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Hypothesis Driven Docking: Docking with Constraints


BioPredict has developed a suite of hypothesis-driven docking and ab-initio ligand design programs for use in virtual screening.  Careful comparison of crystallized ligand-protein complexes of the target or related targets can often identify one or more binding motifs to serve as hypotheses in identifying new active compounds and in predicting their correct placement in the active site.  The software platform described distills these hypotheses into geometrical and chemical constraints that are then incorporated directly into the docking process.  Current docking-based screening methods that rely on energy criteria alone have a high failure rate, both for identifying new active molecules and for predicting correct binding modes1. Hypothesis-driven docking alleviates this problem by augmenting energetic criteria with prior knowledge incorporated directly in the docking process.

Constraints can include but are not limited to: (i) hydrogen bonds and salt bridges between ligand  atoms and designated protein atoms, (ii) distance constraints from ligand atoms to protein atoms or to geometrically placed points in the docking site, and (iii) occupation of hydrophobic pockets. Formally a constraint can be defined as a set of limits on any subset of interaction energy terms describing the interaction of a ligand with any subset of protein atoms in the active site. 

The docking procedure involves breaking the ligand into constituent fragments and recursively docking larger fragment constructs starting from the largest fragment of the ligand.  The ab-initio procedure is similar but it selects its next fragment and linker from a library.  Many possible ligand poses are retained at every stage of this procedure.  Energetic optimization is performed at each stage by adjusting translation, rotation, ligand bond rotation, and side-chain rotations for selected protein side chains.  Constraints are imposed using the Method of Langrange Multipliers.

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1 Docking on Trial, Peter Kirkpatrick, Nature Reviews Drug Discovery 4: 813 (2005).