References

  1. Allen, M. P. (2004). Introduction to molecular dynamics simulation. In N. Attig, K. Binder, H. Grubmüller, & K. Kremer (Eds.), Computational soft matter: From synthetic polymers to proteins (pp. 1–28). John von Neumann Institute for Computing. https://dasher.wustl.edu/chem478/reading/md-intro-2.pdf
  2. Heilmann, N., Wolf, M., & de Groot, B. L. (2020). Sampling of the conformational landscape of small proteins with Monte Carlo methods. Scientific Reports, 10(1), Article 18211. https://doi.org/10.1038/s41598-020-75239-7
  3. Jana, A. K. (2022). Introduction to numerical method and process simulation. In Numerical methods for process simulation (pp. 1–20). Cambridge University Press.
  4. Paquet, E., & Viktor, H. L. (2015). Molecular dynamics, Monte Carlo simulations, and Langevin dynamics: A computational review. BioMed Research International, 2015, Article 183918. https://doi.org/10.1155/2015/183918
  5. Salo-Ahen, O. M. H., Alanko, I., Bhadane, R., Bonvin, A. M. J. J., Honorato, R. V., Hossain, S., Juffer, A. H., Kabedev, A., Lahtela-Kakkonen, M., Larsen, A. S., Lescrinier, E., Marimuthu, P., Mirza, M. U., Mustafa, G., Nunes-Alves, A., Pantsar, T., Saadabadi, A., Singaravelu, K., & Vanmeert, M. (2021). Molecular dynamics simulations in drug discovery and pharmaceutical development. Processes, 9(1), Article 71. https://doi.org/10.3390/pr9010071
  6. Schrödinger. (n.d.). Molecular dynamics simulations accelerate the development and optimization of recyclable tire materials [Case study]. Schrödinger, Inc. https://www.schrodinger.com/materials-science/learn/case-studies/molecular-dynamics-simulations-accelerate-development-and-optimization-recyclable/
  7. Tautermann, C. S. (2015). What can we learn from molecular dynamics simulations for GPCR drug design? Computational and Structural Biotechnology Journal, 13, 131–138. https://doi.org/10.1016/j.csbj.2015.02.001