Binding to acetylcholinesterase may cause toxic effects in humans. Organophosphates simultaneously are both dangerous and useful substances: dangerous since they are employed in chemical warfare; and useful when they are applied as pesticides. Here we suggest the models for organophosphates binding to acetylcholinesterase developed via representing the molecular structure by a simplified molecular input-line entry system (SMILES) using so-called optimal SMILES-based descriptors calculated with the Monte Carlo technique using the CORAL software available on the Internet (http://www.insilico.eu/coral). Quantitative structure-activity relationships (QSARs) serve to develop predictive models for organophosphates. The predictive potential of these models is quite good: the determination coefficient for the validation set ranged from 0.87 to 0.90. These models were built up according to the principle "QSAR is a random event", i.e. predictive potential of an approach should be checked up with several splits of available data into the training and test sets. The special scheme of mechanistic interpretation definition is represented. The mechanistic interpretation is based on probabilities of molecular features to be in the sub-group of promoters of increase for endpoint or in sub-group of promoters of its' decrease.