Flat Map Chains Demo¶

Example demonstrateing how to extract protein chains from PDB entries. This example uses a flatMap function to transform a structure to its polymer chains.

Imports¶

In [1]:

from pyspark import SparkConf, SparkContext
from mmtfPyspark.filters import PolymerComposition
from mmtfPyspark.io import mmtfReader
from mmtfPyspark.mappers import StructureToPolymerChains

Configure Spark¶

In [2]:

conf = SparkConf().setMaster("local[*]") \
                  .setAppName("FlatMapChainsDemo")
sc = SparkContext(conf = conf)

Read in MMTF files¶

In [3]:

path = "../../resources/mmtf_reduced_sample/"

pdb = mmtfReader.read_sequence_file(path, sc)

flat map structure to polymer chains, filter by polymer composition and count¶

Supported polymer composition type:¶

** polymerComposition.AMINO_ACIDS_20 **= [“ALA”,”ARG”,”ASN”,”ASP”,”CYS”,”GLN”,”GLU”,”GLY”,”HIS”,”ILE”,”LEU”,”LYS”,”MET”,”PHE”,”PRO”,”SER”,”THR”,”TRP”,”TYR”,”VAL”]

** polymerComposition.AMINO_ACIDS_22 **= [“ALA”,”ARG”,”ASN”,”ASP”,”CYS”,”GLN”,”GLU”,”GLY”,”HIS”,”ILE”,”LEU”,”LYS”,”MET”,”PHE”,”PRO”,”SER”,”THR”,”TRP”,”TYR”,”VAL”,”SEC”,”PYL”]

** polymerComposition.DNA_STD_NUCLEOTIDES **= [“DA”,”DC”,”DG”,”DT”]

** polymerComposition.RNA_STD_NUCLEOTIDES **= [“A”,”C”,”G”,”U”]

In [4]:

count = pdb.flatMap(StructureToPolymerChains(False, True)) \
           .filter(PolymerComposition(PolymerComposition.AMINO_ACIDS_20)) \
           .count()

print(f"Chains with standard amino acids: {count}")

Chains with standard amino acids: 9386

Terminate Spark¶

In [5]:

sc.stop()

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