Analysis of the interactions between GMF and Arp2/3 complex in two binding sites by molecular dynamics simulation

2018 ◽  
Vol 496 (2) ◽  
pp. 529-535 ◽  
Author(s):  
A. Popinako ◽  
M. Antonov ◽  
D. Dibrova ◽  
A. Chemeris ◽  
O.S. Sokolova
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Binding Sites ◽  
Dynamics Simulation

scholarly journals The Human TSHβ Subunit Proteins and Their Binding Sites on the TSH Receptor Using Molecular Dynamics Simulation

Endocrinology ◽  
2020 ◽  
Vol 161 (9) ◽  
Author(s):  
Mihaly Mezei ◽  
Ramkumarie Baliram ◽  
M Rejwan Ali ◽  
Mone Zaidi ◽  
Terry F Davies ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Hydrogen Bonding ◽  
Molecular Dynamics Simulation ◽  
Binding Sites ◽  
Dynamics Simulation ◽  
Tsh Receptor ◽  
Rich Region ◽  
Monomeric Proteins ◽  
Insight Into

Abstract To gain further insight into the binding of the normal and variant human TSHβ subunits (TSHβ and TSHβv), we modeled the 2 monomeric proteins and studied their interaction with the TSH receptor ectodomain (TSHR-ECD) using molecular dynamics simulation Furthermore, analyzed their bioactivity in vitro using recombinant proteins to confirm that such binding was physiologically relevant. Examining the interaction of TSHβ and TSHβv with the TSHR-ECD model using molecular dynamic simulation revealed strong binding of these proteins to the receptor ECD. The specificity of TSHβ and TSHβv binding to the TSHR-ECD was examined by analyzing the hydrogen-bonding residues of these subunits to the FSH receptor ECD, indicating the inability of these molecules to bind to the FSH receptors. Furthermore, the modelling suggests that TSHβ and TSHβv proteins clasped the concave surface of the leucine rich region of the TSHR ECD in a similar way to the native TSH using dynamic hydrogen bonding. These mutually exclusive stable interactions between the subunits and ECD residues included some high-affinity contact sites corresponding to binding models of native TSH. Furthermore, we cloned TSHβ and TSHβv proteins using the entire coding ORF and purified the flag-tagged proteins. The expressed TSHβ subunit proteins retained bioactivity both in a coculture system as well as with immune-purified proteins. In summary, we showed that such interactions can result in a functional outcome and may exert physiological or pathophysiological effects in immune cells.

scholarly journals Drug Binding Dynamics of the Dimeric SARS-CoV-2 Main Protease, Determined by Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Teruhisa S. KOMATSU ◽  
Noriaki Okimoto ◽  
Yohei M. KOYAMA ◽  
Yoshinori HIRANO ◽  
Gentaro MORIMOTO ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Active Site ◽  
Binding Sites ◽  
Complex Structure ◽  
Drug Binding ◽  
Dynamics Simulation ◽  
Trajectory Data ◽  
Main Protease ◽  
Dynamic Sampling

<div> <div> <div> <p>We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein- ligand complexes and suggest the possibilities of further drug optimisations. <br></p><p><br></p><p><br> </p><div> <div> <div> <p>Raw trajectory data analysed in this paper and movie examples are available at the zenodo repository.<br></p> </div> </div> </div> </div> </div> </div>

scholarly journals Characterizing the Binding Sites for GK Domain of DLG1 and DLG4 via Molecular Dynamics Simulation

2020 ◽  
Vol 7 ◽  
Author(s):  
Hongwei Li ◽  
Qiong Chen ◽  
Changyu Shan ◽  
Chunling Guo ◽  
Xiuming Yang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Binding Sites ◽  
Dynamics Simulation

scholarly journals Drug binding dynamics of the dimeric SARS-CoV-2 main protease, determined by molecular dynamics simulation

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Teruhisa S. Komatsu ◽  
Noriaki Okimoto ◽  
Yohei M. Koyama ◽  
Yoshinori Hirano ◽  
Gentaro Morimoto ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Active Site ◽  
Binding Sites ◽  
Complex Structure ◽  
Drug Binding ◽  
Dynamics Simulation ◽  
Main Protease ◽  
Encounter Complex ◽  
Dynamic Sampling

Abstract We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein–ligand complexes and suggest the possibilities of further drug optimisations.

scholarly journals Drug Binding Dynamics of the Dimeric SARS-CoV-2 Main Protease, Determined by Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Teruhisa S. KOMATSU ◽  
Noriaki Okimoto ◽  
Yohei M. KOYAMA ◽  
Yoshinori HIRANO ◽  
Gentaro MORIMOTO ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Active Site ◽  
Binding Sites ◽  
Complex Structure ◽  
Drug Binding ◽  
Dynamics Simulation ◽  
Trajectory Data ◽  
Main Protease ◽  
Dynamic Sampling

<div> <div> <div> <p>We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein- ligand complexes and suggest the possibilities of further drug optimisations. <br></p><p><br></p><p><br> </p><div> <div> <div> <p>Raw trajectory data analysed in this paper and movie examples are available at the zenodo repository.<br></p> </div> </div> </div> </div> </div> </div>

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