姆(CPKS)方程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5f4/9415587/bb0814994aab/pharmaceuticals-15-00938-g001.jpg

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