Enormous strides have been made over the past three decades to understand the key determinants of pharmacokinetics as they apply to pharmaceutical drug design and the underlying causes of drug attrition. However, despite the knowledge gained from active research in pharmacokinetics and ADME (absorption, distribution, metabolism and elimination) of pharmaceuticals, minimal attention has been given to the optimizing and understanding "agrokinetics" as they apply to the same problems in agrochemical discovery.
Although "rules of 3" and their counterpart ("rule of 5") exist in the literature, useful molecular design/delivery rules and tailored informatics approaches are underdeveloped for pest species targeted by agrochemicals such as plants, insects and fungi. Here we describe retrospective analyses using public datasets assembled from the literature on chemical uptake through plant foliar systems, insect oral absorption, and fungal uptake. These data have been applied to develop both (i) biophysical and (ii) QSAR/QSPR-based cheminformatic and machine learning models in MOE (Molecular operating Environment) to shed some light on the agrokinetic parameters of biologically active pesticides. These exploratory models can help pave the way for new experimental and in silico methods of capturing and understanding the key agrokinetic descriptors for modern pesticides.
Rather than "spraying and praying" for new agrochemical solutions, it is our hope that both the rules and relationships gleaned from these experimental models will hold promise in reducing toxicity, enhancing potency, reducing biological resistance and streamlining the value of ultra-large agrochemical library datasets. These simple informatics-driven approaches for estimating agrokinetic determinants can bring a much-needed "rational" dimension to agrochemical design and focus discovery or optimization efforts down to a molecular level of resolution.