Plant hormones are small molecules that play versatile roles in regulating plant growth, development, and responses to the environment. Classic methodologies, including genetics, analytic chemistry, biochemistry, and molecular biology, have contributed to the progress in plant hormone studies. In addition, chemical regulators of plant hormone functions have been important in such studies. Today, synthetic chemicals, including plant growth regulators, are used to study and manipulate biological systems, collectively referred to as chemical biology. Here, we summarize the available chemical regulators and their contributions to plant hormone studies. We also pose questions that remain to be addressed in plant hormone studies and that might be solved with the help of chemical regulators.

Scoring functions are important components in molecular docking for structure-based drug discovery. Traditional scoring functions, generally empirical- or force field-based, are robust and have proven to be useful for identifying hits and lead optimizations. Although multiple highly accurate deep learning- or machine learning-based scoring functions have been developed, their direct applications for docking and screening are limited. We describe a novel strategy to develop a reliable protein–ligand scoring function by augmenting the traditional scoring function Vina score using a correction term (OnionNet-SFCT). The correction term is developed based on an AdaBoost random forest model, utilizing multiple layers of contacts formed between protein residues and ligand atoms. In addition to the Vina score, the model considerably enhances the AutoDock Vina prediction abilities for docking and screening tasks based on different benchmarks (such as cross-docking dataset, CASF-2016, DUD-E and DUD-AD). Furthermore, our model could be combined with multiple docking applications to increase pose selection accuracies and screening abilities, indicating its wide usage for structure-based drug discoveries. Furthermore, in a reverse practice, the combined scoring strategy successfully identified multiple known receptors of a plant hormone. To summarize, the results show that the combination of data-driven model (OnionNet-SFCT) and empirical scoring function (Vina score) is a good scoring strategy that could be useful for structure-based drug discoveries and potentially target fishing in future.

Auxin inactivation is critical for plant growth and development. To develop plant growth regulators functioning in auxin inactivation pathway, we performed a phenotype-based chemical screen in Arabidopsis and identified a chemical, nalacin, that partially mimicked the effects of auxin. Genetic, pharmacological, and biochemical approaches demonstrated that nalacin exerts its auxin-like activities by inhibiting indole-3-acetic acid (IAA) conjugation that is mediated by Gretchen Hagen 3 (GH3) acyl acid amido synthetases. The crystal structure of Arabidopsis GH3.6 in complex with D4 (a derivative of nalacin) together with docking simulation analysis revealed the molecular basis of the inhibition of group II GH3 by nalacin. Sequence alignment analysis indicated broad bioactivities of nalacin and D4 as inhibitors of GH3s in vascular plants, which were confirmed, at least, in tomato and rice. In summary, our work identifies nalacin as a potent inhibitor of IAA conjugation mediated by group II GH3 that plays versatile roles in hormone-regulated plant development and has potential applications in both basic research and agriculture.

Plant development is regulated by both synergistic and antagonistic interactions of different phytohormones, including a complex crosstalk between ethylene and auxin. For instance, auxin and ethylene synergistically control primary root elongation and root hair formation. However, a lack of chemical agents that specifically modulate ethylene or auxin production has precluded precise delineation of the contribution of each hormone to root development. Here, we performed a chemical genetic screen based on the recovery of root growth in ethylene-related Arabidopsis mutants with constitutive "short root" phenotypes (eto1–2 and ctr1–1). We found that ponalrestat exposure recovers root elongation in these mutants in an ethylene signal–independent manner. Genetic and pharmacological investigations revealed that ponalrestat inhibits the enzymatic activity of the flavin-containing monooxygenase YUCCA, which catalyzes the rate-limiting step of the indole-3-pyruvic acid branch of the auxin biosynthesis pathway. In summary, our findings have identified a YUCCA inhibitor that may be useful as a chemical tool to dissect the distinct steps in auxin biosynthesis and in the regulation of root development.

AC94377 preferentially binds the GID1 receptor to activate the gibberellin signaling in Arabidopsis.