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Copy file name to clipboardExpand all lines: education/HADDOCK3/HADDOCK3-protein-protein-basic/index.md
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@@ -71,7 +71,7 @@ inherited from CNS, to incorporate experimental data as restraints and use these
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traditional energetics and shape complementarity. Moreover, the intimate coupling with CNS endows HADDOCK with the
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ability to actually produce models of sufficient quality to be archived in the Protein Data Bank.
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A central aspect to HADDOCK is the definition of Ambiguous Interaction Restraints or AIRs. These allow the
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A central aspect to HADDOCK is the definition of Ambiguous Interaction Restraints or AIRs (see [https://www.bonvinlab.org/haddock3-user-manual/intro_restraints.html](https://www.bonvinlab.org/haddock3-user-manual/intro_restraints.html#ambiguous-distance-restraints)). These allow the
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translation of raw data such as NMR chemical shift perturbation or mutagenesis experiments into distance
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restraints that are incorporated in the energy function used in the calculations. AIRs are defined through
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a list of residues that fall under two categories: active and passive. Generally, active residues are those
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</figure>
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To keep HADDOCK3 modules organized, we catalogued them into several
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categories. But, there are no constraints on piping modules of different
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categories.
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The main module categories are "topology", "sampling", "refinement",
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***Sampling modules**
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*`rigidbody`: *Rigid body energy minimization with CNS (`it0` in haddock2.x).*
*`flexref`: *Semi-flexible refinement using a simulated annealing protocol through molecular dynamics simulations in torsion angle space (`it1` in haddock2.x).*
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*`emref`: *Refinement by energy minimisation (`itw` EM only in haddock2.4).*
Once you have defined your active and passive residues for both molecules, you
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can proceed with the generation of the ambiguous interaction restraints (AIR) file for HADDOCK.
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HADDOCK3 also provides an analysis module (`caprieval`) that allows
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to compare models to either the best scoring model (if no reference is given) or a reference structure, which in our case
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we have at hand. This will directly allow us to assess the performance of the protocol for the following three scenarios:
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we have at hand. This will directly allow us to assess the performance of the protocol for the following two scenarios:
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1. Scenario 1: 1000 rigidbody docking models, selection of top200 and flexible refinement + EM
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3. Scenario 2: 1000 rigidbody docking models, FCC clustering and selection of max 20 models per cluster followed by flexible refinement and EM
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The basic workflow for all three scenarios will consists of the following modules, with some differences in the restraints used and some parameter settings (see below):
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The basic workflow for all three scenarios will consists of the following modules, with some differences in the parameter settings (see below):
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1.**`topoaa`**: *Generates the topologies for the CNS engine and build missing atoms*
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2.**`rigidbody`**: *Rigid body energy minimisation (`it0` in haddock2.x)*
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7.**`clustfcc`**: *Clustering of models based on the fraction of common contacts (FCC)*
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8.**`caprieval`**: *Calculates CAPRI metrics (i-RMSD, l-RMSD, Fnat, DockQ) with respect to the top scoring model or reference structure if provided*
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The input PDB files are the same for all two scenarios. The differences are in the sampling at the rigid body stage.
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The input PDB and restraints files are the same for the two scenarios. The differences are in the sampling at the rigid body stage.
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<hr>
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### Structure of the run directory
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Once your run has completed inspect the content of the resulting directory. You will find the various steps (modules) of the defined workflow numbered sequentially, e.g.:
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Once your run has completed inspect the content of the resulting directory. You will find the various steps (modules) of the defined workflow numbered sequentially, e.g. for scenario 2:
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