Team:NJMU-China/Simulation of Interactions

















Overview



As a preliminary characterization and verification of our parts, we simulated the interactions between proteins (LasR, LacZ), DNA (PlasI) and small molecules (Serotonin, Dopamine, 3-O-C12-HSL, X-gal). We employed homology modeling to predict protein structures from SWISS-MODEL, and constructed the DNA structure. Also, we simulated and visualized the docking through Hdock and Pymol and verified the function of our parts at modeling dimension.



Homology-Modeling of Protein Structures



Function follows form in biology. Knowing the structure of a protein is crucial for understanding how it works in nature, how it would function through interactions or how it could be targeted1.

The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB; RCSB.org), a founding member of the Worldwide Protein Data Bank (wwPDB) partnership , integrates the entire corpus of PDB data with ~40 external biodata resources 2. Based on RCBS PDB, we have obtained the primary 3D structure of both standard LasR and LacZ (beta-galactosidase) complex (Figure 1).





Figure 1. 3D Structure of LasR and LacZ Complex Based on RCSB PDB

Currently, homology modeling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures3. Therefore, we employed homology modelling utilizing SWISS-MODEL to improve the structure model as there are slight differences between our inserted sequences and natural complex’s sequences from RCSB PDB (Figure 2).





Figure 2. 3D Structure of LasR and LacZ Complex Derived from Homology Modeling




Modeling of Small Molecule & DNA Structures



For the docking of both protein-chemical and protein-DNA interaction, we accomplished the modeling of some small molecules (Serotonin, Dopamine, 3-O-C12-HSL, X-gal) and DNA fragment (PlasI). As for the structure of small molecules, we obtained them from PubChem (https://pubchem.ncbi.nlm.nih.gov) (Figure 3)4 .

Figure 3. 3D Structure of Small Molecules (Compounds) Based on PubChem



As for the structure of DNA fragment PlasI, we obtained it from Supercomputing Facility for Bioinformatics & Computational biology, IIT Delhi. (http://www.scfbio-iitd.res.in/main.htm) (Figure 4)5 .





Figure 4. 3D Structure of DNA Fragment, PlasI





Docking of Protein-Molecule and Protein-DNA Interaction



1. Docking of LasR-HSL ~ PlasI

Firstly, we successfully simulated the interactions between LasR and 3-O-C12-HSL using AutoDock (Figure 5A) 6,7. AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure.

Moreover, we simulated the further interactions between the protein complex LasR-HSL and DNA fragment PlasI using HDOCK server from Huang’s Lab (http://huanglab.phys.hust.edu.cn/) (Figure 5B, C) 8,9. With input information for receptor and ligand molecules (either amino acid sequences or Protein Data Bank structures), the server automatically predicts their interaction through a hybrid algorithm of template-based and template-free docking. What’s more, HDOCK also supports protein–RNA/DNA docking with an intrinsic scoring function 10.





Figure 5. 3D Structure of LasR-HSL ~ PlasI Docking



2. Docking of LasR-Serotonin/Dopamine ~ PlasI

For the preliminary verification of our parts, we simulated the interaction between LasR and Serotonin, and further with the DNA fragment PlasI (Figure 6 Left Lane). Alike serotonin, as one of the monoamine neurotransmitters which were assumed to be involved in the neural basis of ASD, dopamine plays a vital role in the development and behavioral impairment in ASD and is listed as one of the biomarkers to choose 11,12. Therefore, we simulated the interaction with Dopamine as well, as a rough estimation of feasibility (Figure 6 Right Lane).





Figure 6. 3D Structure of LasR-Serotonin/Dopamine ~ PlasI Docking

3. Evaluation of the Docking

The evaluation of docking is based on docking scores. Given two individual structures, docking tries to sample all possible binding modes of one structure related to the other. A scoring function is then used to rank the sampled binding modes during and/or after sampling9 . The results show that, the docking of LasR-Serotonin/Dopamine ~ PlasI have scores of -260.09 and -258.87 (the greater the absolute value, the more informative) (Table 1). We also computed the docking score of LasR-HSL ~ PlasI (Positive Control) and LasR ~ PlasI (Negative Control). We found that the docking of LasR-Serotonin/Dopamine ~ PlasI have almost same score with the docking of LasR-HSL ~ PlasI at similar ligand RMSD, while having apparently higher score in comparison with the docking of LasR ~ PlasI.

Interaction Type Docking score Ligand rmsd (Å)
LasR-HSL/PlasI -257.85 135.92
LasR-serotonin/PlasI -260.09 135.53
LasR-dopamine/Plas -258.87 167.30
LasR/PlasI -229.76 174.41

Table 1. Docking Scores of Different Interactions

In all, by simulating and evaluating the interactions between proteins, DNA and small molecules, we preliminarily verified the function of our parts. In the general background of COVID-19 pandemic, many teams are facing difficulties in accessing labs. Our attempts in the modeling of simulation may provide a solution to these teams.



References



1 Goodsell, D. S. & Burley, S. K. RCSB Protein Data Bank tools for 3D structure-guided cancer research: human papillomavirus (HPV) case study. Oncogene 39, 6623-6632, doi:10.1038/s41388-020-01461-2 (2020).
2 Berman, H. M. et al. The Protein Data Bank. Nucleic Acids Res 28, 235-242, doi:10.1093/nar/28.1.235 (2000).
3 Waterhouse, A. et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res 46, W296-W303, doi:10.1093/nar/gky427 (2018).
4 Kim, S. et al. PubChem 2019 update: improved access to chemical data. Nucleic Acids Res 47, D1102-D1109, doi:10.1093/nar/gky1033 (2019).
5 Pant, P., Afshan Shaikh, S. & Jayaram, B. Design and characterization of symmetric nucleic acids via molecular dynamics simulations. Biopolymers 107, doi:10.1002/bip.23002 (2017).
6 Morris, G. M. et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem 30, 2785-2791, doi:10.1002/jcc.21256 (2009).
7 Trott, O. & Olson, A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31, 455-461, doi:10.1002/jcc.21334 (2010).
8 Yan, Y., Tao, H., He, J. & Huang, S. Y. The HDOCK server for integrated protein-protein docking. Nat Protoc 15, 1829-1852, doi:10.1038/s41596-020-0312-x (2020).
9 Yan, Y., Zhang, D., Zhou, P., Li, B. & Huang, S. Y. HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy. Nucleic Acids Res 45, W365-W373, doi:10.1093/nar/gkx407 (2017).
10 Huang, S. Y. & Zou, X. A knowledge-based scoring function for protein-RNA interactions derived from a statistical mechanics-based iterative method. Nucleic Acids Res 42, e55, doi:10.1093/nar/gku077 (2014).
11 Robinson, P. D., Schutz, C. K., Macciardi, F., White, B. N. & Holden, J. J. Genetically determined low maternal serum dopamine beta-hydroxylase levels and the etiology of autism spectrum disorders. Am J Med Genet 100, 30-36, doi:10.1002/ajmg.1187 (2001).
12 DiCarlo, G. E. et al. Autism-linked dopamine transporter mutation alters striatal dopamine neurotransmission and dopamine-dependent behaviors. J Clin Invest 129, 3407-3419, doi:10.1172/JCI127411 (2019).









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