Combination of Ambiguous and Unambiguous Data in the Restraint-driven Docking of Flexible Peptides with HADDOCK: The Binding of the Spider Toxin PcTx1 to the Acid Sensing Ion Channel (ASIC) 1a

Abstract

Peptides that bind to ion channels have attracted much interest as potential lead molecules for the development of new drugs and insecticides. However, the structure determination of large peptide-channel complexes using experimental methods is challenging. Thus structural models are often derived from combining experimental information with restraint-driven docking approaches. Using the complex formed by the venom peptide PcTx1 and the acid sensing ion channel (ASIC) 1a as a case study, we have examined the effect of different combinations of restraints and input structures on the statistical likelihood of (a) correctly predicting the structure of the binding interface and (b) the ability to predict which residues are involved in specific pairwise peptide-channel interactions. For this, we have analyzed over 200 000 water-refined docked structures obtained with various amounts and types of restraints of the peptide-channel complex predicted using the docking program HADDOCK. We found that increasing the number of restraints or even the use of pairwise interaction data resulted in only a modest improvement in the likelihood of finding a structure within a given accuracy. This suggests that shape complementarity and the force field make a large contribution to the accuracy of the predicted structure. The results also showed that there are large variations in the accuracy of the predicted structure depending on the precise combination of residues used as restraints. Finally, we reflect on the limitations of relying on geometric criteria such as root-mean square deviations to assess the accuracy of docking procedures. We propose that in addition to currently used measures, the likelihood of finding a structure within a given level of accuracy should be also used to evaluate docking methods.