Analysis parameters

These are parameters to set up the analysis package of the Platform.

List of aquaPELE parameters:

List of examples:

analyse

  • Description: Whether to run or not the analysis at the end of the simulation.

  • Type: Boolean

  • Default: True

See also

only_analysis, Example 1

only_analysis

  • Description: Analyze an existing PELE simulation without running a new one from scratch.

  • Type: Boolean

  • Default: False

Note

We recommend adding the path to the simulation you want to analyse using the working_folder flag.

See also

analyse, Example 2

bandwidth

  • Description: Sets the cluster size for the clustering algorithm. If it is set to “auto” the software automatically will choose a right value

  • Type: Float or auto

  • Default: auto

Note

Note that auto mode will only run when using the Mean Shift algorithm as clustering method. Although it is the default method and the only one that is recommended, there are other clustering methods implemented in the Platform (check advanced parameters to get further information).

Note

When it is set to auto, it will select the best bandwidth value to cover the percentage of all explored points that is set with the clustering_coverage parameter.

See also

clustering_coverage, Example 2

max_top_clusters

  • Description: Sets the maximum number of clusters to be selected as top.

  • Type: Integer

  • Default: 8

See also

Example 2

top_clusters_criterion

  • Description: Sets the method of selecting top clusters, we can choose one of:

    • total_25_percentile - total energy 25th percentile

    • total_5_percentile - total energy 5th percentile

    • total_mean - total energy mean

    • total_min - total energy min

    • interaction_25_percentile - interaction energy 25th percentile

    • interaction_5_percentile - interaction energy 5th percentile

    • interaction_mean - interaction energy mean

    • interaction_min - interaction energy min

    • population - cluster population

  • Type: String

  • Default: interaction_25_percentile

See also

Example 2

cluster_representatives_criterion

  • Description: Sets method of selecting representative structures for each cluster, you can choose one of:

    • total_25_percentile - total energy 25th percentile

    • total_5_percentile - total energy 5th percentile

    • total_mean - total energy mean

    • total_min - total energy min

    • interaction_25_percentile - interaction energy 25th percentile

    • interaction_5_percentile - interaction energy 5th percentile

    • interaction_mean - interaction energy mean

    • interaction_min - interaction energy min

  • Type: String

  • Default: interaction_min

See also

Example 2

max_top_poses

  • Description: Sets the maximum number of top poses to be retrieved.

  • Type: Integer

  • Default: 100

See also

Example 2

min_population

  • Description: Sets the minimum population that selected clusters must fulfil. It takes a value between 0 and 1. The default value of 0.01 implies that all selected clusters need to have a population above 1% of the total amount of sampled poses.

  • Type: Float

  • Default: 0.01

See also

Example 2

clustering_coverage

  • Description: Sets the minimum percentage of points that needs to be assigned to a top cluster when running mean shift clustering with automated bandwidth. Thus, clustering bandwidth will keep increasing once covering the coverage percentage that is defined.

  • Type: Float

  • Default: 0.75

Note

Note that this parameter is only used when the auto bandwidth mode is set.

See also

bandwidth, Example 3

Example 1

In this example we set an induced fit docking simulation with 30 computation cores. Besides, we disable the analysis package so the simulation will run but it will not be analyzed.

# Required parameters
system: 'system.pdb'
chain: 'L'
resname: 'LIG'

# General parameters
cpus: 30
seed: 2021

# Package selection
induced_fit_fast: True

# Analysis parameters
analyse: False

Example 2

In this example we set an induced fit docking simulation with 30 computation cores. However, instead of running the whole simulation from scratch, we ask the analyze an existing simulation with the only_analysis option. It is a useful feature when we want to reanalyze a previous simulation changing some parameters, like shown below.

# Required parameters
system: 'system.pdb'
chain: 'L'
resname: 'LIG'

# General parameters
cpus: 30
seed: 2021

# Package selection
induced_fit_fast: True

# Analysis parameters
only_analysis: True
bandwidth: 8
max_top_clusters: 12
top_clusters_criterion: "population"
cluster_representatives_criterion: "interaction_mean"
max_top_poses: 20
min_population: 0.005

Example 3

In this example we set an induced fit docking simulation with 30 computation cores. For the analysis, we rely on the default bandwidth parameter, which is auto. This option finds the right clustering bandwidth for the Mean Shift algorithm according to the clustering_coverage. Thus, the right bandwidth is selected to include inside top cluster selection, at least, the percentage of points that is supplied with the clustering_coverage parameter.

# Required parameters
system: 'system.pdb'
chain: 'L'
resname: 'LIG'

# General parameters
cpus: 30
seed: 2021

# Package selection
induced_fit_fast: True

# Analysis parameters
only_analysis: True
working_folder: "LIG_Pele"
clustering_coverage: 0.60
bandwidth: 8
max_top_clusters: 12
top_clusters_criterion: "population"
cluster_representatives_criterion: "interaction_mean"
max_top_poses: 20
min_population: 0.005