Tutorial 3. Using a new ligand and link descriptions
1. Introduction
This tutorial uses a 1.6 Å resolution P212121 crystal structure of
pig cytosolic aspartate aminotransferase in complex with
2-methylaspartat (Rhee et al., 1997; PDB code 1ajs). The
asymmetric unit contains a dimer formed by subunits A and B. The
coenzyme pyridoxal-5'-phosphate is present as the external
aldimine in subunit A, where it forms an Schiff base with the
substrate analogue 2-methylaspartate. At the same time the
coenzyme in subunit B forms the internal aldimine with the side
chain of Lys 258. The two aldimines will be defined as a monomer
and as a link, respectively.
• The directory "jligand/3_newlink" contains the tutorial data
(files 1ajs.mtz and model.pdb).
– Set up ccp4i project "3_newlink" with this directory as the
project directory.
2. Refine incomplete structure and analyse the electron
density
• Run Refmac
Input files: 1ajs.mtz, model.pdb
Output files: 1ajs_refmac1.mtz, model_refmac1.pdb
• Launch Coot from Refmac result page.
• Validate > Difference Map Peaks
• Two top peaks should correspond to
– PLP covalently bound to lysine
– PLP covalently bound to alpha-methyl-aspartate.
• The two compounds are shown below. The first one is incorporated
into the polypeptide chain and we will define it as a link in the
additio al library; the second is an isolated ligand and will be
defined as a monomer.
3. Generate description of link LYS-PLP
• ccp4i > Refinement > Restraint Preparation > Ligands
and links with JLigand
• In JLigand window, load LYS and PLP from "Load Ligand" text box
• Check "Atom Ids" check-box
• Select "Del" in the left bar and delete O4A atom in PLP
• Select "Link" and connect NZ (LYS) and C4A (PLP)
• Double-click on the new bond and change bond type to "double"
• Ligand > Regularise > LYS-PLP
• File > Save as Link > LYS-PLP
– In "Save as CIF-library" window select filename refmac.cif
– Read notes in "Save Link Record" window and press "Yes" button
– Save "linkrecord.pdb"
Output files: refmac.cif, linkrecord.pdb
4. Generate description and coordinates of PLP bound to
Methyl-ASP
• Examine molecular graph editing Help > JLigand Help
• Load PLP and extend the molecular graph following the figure
below
• Rename atoms according to the figure
• Rename ligand to MSP
• Regularise MSP
• To avoid confusion, make sure that chirality of CA is set
to "allow both"
– Double-click on CA to open "Edit atom details"
– Check selection in "Chirality" menu and change it if necessary
– This will make it possible to correct chirality of the atom
later in Coot
• File > Append as Monomer > MSP
– In "Append to CIF-library" window select refmac.cif and press
"Append"
• File > Save Coordinates > MSP
– In "Save coordinates" window select "Exclude Hydrogens"
– In "Save coordinates in PDB-file" window, keep the default
filename MSP.pdb
Output files: refmac.cif, MSP.pdb
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)
5. Dock MSP into electron density
• Files 1ajs_refmac1.mtz and model_refmac1.pdb are already opened
in Coot
• Load the description and coordinates of MSP
– File > Import CIF dictionary; select project 3_newlink and
file refmac.cif
– File > Open Coordinates; select project 3_newlink and file
MSP.pdb
• Fit MSP into its density,
– Calculate > Other Modelling Tools > Find Ligands
– Find Ligands window, section "Select Ligands to Search for":
select ".../MSP.pdb" and "Flexible?" check boxes and then press
"Find Ligands" button
– Fitted Ligands window: select "Fitted Ligand •0" and press OK to
navigate to fitted ligand
• Refine fitting
• Append fitted ligand to the protein molecule
– Edit (Calculate in old Coot) > Merge Molecules...; select "Fitted ligand • 0"
• Make sure that the ligand is appended
– Open Display Manager and switch on and off the molecule
model_refmac1.pdb
6. Dock PLP into electron density and save the structure with
ligands
• Load description and coordinates of PLP from the standard
library,
– Coot: File > Get Monomer...; enter 3-letter code PLP
• Remove hydrogen atoms
• Fit PLP into its density
• Refine fitting
• Delete O4A atom from PLP
• Append fitted ligand to the molecule model_refmac1.pdb
• Make sure that the ligand is appended
• Take a note of PLP residue number and chain ID (should be "D 1")
• Save molecule model_refmac1.pdb
– select project 3_newlink and keep default filename
model_refmac1-coot-0.pdb
• Exit Coot
7. Refine structure with ligand and link
• Edit the file linkrecord.pdb. This file contains one line, which
is an instruction for Refmac to apply the link LYS-PLP to
specified residues.
– If you have followed instructions precisely,
model_refmac1-coot-0.pdb will contain PLP as residue 1 in chain D
("PLP D 1"). Check if this is correct using a text editor or in
Coot
– Edit chain IDs and residue numbers in linkrecord.pdb. These
should be: "LYS B 258" and "PLP D 1". Keep format of
the record as it was, i.e. four characters for the residue number
etc.
• Insert the LINK-record from linkrecord.pdb into
model_refmac1-coot-0.pdb, just before CRYST1 record.
• Run Refmac with the completed model and additional library
refmac.cif.
– In the line Libin specify additional library refmac.cif
Input files: 1ajs.mtz, model_refmac1-coot-0.pdb, refmac.cif
Output files: 1ajs_refmac2.mtz, model_refmac2.pdb
• Note the decrease in R-free compared to the previous Refmac run
• In Output Files section of Result viewer press Display to see
the content of the output PDB-file. Check, if this file contains
LINKR record (a few lines before CRYST1). If it does, then
everything was done correctly.
• Launch Coot to examine the electron density of the ligands