Example of using PySpark to find ligand interaction fingerprint¶

Demo how to calculate ligand-polymer interaction data and maps it to polymer chains.

Imports and variables¶

In [2]:

from pyspark import SparkConf, SparkContext
from mmtfPyspark.io import mmtfReader
from mmtfPyspark.interactions import InteractionFilter, InteractionFingerprinter

# Create variables
APP_NAME = "MMTF_Spark"

# Configure Spark
conf = SparkConf().setAppName(APP_NAME).setMaster("local[*]")
sc = SparkContext(conf=conf)

Download 1OHR structure¶

In [2]:

pdb = mmtfReader.download_mmtf_files(['1OHR'], sc)

Find interactions of small molecules (except water)¶

In [3]:

interactionFilter = InteractionFilter()
interactionFilter.set_distance_cutoff(4.0)
interactionFilter.set_query_groups(False, "HOH") # ignore water interactions

interactions = InteractionFingerprinter.get_ligand_polymer_interactions(pdb, interactionFilter)
interactions.toPandas().head(10)

Out[3]:

	structureChainId	queryLigandId	queryLigandNumber	queryLigandChainId	targetChainId	groupNumbers	sequenceIndices	sequence	interactingChains
0	1OHR.A	1UN	201	A	A	[25, 27, 28, 29, 30, 49, 50, 80, 81, 82, 84]	[24, 26, 27, 28, 29, 48, 49, 79, 80, 81, 83]	PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...	2
1	1OHR.B	1UN	201	A	B	[8, 23, 25, 27, 28, 29, 30, 32, 47, 48, 49, 50...	[7, 22, 24, 26, 27, 28, 29, 31, 46, 47, 48, 49...	PQITLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKM...	2

Terminate Spark¶

In [3]:

sc.stop()

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