create fingerprints for polymers
Project description
polymerfingerprint
origin
The Polymerfingerprint is a decoder for SMILES of polymer monomer units specialised for machine learning and the product
of a prior scientific study "Fingerprint applicable for machine learning tested on LCST behavior of polymers".
Please cite us under https://doi.org/10.1016/j.xcrp.2023.101553 upon using the code or the data generated with it.
A tutorial to redo the study is available as "Protocol for creating representations of molecular structures
using a polymer-specific decoder" (https://doi.org/10.1016/j.xpro.2024.103055)
Use cases
- creating fingerprints of homo-, or random copolymers
- the polymerfingerprint consists of morgan and atom pair fingerprints by default
- constituting fingerprints can be added removed or swapped out
- reducing these sets to gain a concise representation for machine learning
- reducing a new set of polyfingerprints like a prior one to make them comparable and predictable in models trained solely on the first set
- checking validity of SMILES and parsing them to a PSMILES format and vice versa
Example for creating a reducing a fingerprint set
import polymerfingerprint as pfp
# the create fingerprint function can take dataframes or lists of molecules. These two serve just as examples
a_polyfingerprint = pfp.create_pfp(end_units={"start": "[C](C)(C)(C#N)", "end": "[S]C(=S)OCC"},
repeating_units={0.53: "[CH2][CH1](OC(=O)C)", 0.47: "[CH2][CH](N1C(=O)CCCCC1)"},
mol_weight=35370,
fp_size=2048)
b_polyfingerprint = pfp.create_pfp(end_units={"start": "[C](C=C)(C)(C#N)", "end": "[S]C(=S)OCCCC"},
repeating_units={0.53: "[CH2][CH1](OC(=O)CC)", 0.47: "[CH2][CH](N1C(=O)CCC1)"},
mol_weight=35370, fp_size=2048)
# create a list of polymerfingerprints
list_of_pfps = [a_polyfingerprint, b_polyfingerprint]
reduced_set = pfp.reduce_fp_set(∗list_of_pfps)
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