Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein-protein binding free energies and re-rank binding poses generated by protein-protein docking.

By Fu Chen, Hui Liu, Huiyong Sun, P. Pan, Youyong Li, Dan Li, Tingjun Hou. Physical Chemistry, Chemical Physics - PCCP, 2016

418 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1d98329de035734e4a7d6d4cf0a555cb2d95acc3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Junmei Wang
2. John C. Dearden

In Materials Chemistry

1. Ray Luo
2. Tingjun Hou
3. Hui Liu
4. Junmei Wang

In Molecular Biology

1. Gaoqi Weng
2. Ray Luo
3. Tingjun Hou
4. Feng Zhu
5. Zhe Wang
6. Hui Liu
7. Li Xiao
8. D'Artagnan Greene

Citations in the corpus

• HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA (2019, result): “According to the assessment results reported by our previous study (25), MM / GBSA achieved better results not only in predicting the binding affinities but also in recognizing the near-native binding modes for PPIs than the tested scoring functions.”
• Recent Developments and Applications of the MMPBSA Method (2018, background): “…efforts focused on HIV viruses, including HIV-1 protease (Li D. et al., 2014; Tzoupis et al., 2014; Chen J. Z. et al., 2015; Meher and Wang, 2015; Chen, 2016; Hu et al., 2016; Sroczynski et al., 2016; Xanthopoulos et al., 2016), gp120 (Wang J. H. et al., 2015), gp41 (Song et al., 2014), reverse…”