RosettaAntibody3: Protocol Workflow

Metadata

Author: Jianqing Xu (xubest@gmail.com), Daisuke Kuroda (dkuroda1981@gmail.com), Oana Lungu (olungu@utexas.edu), Jeffrey Gray (jgray@jhu.edu)

Last edited 4/25/2013. Corresponding PI Jeffrey Gray (jgray@jhu.edu).

References

We recommend the following articles for further studies of RosettaDock methodology and applications:

Overview

Please realize this the overview is to speed you up to run the protocol asap with minimum knowledge. For details of each steps, please check

To build an antibody model from sequences of its light chain and heavy chain, you need

  1. your input Fv sequences
  2. antibody.py (Downloading antibody.py from developer-only repository: https://svn.rosettacommons.org/source/trunk/antibody/scripts.v2/ )
  3. ProFit (Installing ProFit3.1: http://www.bioinf.org.uk/software/profit/ )
  4. BLAST (C++ version) (Installing BLAST: http://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE_TYPE=BlastDocs&DOC_TYPE=Download )
  5. Rosetta

Currently, antibody homology modelling is a 3 step process:

  1. Template selections by BLAST
  2. Grafting of CDR templates onto a FR template and Fv refinement
  3. Intensive H3 modeling and VL/VH refinement

Usage for a Production Run

Steps 1 and 2:

./antibody.py --light-chain <input_l.fasta> --heavy-chain <input_h.fasta> --profit=<ProFit> --blast=<blast> --blast-database=<blast_database> --antibody-database=<antibody_database> --rosetta-bin=<rosetta/rosetta_sourse/bin> --rosetta-database=<rosetta_database>

<input_l.fasta> and <input_h.fasta> are the files having sequences of the light and heavy chains, respectively, which you want to model.

Inputs:

  1. Sequence of the light chain Fv in FASTA format
  2. Sequence of the heavy chain Fv in FASTA format

Outputs:

  1. Sequence-grafted and refined Fv pdb: grafted.pdb, grafted.relaxed.pdb
  2. Constraints file for optional use in Step 3: cter_constraint

The script calls two Rosetta executable (relax and antibody_assemble_CDRs) for grafting and refinement, respectively, by specifying “–rosetta-bin” option. You can see other options by typing: ./antibody.py –help

Step 3:

[path to executable] /antibody_model_CDR_H3.[platform|linux/mac][compile|gcc/ ixx]release –database [path to database] @options

Sample options for a production run may look like: (this is an example, see details in RosettaAntibody3 application: Antibody Modeler Protocol (Loop H3 and VL-VH) .

Flags starting from "-kic_bump_overlap_factor 0.36" to "-loops:outer_cycles 5" will turn on the NGK or KIC2 for H3 loop modeling. Without these flags, the code is running KIC1 for H3

  -nstruct 2000   
  -s grafted.relaxed.pdb                             # Output of the antibody.py
  -antibody::remodel              perturb_kic        # low-res H3 modeling
  -antibody::snugfit              true               # VL-VH orientation optimization via docking
  -antibody::refine               refine_kic         # high-res H3 modeling
  -antibody::cter_insert          false              # H3 cterminal insertion using Kink/Extend fragments
  -antibody::flank_residue_min    true               # minimize 2 stem residues each side of H3 during modeling
  -antibody::bad_nter             false              # if n-terminal stem of H3 is bad and you have a pdb file with correct stem to copy
  -antibody::h3_filter            true               # using bioinformatics rules of Kink/Extend to filter out bad H3 decoys
  -antibody::h3_filter_tolerance  20                 # the maximum number of filtering is set to 20
  -ex1 -ex2 -extrachi_cutoff 0                       # packing options
  -constraints:cst_file cter_constraint              # constraint file which can include one or two lines of below optional constraints: 
  -antibody:constrain_cter                           #   optional constraint (a) the H3 cterminus to be Kink/Extend
  -antibody:constrain_vlvh_qq                        #   optional constraint (b) the distance between two GLN-GLN residues one L and H chains
  -kic_bump_overlap_factor 0.36                      # KIC1 become KIC2 (or NGK) after turning on the flags from here
  -corrections:score:use_bicubic_interpolation false
  -loops:legacy_kic false
  -loops:kic_min_after_repack true
  -loops:kic_omega_sampling
  -loops:allow_omega_move true
  -loops:ramp_fa_rep
  -loops:ramp_rama
  -loops:outer_cycles 5

Inputs:

  1. Sequence-grafted and refined Fv pdb: grafted.relaxed.pdb
  2. Constraints file for optional use, output from steps 1 and 2: cter_constraint

Outputs:

  1. Set of modeled and refined Fv pdbs with loop modeled CDH3 loops: <grafted.relaxed_000X.pdb> We recommend generating at least 2000 decoys during this step

Post Processing

You can use a set of decoys simultaneously for antibody-antigen docking simulations, such as SnugDock and EnsembleDock.

New things since last release

This is the first public release in Rosetta3