[ Receptor Considerations | Ligand Considerations | Chirality Considerations | Protonation Considerations | Internal Hydrogen Bonds | Pyramidal Sampling | Membrane Exposed Docking | Waters | Scoring | Ligand Strain ]

Receptor preparation is particularly important. An incorrect pocket geometry, an unsuitable protonation state, or an unrepresented receptor conformation can prevent an otherwise suitable ligand from docking correctly.

• ICM samples ligand conformations and positions within the defined binding site. Its stochastic global optimization uses receptor interaction grids together with the ligand's internal conformational energy.
• Alternative low-energy poses are retained in a conformational stack for inspection and scoring.
• Runtime depends on ligand size and flexibility, receptor settings, hardware, and the thoroughness/effort parameter. Increase thoroughness when additional sampling is needed.
• For ultra large-library screening, see RIDGE, GigaScreen, and CombiRIDGE.

Please click here to read more about ICM Docking.

Choose a receptor structure that represents the binding site you wish to study. Convert it to an ICM object and review the pocket before generating docking maps.

• Compare the local quality and completeness of available structures. For crystallographic models, consider resolution, occupancy, B-factors, and missing atoms near the pocket.
• Prefer a relevant ligand-bound conformation when available. An apo structure or predicted model may require pocket refinement before docking.
• Check polar hydrogen positions, histidine states, and the protonation of binding-site residues - this is part of the pdb to icm object conversion procedure.
• Retain chains, cofactors, metal ions, and other components needed to represent the binding site. Remove unrelated components and review pocket waters.
• If side chains obstruct the pocket or alternative conformations are plausible, consider flexible receptor methods, including 4D docking SCARE or Local Boltz Diffusion Docking.
• A homology model or Boltz co-folding model can be used for docking, but uncertainty in the pocket should be considered when interpreting the results.

If known ligands are available, dock them first to assess whether the prepared receptor can accommodate their expected binding modes. For screening, check the chemical quality and relevance of the compound library before committing to a large calculation.

Standard flexible docking can generate ligand 3D coordinates during the calculation. RIDGE instead uses a prepared conformer database. Check bond orders, formal charges, stereochemistry, and protonation settings before either workflow.

For peptide sequences, use the dedicated peptide docking workflow.

Review stereochemistry before docking. For acyclic chiral centers, the Sample Racemic Centers option is available in Docking/Preferences/General.

For ring stereocenters, or when explicit control of the input stereoisomers is required, generate the intended stereoisomers with Chemistry/Generate Stereoisomers before docking. Do not rely on an unspecified stereocenter to represent a particular stereoisomer.

Set ligand charging options in Docking/Preferences/General, using the Charge Groups field.

• auto: Use MolSoft's built-in pKa model to assign protonation and charge states.
• NH2, NH, and NT: Specify primary, secondary, and tertiary aliphatic amines, respectively. Options are also available for imidazole and amidine groups.
• none: Disable the basic-group charging selection. Review acid/carboxyl settings separately; do not assume that this option alone preserves every input charge state.

To examine protonation over a range of pH values, use Chemistry/Set Formal Charges and select Auto using Pka Model. Review the resulting structures before docking.

Internal hydrogen bonds are taken into account during docking by default. You can check in the docking_project_name.dtb table file to make sure that l_internalHB field is 'yes'.

If the parameter l_samplePyramid is set to yes in the Docking Project .dtb file:

• During Monte Carlo sampling, the algorithm includes steps to invert the pyramid geometry at nitrogen atoms.
• This specifically targets uncharged aliphatic amines and sulfonamides.

(l_membraneScore)

If you are docking to a membrane-exposed site, set the l_membraneScore flag in the docking project .dtb file to yes.

Before docking, you will need to convert your PDB structure into an ICM object. During this step, you can choose how water molecules are handled. The options are to keep all waters, delete all waters, or remove only loose waters.

Loose waters are defined as water molecules that do not make any hydrogen bonds with the protein or a co-crystallized ligand. Tight waters are those that make three or more hydrogen bonds and are often more structurally stable.

Before docking, crystallographic water molecules in or near the binding pocket should be reviewed carefully. In most cases, bulk or weakly ordered waters should be deleted, as docking methods implicitly account for solvent effects and these waters may block ligand placement.

Waters that may be safely removed include:

• Waters located at the pocket entrance or solvent-exposed regions
• Waters with high B-factors or partial occupancy
• Waters not involved in stable hydrogen-bond networks
• Waters displaced by known ligands in co-crystal structures

Waters that may be worth retaining include:

• Conserved waters observed across multiple crystal structures
• Waters that bridge key protein-ligand interactions
• Waters forming stable hydrogen-bond networks with low B-factors
• Waters deeply buried in the pocket with limited exchange

When waters are retained, they should be treated consistently during docking and scoring. If the role of a water molecule is uncertain, it can be useful to run docking with and without selected waters and compare docking scores and poses.

• Physics-based Score. The Score is the ICM VLS Score which is a GBSA/MM-type scoring function augmented with a directional hydrogen bonding term (see Neves et al 2012). An ICM Score of approximately -32 or lower can be a useful historical reference, but suitable cutoffs depend on the receptor, ligand size, and screening objective. Use known ligands and pilot screens to calibrate selection.

  An important parameter in a VLS run is the score threshold. A docked conformation for a given ligand is stored by the ICM VLS procedure only if its binding score is below this threshold.

  The threshold can be chosen in several ways:

  1. If a co-crystal structure is available, remove the ligand, re-dock it, and use the resulting score as a reference.
  2. If known ligands exist, dock them and examine their scores. A threshold set slightly above the typical scores of these ligands is usually a good starting point.
  3. If no ligands are known, run a short pre-simulation using approximately 1000 compounds from the screening database. Based on the score distribution, set the threshold to retain roughly 1 percent of the ligands.

  You can edit the Score threshold in the Docking/Preferences dialog box or edit the .dtb file.

• RTCNN Score is a Neural Network Score. RTCNN is a Radial Convolutional Neural Net including layers that do Topological (chemical graph) convolutions and 3D Radial convolutions. The RTCNN score is different from the regular ICM Score (see above) - it does not use any molecular mechanics or physical energy terms. Instead, the score is trained to recognize native-like complexes versus decoys directly, based only on geometries of putative complexes. So, for example, if internally the neural net recognizes a hydrogen bond, it is because it is observed during training that the configurations of atoms that we call hydrogen bonds are present to a greater extent in native-like structures. This is the same for other favorable or unfavourable interactions - it is all learnt from examples, not from any input terms.

  The RTCNN score performs extremely well on our benchmarks and the CASF benchmark (Su et al J.Chem.Inf.Model 2019). Please find details about this benchmark here: RTCNN_performance.pdf and read more about RTCNN Score here.

  When analyzing a hitlist from virtual screening we would recommend to plot Score vs RTCNN and prioritize those in the quadrant that have low Score and low RTCNN score. One key difference you may observe between RTCNN score and the regular Score is that the RTCNN score has a lower penalty for small induced fit ligand-receptor clashes. The lower the RTCNN score the better the predicted ligand-receptor interaction.

• mfScore is the statistical potential of mean force which was derived according to the published methodology (see Muegge J.Med.Chem 2006)

To calculate Strain, an ensemble of low-energy ligand conformers is generated in solution using the MMFF94s force field. The lowest-energy conformer is used as the unstrained reference. Strain is then defined as the energy difference between this reference conformation and the docked pose, with both energies computed using the same force field.

Analysis of specific torsion can be performed via torsion profile calculation at force-field level with MolMechanics/Torsion Scan, or via Crystallography Open Database search with appropriate substructure (Search Tab, select COD search, draw substructure) and statistics calculation with Chemistry/Torsion analysis.