ABSTRACT
The global cost-benefit analysis of pesticide use during the last 30 years has been characterized by a significant increase during the period from 1990 to 2007 followed by a decline. This observation can be attributed to several factors including, but not limited to, pest resistance, lack of novelty with respect to modes of action or classes of chemistry, and regulatory action. Due to current and projected increases of the global population, it is evident that the demand for food, and consequently, the usage of pesticides to improve yields will increase. Addressing these challenges and needs while promoting new crop protection agents through an increasingly stringent regulatory landscape requires the development and integration of infrastructures for innovative, cost- and time-effective discovery and development of novel and sustainable molecules. Significant advances in artificial intelligence (AI) and cheminformatics over the last two decades have improved the decision-making power of research scientists in the discovery of bioactive molecules. AI- and cheminformatics-driven molecule discovery offers the opportunity of moving experiments from the greenhouse to a virtual environment where thousands to billions of molecules can be investigated at a rapid pace, providing unbiased hypothesis for lead generation, optimization, and effective suggestions for compound synthesis and testing. To date, this is illustrated to a far lesser extent in the publicly available agrochemical research literature compared to drug discovery. In this review, we provide an overview of the crop protection discovery pipeline and how traditional, cheminformatics, and AI technologies can help to address the needs and challenges of agrochemical discovery towards rapidly developing novel and more sustainable products.
ABSTRACT
Phenotypic screening is a neoclassical approach for drug discovery. We conducted phenotypic screening for insulin secretion enhancing agents using INS-1E insulinoma cells as a model system for pancreatic beta-cells. A principal regulator of insulin secretion in beta-cells is the metabolically regulated potassium channel Kir6.2/SUR1 complex. To characterize hit compounds, we developed an assay to quantify endogenous potassium channel activity in INS-1E cells. We quantified ligand-regulated potassium channel activity in INS-1E cells using fluorescence imaging and thallium flux. Potassium channel activity was metabolically regulated and coupled to insulin secretion. The pharmacology of channel opening agents (diazoxide) and closing agents (sulfonylureas) was used to validate the applicability of the assay. A precise high-throughput assay was enabled, and phenotypic screening hits were triaged to enable a higher likelihood of discovering chemical matter with novel and useful mechanisms of action.
