Ligorio Raphael F, Grosskopf Paul, Dos Santos Leonardo H R, Krawczuk Anna
Institute of Inorganic Chemistry, University of Goettingen, Tammannstrasse 4, D-37077 Göttingen, Germany.
Departamento de Química, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31270-901 Belo Horizonte, MG, Brazil.
J Phys Chem B. 2024 Aug 22;128(33):7954-7965. doi: 10.1021/acs.jpcb.4c03062. Epub 2024 Jul 8.
Understanding electrostatics and electric properties of macromolecules is crucial in uncovering the intricacies of their behavior and functionality. The precise knowledge of these properties enhances our ability to manipulate and engineer macromolecules for diverse applications, spanning from drug design to materials science. Having that in mind, we present here the GruPol database approach to characterize and accurately predict dipole moments, static polarizabilities, and electrostatic potential of proteins and their subunits. The method involves partitioning of the electron density, calculated at the M06-HF/aug-cc-pVDZ level of theory, of small peptides into predefined building blocks that are averaged over the database. By manipulating and positioning these building blocks, GruPol enables the description of proteins assembled from over nearly 100 residual entries, allowing for efficient and precise computation of the above-mentioned properties across a broad range of proteins. The database enables the user to include solvent effects as well as define protonation states on the protein's backbone to account for pH variations. The precision of the proposed scheme is benchmarked against experimental data for myoglobin species.
了解大分子的静电学和电学性质对于揭示其行为和功能的复杂性至关重要。对这些性质的精确了解增强了我们为各种应用（从药物设计到材料科学）操纵和设计大分子的能力。考虑到这一点，我们在此介绍GruPol数据库方法，用于表征和准确预测蛋白质及其亚基的偶极矩、静态极化率和静电势。该方法涉及将在M06-HF/aug-cc-pVDZ理论水平计算的小肽的电子密度划分为预定义的构建块，并在数据库中进行平均。通过操纵和定位这些构建块，GruPol能够描述由近100个残基条目组装而成的蛋白质，从而能够在广泛的蛋白质范围内高效、精确地计算上述性质。该数据库使用户能够纳入溶剂效应，并定义蛋白质主链上的质子化状态，以考虑pH值变化。所提出方案的精度以肌红蛋白物种的实验数据为基准进行了验证。
