Sun Shengjie, Lopez Juan A, Xie Yixin, Guo Wenhan, Liu Dongfang, Li Lin
Computational Science Program, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Department of Computer Science, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Comput Struct Biotechnol J. 2022 Mar 24;20:1580-1583. doi: 10.1016/j.csbj.2022.03.022. eCollection 2022.
The electrostatic features of highly charged biomolecules are crucial and challenging tasks in computational biophysics. The electrostatic calculations by traditional implicit solvent methods are efficient but have difficulties on highly charged biomolecules. We have developed a Hybridizing Ion Treatment (HIT) tool, which successfully hybridizes the explicit ions and implicit solvation model to accurately calculate the electrostatic potential for highly charged biomolecules. Here we implemented the HIT tool into a web server. In this study, a training set was prepared to optimize the number of frames for the HIT web server. The results on tubulins, DNAs, and RNAs, reveal the mechanisms for the motor proteins, DNA of HIV, and tRNA. This HIT web server can be widely used to study highly charged biomolecules, including DNAs, RNAs, molecular motors, and other highly charged biomolecules.
高电荷生物分子的静电特性是计算生物物理学中的关键且具有挑战性的任务。传统隐式溶剂方法进行的静电计算效率较高，但在处理高电荷生物分子时存在困难。我们开发了一种杂交离子处理（HIT）工具，它成功地将显式离子与隐式溶剂化模型相结合，以准确计算高电荷生物分子的静电势。在此，我们将HIT工具实现到一个网络服务器中。在本研究中，准备了一个训练集来优化HIT网络服务器的帧数。在微管蛋白、DNA和RNA上的结果揭示了驱动蛋白、HIV的DNA和转运RNA的机制。这个HIT网络服务器可广泛用于研究高电荷生物分子，包括DNA、RNA、分子马达和其他高电荷生物分子。
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