Script is an attempt to use principal component analysis (PCA) to identify key characteristics allowing to differ 'efficient' (working) reactions from 'inefficient' (not-working) ones.
For a random sample of chemical compounds, script employs retrosynthetic transforms developed at NU, to generate a space of all possible reactions. Then, it performs PCA for a predefined set of reaction descriptors.
Currently about a 100 of molecular descriptors are available. For each reaction a sum of values of a given molecular descriptor is calculated separately for its reactants and products. Compounds which H-depleted molecular graphs contains a single atom only (e.g. water 'O') are excluded, as many topological descriptors are not defined for them.
Each such a pair is treated as reaction descriptor corresponding to a given molecular descriptor.
To run the script type (currently all arguments are optional):
rxnpca.py --size <size> --seed <seed> --selection-type <type>
where
-
size
Sample size, i.e. number of chemicals for which reactions will be generated. Defaults to 1000.
-
seed
Pseudo-random number generator seed. Default to
None, meaning that current system time will be used. -
type
Selection method of reactions sharing the same product. Available choices are:
all: all available reactions will be selected,random: a random pair of published and unpublished reactions will be selected for each product,popular: a pair of published and unpublished reactions having the highest value of popularity index will be picked. If absent, default toall.