Chapter 10
Applications of Molecular Dynamics
Simulations in Computational Toxicology
Sugunadevi Sakkiah, Rebecca Kusko, Weida Tong and Huixiao Hong
Abstract Computational toxicology is a discipline seeking to computationally
model and predict toxicity of chemicals including drugs, food additives, and other
environmental chemicals. Risk assessment of chemicals using current in vitro or
in vivo experimental methods is at best time-consuming and expensive. Computational toxicology seeks to accelerate this process and decrease the cost by predicting
the risk of chemicals to humans and animals. Molecular dynamics (MD) simulation,
an emerging computational toxicology technique, characterizes the interactions of
chemicals with biomolecules such as proteins and nucleic acids. This chapter will
give a brief review both of available software tools for MD simulations and also
how to apply these software tools to computational toxicology challenges. We also
summarize key protocols to run MD simulations.
Keywords MD simulations · Computational toxicology · In silico toxicology ·
AMBER · GROMACS · NAMD · Desmond
S. Sakkiah · W. Tong · H. Hong (B)
National Center for Toxicological Research, US Food and Drug Administration,
Jefferson, AR, USA
e-mail: Huixiao.hong@fda.hhs.gov
S. Sakkiah
e-mail: Suguna.Sakkiah@fda.hhs.gov
W. Tong
e-mail: Weida.Tong@fda.hhs.gov
R. Kusko
Immuneering Corporation, Cambridge, MA 02142, USA
e-mail: bkusko@immuneering.com
© This is a U.S. government work and not under copyright protection in the U.S.; foreign
copyright protection may apply 2019
H. Hong (ed.), Advances in Computational Toxicology, Challenges and Advances
in Computational Chemistry and Physics 30,
https://doi.org/10.1007/978-3-030-16443-0_10
181
Applications of Molecular Dynamics
Simulations in Computational Toxicology
Sugunadevi Sakkiah, Rebecca Kusko, Weida Tong and Huixiao Hong
Abstract Computational toxicology is a discipline seeking to computationally
model and predict toxicity of chemicals including drugs, food additives, and other
environmental chemicals. Risk assessment of chemicals using current in vitro or
in vivo experimental methods is at best time-consuming and expensive. Computational toxicology seeks to accelerate this process and decrease the cost by predicting
the risk of chemicals to humans and animals. Molecular dynamics (MD) simulation,
an emerging computational toxicology technique, characterizes the interactions of
chemicals with biomolecules such as proteins and nucleic acids. This chapter will
give a brief review both of available software tools for MD simulations and also
how to apply these software tools to computational toxicology challenges. We also
summarize key protocols to run MD simulations.
Keywords MD simulations · Computational toxicology · In silico toxicology ·
AMBER · GROMACS · NAMD · Desmond
S. Sakkiah · W. Tong · H. Hong (B)
National Center for Toxicological Research, US Food and Drug Administration,
Jefferson, AR, USA
e-mail: Huixiao.hong@fda.hhs.gov
S. Sakkiah
e-mail: Suguna.Sakkiah@fda.hhs.gov
W. Tong
e-mail: Weida.Tong@fda.hhs.gov
R. Kusko
Immuneering Corporation, Cambridge, MA 02142, USA
e-mail: bkusko@immuneering.com
© This is a U.S. government work and not under copyright protection in the U.S.; foreign
copyright protection may apply 2019
H. Hong (ed.), Advances in Computational Toxicology, Challenges and Advances
in Computational Chemistry and Physics 30,
https://doi.org/10.1007/978-3-030-16443-0_10
181