| Autor: |
Shengjie Sun, Juan A. Lopez, Yixin Xie, Wenhan Guo, Dongfang Liu, Lin Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 1580-1583 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2001-0370 |
| DOI: |
10.1016/j.csbj.2022.03.022 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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