The last data collection procedure was molecular dynamic simulations, aiming to evaluate the behavior of the protein-ligand complex in an aqueous environment. At this stage, only PJ34 (control group) and Sample 4 were subjected to this experiment.
Source: UCSF ChimeraX-1.8 (MENG et al., 2023)
For the simulation, the software was used GROMACS (ABRAHAM et al., 2015) (BEKKER et al., 1993) (BERENDSEN et al., 1995) (HESS et al., 2008) (LINDAHL et al., 2001) (PÁLL et al., 2015) (PRONK et al., 2013) (VAN DER SPOEL et al., 2005) and the CHARMM36 all-atom force field (July 2022) , in addition to the CHARMM-modified TIP3P water model. The ligand topology was prepared in CGenFF ( VANOMMESLAEGHE et al., 2010). The simulation was 10 ns . The files used in the simulation are available in the here.
Source: Authors
The radius of gyration versus time plot depicts the structural compaction or expansion of molecules through the distribution of atoms taking into account the center of mass of the complex. The data are relatively stable, with a sharper decrease around 4 ns, which recovers quickly, and an increasing trend towards the end of the simulation, indicating an expansion.
Source: Authors
The RMSD (Root Mean Square Deviation) graph depicts the displacement of the system in relation to the initial conformation of the simulation. Thus, it is possible to see that, after a period of stability of up to 6 ns, there is a conformational change, which stabilizes at the end of the simulation.
Source: Authors
The SASA (Solvent Accessible Surface Area) plot indicates the exposure of the complex to the solvent (water). There is no obvious trend in the limited time of the simulation.
Source: Authors
The RMSF (Root Mean Square Fluctuation) plot reflects the flexibility of the protein residues during the simulation. There are regions of exotoxin A with more structural stability (around residue 550) and others with more flexibility (around residue 490).
ABRAHAM, Mark James et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX , v. 1, p. 19-25, 2015. Available at: < https://www.sciencedirect.com/science/article/pii/S2352711015000059 >. Accessed on: Dec. 20, 2024
BEKKER, Henk et al. Gromacs-a parallel computer for molecular-dynamics simulations. In: 4th international conference on computational physics (PC 92) . World Scientific Publishing, 1993. p. 252-256. Available at: < https://research.rug.nl/en/publications/gromacs-a-parallel-computer-for-molecular-dynamics-simulations >. Accessed on: 20. Dec. 2024
BERENDSEN, Herman JC; VAN DER SPOEL, David; VAN DRUNEN, Rudi. GROMACS: A message-passing parallel molecular dynamics implementation. Computer physics communications , v. 91, n. 1-3, p. 43-56, 1995. Available at: < https://www.sciencedirect.com/science/article/abs/pii/001046559500042E >. Accessed on: Dec. 20, 2024
HESS, Berk et al. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. Journal of chemical theory and computation , vol. 4, no. 3, p. 435-447, 2008. Available at: < https://pubs.acs.org/doi/abs/10.1021/ct700301q >. Accessed on: 20. Dec. 2024
LINDAHL, Erik; HESS, Berk; VAN DER SPOEL, David. GROMACS 3.0: a package for molecular simulation and trajectory analysis. Molecular modeling annual , v. 7, p. 306-317, 2001. Available at: < https://link.springer.com/article/10.1007/s008940100045 >. Accessed on: December 20, 2024
MENG, Elaine C. et al. UCSF ChimeraX: Tools for structure construction and analysis. Protein Science , vol. 32, no. 11, p. e4792, 2023. Available at: < https://www.tandfonline.com/doi/abs/10.1128/mcb.4.4.642-650.1984 >. Accessed on: 12 Aug. 2024.
PÁLL, Szilárd et al. Tackling exascale software challenges in molecular dynamics simulations with GROMACS. In: Solving Software Challenges for Exascale: International Conference on Exascale Applications and Software, EASC 2014, Stockholm, Sweden, April 2-3, 2014, Revised Selected Papers 2 . Springer International Publishing, 2015. p. 3-27. Available at: < https://link.springer.com/chapter/10.1007/978-3-319-15976-8_1 >. Accessed on: 20. Dec. 2024
PRONK, Sander et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics , vol. 29, no. 7, p. 845-854, 2013. Available at: < https://academic.oup.com/bioinformatics/article/29/7/845/253065?login=false >. Accessed on: 20. Dec. 2024
VAN DER SPOEL, David et al. GROMACS: fast, flexible, and free. Journal of computational chemistry , v. 26, n. 16, p. 1701-1718, 2005. Available at: < https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.20291 >. Accessed on: Dec. 20, 2024
VANOMMESLAEGHE, Kenno et al. CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. Journal of computational chemistry , vol. 31, no. 4, p. 671-690, 2010. Available at: < https://pmc.ncbi.nlm.nih.gov/articles/PMC2888302/ >. Accessed on: 20. Dec. 2024
Comentarios