Multiple-Conformation and Protonation-State Representation in 4D-QSAR: The Neurokinin-1 Receptor System

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Abstract

Using a 4D-QSAR approach (software Quasar) allowing for multiple-conformation, orientation, and protonation-state ligand representation as well as for the simulation of local induced-fit phenomena, we have validated a family of receptor surrogates for the neurokinin-1 (NK-1) receptor system. The evolution was based on a population of 500 receptor models and simulated during 40 000 crossover steps, corresponding to 80 generations. It yielded a cross-validated r(2) of 0.887 for the 50 ligands of the training set (represented by a total of 218 conformers and protomers) and a predictive r(2) of 0.834 for the 15 ligands of the test set (70 conformers and protomers). A series of five "scramble tests" (with an average predictive r(2) of -0.438) demonstrates the sensitivity of the surrogate toward the biological data, for which it should establish a QSAR. On the basis of this model, the activities of 12 new compounds - four of which have been synthesized and tested in the meantime - are predicted. For most of the NK-1 antagonists, the genetic algorithm selected a single entity - out of the up to 12 conformers or protomers - to preferably bind to the receptor surrogate. Moreover, the evolution converged at an identical protonation scheme for all NK-1 antagonists. This indicates that 4D-QSAR techniques may, indeed, reduce the bias associated with the choice of the bioactive conformation as each ligand molecule can be represented by an ensemble of conformations, orientations, and protonation states.

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