1. 10/19/2015BCHB524 - 2015 Protein Structure Informatics using Bio.PDB BCHB524 2015 Lecture 12 By Edwards & Li

2. 10/19/2015BCHB524 - 2015 Outline Review Python modules Biopython Sequence modules Biopython’s Bio.PDB Protein structure primer / PyMOL PDB file parsing PDB data navigation: SMCRA Examples

3. 10/19/2015BCHB524 - 2015 Python Modules Review Access the program environment sys, os, os.path Specialized functions math, random Access file-like resources as files: zipfile, gzip, urllib Make specialized formats into “lists” and “dictionaries” csv (, XML, …)

4. 10/19/2015BCHB524 - 2015 BioPython Sequence Modules Provide “sequence” abstraction More powerful than a python string Knows its alphabet! Basic tasks already available Easy parsing of (many) downloadable sequence database formats FASTA, Genbank, SwissProt/UniProt, etc… Simplify access to large collections of sequence Access by iteration, get sequence and accession Other content available as lists and dictionaries. Little semantic extraction or interpretation

5. Biopython Bio.SeqIO Access to additional information annotations dictionary features list Information, keys, and keywords vary with database! Semantic content extraction (still) up to you! 10/19/2015BCHB524 - 2015 import Bio.SeqIO import sys seqfile = open(sys.argv[1]) for seq_record in Bio.SeqIO.parse(seqfile, "uniprot-xml"): print "\n------NEW SEQRECORD------\n" print "seq_record.annotations\n\t",seq_record.annotations print "seq_record.features\n\t",seq_record.features print "seq_record.dbxrefs\n\t",seq_record.dbxrefs print "seq_record.format('fasta')\n",seq_record.format('fasta') seqfile.close()

6. 10/19/2015BCHB524 - 2015 Proteins are… …a linear sequence of amino-acids, after transcription from DNA, and translation from mRNA.

7. 10/19/2015BCHB524 - 2015 Proteins are… …3-D molecules that interact with other (biological) molecules to carry out biological functions… DNA Polymerase Hemoglobin

8. Proteins are… www.uniprot.or g www.rcsb.org PrimarySecondaryTertiaryQuaternary Introduction to Protein Structure, by Carl Branden and John Tooze

9. Proteins are Composed of 20 Amino Acids

10. Representations of Protein 3D Structures Ball-StickRibbonSurface Ball-Stick: Atom- Bond Helix, Sheet and Random Coil Solvent Accessible Surface

11. 10/19/2015BCHB524 - 2015 Protein Data Bank (PDB) Repository of the 3-D conformation(s) / structure of proteins. The result of laborious and expensive experiments using X-ray crystallography and/or nuclear magnetic resonance (NMR). (x,y,z) position of every atom of every amino-acid Some entries contain multi-protein complexes, small-molecule ligands, docked epitopes and antibody-antigen complexes…

12. 10/19/2015BCHB524 - 2015 Visualization (PyMOL)

13. Molecular Visualization Tools PyMol: http://pymol.sourceforge.net/http://pymol.sourceforge.net/ Chimera: http://www.cgl.ucsf.edu/chimera/http://www.cgl.ucsf.edu/chimera/ PMV: http://www.scripps.edu/~sanner/python/http://www.scripps.edu/~sanner/python/ Coot: http://www.ysbl.york.ac.uk/~emsley/coot/http://www.ysbl.york.ac.uk/~emsley/coot/ CCP4mg: http://www.ysbl.york.ac.uk/~lizp/molgraphics.htmlhttp://www.ysbl.york.ac.uk/~lizp/molgraphics.html mmLib: http://pymmlib.sourceforge.net/http://pymmlib.sourceforge.net/ VMD: http://www.ks.uiuc.edu/Research/vmd/http://www.ks.uiuc.edu/Research/vmd/ MMTK: http://starship.python.net/crew/hinsen/MMTK/http://starship.python.net/crew/hinsen/MMTK/ http://biopython.org/

14. Overall Layout of a Structure Object A structure consists of models A model consists of chains A chain consists of residues A residue consists of atoms http://biopython.org/

15. 10/19/2015BCHB524 - 2015 Biopython Bio.PDB Parser for PDB format files Navigate structure and answer atom-atom distance/angle questions. Structure (PDB File) >> Model >> Chain >> Residue >> Atom >> (x,y,z) coordinates SMCRA representation mirrors PDB format

16. 10/19/2015BCHB524 - 2015 SMCRA Data-Model Each PDB file represents one “structure” Each structure may contain many models In most cases there is only one model, index 0. Each polypeptide (amino-acid sequence) is a “chain”. A single-protein structure has one chain, “A” 1HPV is a dimer and has chains “A” and “B”.

17. 10/19/2015BCHB524 - 2015 SMCRA Data-Model #eg1.py import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure = parser.get_structure("1HPV", "1HPV.pdb") model = structure[0] # This structure is a dimer with two chains achain = model['A'] bchain = model['B']

18. 10/19/2015BCHB524 - 2015 SMCRA Chains are composed of amino-acid residues Access by iteration, or by index Residue “index” may not be sequence position Residues are composed of atoms: Access by iteration or by atom name …except for H! Water molecules are also represented as atoms – HOH residue name, het=“W”

19. 10/19/2015BCHB524 - 2015 SMCRA Data-Model #eg2.py import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure = parser.get_structure("1HPV", "1HPV.pdb") model = structure[0] for chain in model: for residue in chain: for atom in residue: print chain, residue, atom, atom.get_coord()

20. 10/19/2015BCHB524 - 2015 Polypeptide molecules S-G-Y-A-L

21. 10/19/2015BCHB524 - 2015 SMCRA Atom names

22. 10/19/2015BCHB524 - 2015 Check polypeptide backbone #eg3.py import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure = parser.get_structure("1HPV", "1HPV.pdb") model = structure[0] achain = model['A'] for residue in achain: index = residue.get_id()[1] calpha = residue['CA'] carbon = residue['C'] nitrogen = residue['N'] oxygen = residue['O'] print "Residue:",residue.get_resname(),index print "N - Ca",(nitrogen - calpha) print "Ca - C ",(calpha - carbon) print "C - O ",(carbon - oxygen) print break

23. 10/19/2015BCHB524 - 2015 Check polypeptide backbone #eg4.py # As before... for residue in achain: index = residue.get_id()[1] calpha = residue['CA'] carbon = residue['C'] nitrogen = residue['N'] oxygen = residue['O'] print "Residue:",residue.get_resname(),index print "N - Ca",(nitrogen - calpha) print "Ca - C ",(calpha - carbon) print "C - O ",(carbon - oxygen) if achain.has_id(index+1): nextresidue = achain[index+1] nextnitrogen = nextresidue['N'] print "C - N ",(carbon - nextnitrogen) print

24. 10/19/2015BCHB524 - 2015 Find potential disulfide bonds The sulfur atoms of Cys amino-acids often form “di-sulfide” bonds if they are close enough – less than 8 Å. Compare with PDB file contents: SSBOND Bio.PDB does not provide an easy way to access the SSBOND annotations

25. 10/19/2015BCHB524 - 2015 Find potential disulfide bonds #eg5.py import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure = parser.get_structure("1KCW", "1KCW.pdb") model = structure[0] achain = model['A'] cysresidues = [] for residue in achain: if residue.get_resname() == 'CYS': cysresidues.append(residue) for c1 in cysresidues: c1index = c1.get_id()[1] for c2 in cysresidues: c2index = c2.get_id()[1] if (c1['SG'] - c2['SG']) < 8.0: print "possible di-sulfide bond:", print "Cys",c1index,"-", print "Cys",c2index, print round(c1['SG'] - c2['SG'],2)

26. 10/19/2015BCHB524 - 2015 Find contact residues in a dimer #eg6.py import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure = parser.get_structure("1HPV","1HPV.pdb") achain = structure[0]['A'] bchain = structure[0]['B'] for res1 in achain: if res1.get_id()[0][0] is 'H' or res1.get_id()[0][0] is 'W': continue r1ca = res1['CA'] r1ind = res1.get_id()[1] r1sym = res1.get_resname() for res2 in bchain: if res2.get_id()[0][0] is 'H' or res2.get_id()[0][0] is 'W': continue r2ca = res2['CA'] r2ind = res2.get_id()[1] r2sym = res2.get_resname() if (r1ca - r2ca) < 6.0: print "Residues",r1sym,r1ind,"in chain A", print "and",r2sym,r2ind,"in chain B", print "are close to each other:",round(r1ca-r2ca,2)

27. 10/19/2015BCHB524 - 2015 Find contact residues in a dimer – better version #eg7.py import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure = parser.get_structure("1HPV","1HPV.pdb") achain = structure[0]['A'] bchain = structure[0]['B'] bchainca = [ r['CA'] for r in bchain ] neighbors = Bio.PDB.NeighborSearch(bchainca) for res1 in achain: r1ca = res1['CA'] r1ind = res1.get_id()[1] r1sym = res1.get_resname() for r2ca in neighbors.search(r1ca.get_coord(), 6.0): res2 = r2ca.get_parent() r2ind = res2.get_id()[1] r2sym = res2.get_resname() print "Residues",r1sym,r1ind,"in chain A", print "and",r2sym,r2ind,"in chain B", print "are close to each other:",round(r1ca-r2ca,2)

28. 10/19/2015BCHB524 - 2015 Superimpose two structures import Bio.PDB import Bio.PDB.PDBParser import sys # Use QUIET=True to avoid lots of warnings... parser = Bio.PDB.PDBParser(QUIET=True) structure1 = parser.get_structure("2WFJ","2WFJ.pdb") structure2 = parser.get_structure("2GW2","2GW2a.pdb") ppb=Bio.PDB.PPBuilder() # Manually figure out how the query and subject peptides correspond... # query has an extra residue at the front # subject has two extra residues at the back query = ppb.build_peptides(structure1)[0][1:] target = ppb.build_peptides(structure2)[0][:-2] query_atoms = [ r['CA'] for r in query ] target_atoms = [ r['CA'] for r in target ] superimposer = Bio.PDB.Superimposer() superimposer.set_atoms(query_atoms, target_atoms) print "Query and subject superimposed, RMS:", superimposer.rms superimposer.apply(structure2.get_atoms()) # Write modified structures to one file outfile=open("2GW2-modified.pdb", "w") io=Bio.PDB.PDBIO() io.set_structure(structure2) io.save(outfile) outfile.close()

29. 10/19/2015BCHB524 - 2015 Superimpose two chains import Bio.PDB parser = Bio.PDB.PDBParser(QUIET=1) structure = parser.get_structure("1HPV","1HPV.pdb") model = structure[0] ppb=Bio.PDB.PPBuilder() # Get the polypeptide chains achain,bchain = ppb.build_peptides(model) aatoms = [ r['CA'] for r in achain ] batoms = [ r['CA'] for r in bchain ] superimposer = Bio.PDB.Superimposer() superimposer.set_atoms(aatoms, batoms) print "Query and subject superimposed, RMS:", superimposer.rms superimposer.apply(model['B'].get_atoms()) # Write structure to file outfile=open("1HPV-modified.pdb", "w") io=Bio.PDB.PDBIO() io.set_structure(structure) io.save(outfile) outfile.close()

30. 10/19/2015BCHB524 - 2015 Exercises Read through and try the examples from Chapter 10 of the Biopython Tutorial and the Bio.PDB FAQ. Write a program that analyzes a PDB file (filename provided on the command-line!) to find pairs of lysine residues that might be linked if the BS3 cross-linker is used. The rigid BS3 cross-linker is approximately 11 Å long. Write two versions, one that computes the distance between all pairs of lysine residues, and one that uses the NeighborSearch technique.