ScMiles2: A Script to Conduct and Analyze Milestoning Trajectories for Long Time Dynamics.
Alfredo E CardenasAllison HunterHao WangRon ElberPublished in: Journal of chemical theory and computation (2022)
Milestoning is a theory and an algorithm that computes kinetics and thermodynamics at long time scales. It is based on partitioning the (phase) space into cells and running a large number of short trajectories between the boundaries of the cells. The termination points of the trajectories are analyzed with the Milestoning theory to obtain kinetic and thermodynamic information. Managing the tens to hundreds of thousands of Milestoning trajectories is a challenge, which we handle with a python script, ScMiles. Here, we introduce a new version of the python script ScMiles2 to conduct Milestoning simulations. Major enhancements are: (i) post analysis of Milestoning trajectories to obtain the free energy, mean first passage time, the committor function, and exit times; (ii) similar to (i) but the post analysis is for a single long trajectory; (iii) we support the use of the GROMACS software in addition to NAMD; (iv) a restart option; (v) the automated finding, sampling, and launching trajectories from new milestones that are found on the fly; and (vi) support Milestoning calculations with several coarse variables and for complex reaction coordinates. We also evaluate the simulation parameters and suggest new algorithmic features to enhance the rate of convergence of observables. We propose the use of an iteration-averaged kinetic matrix for a rapid approach to asymptotic values. Illustrations are provided for small systems and one large example.
Keyphrases
- depressive symptoms
- induced apoptosis
- molecular dynamics
- cell cycle arrest
- machine learning
- deep learning
- healthcare
- molecular dynamics simulations
- cell proliferation
- cell death
- pi k akt
- signaling pathway
- endoplasmic reticulum stress
- social media
- data analysis
- monte carlo
- psychometric properties
- neural network
- quantum dots