The G143A mutation is thought to result in significant as well as stable resistance factors towards QoIs, while other mutations play only a minor role. Since G143A development is prevented in Phakopsora pachyhrizi, a stable control of soybean rust with QoIs in future is rather likely. In contrast, a shifting in sensitivity towards DMIs has been observed, which is due to multiple independent mechanisms.
Protoporphyrinogen oxidase (PPO)-inhibiting herbicides are used to control weeds in a variety of crops. These herbicides inhibit heme and photosynthesis in plants. PPO-inhibiting herbicides are used to control
Amaranthus palmeri
(Palmer amaranth) especially those with resistance to glyphosate and acetolactate synthase (ALS) inhibiting herbicides. While investigating the basis of high fomesafen-resistance in
A. palmeri
, we identified a new amino acid substitution of glycine to alanine in the catalytic domain of PPO2 at position 399 (G399A) (numbered according to the protein sequence of
A. palmeri
). G399 is highly conserved in the PPO protein family across eukaryotic species. Through combined molecular, computational, and biochemical approaches, we established that PPO2 with G399A mutation has reduced affinity for several PPO-inhibiting herbicides, possibly due to steric hindrance induced by the mutation. This is the first report of a PPO2 amino acid substitution at G399 position in a field-selected weed population of
A. palmeri
. The mutant
A. palmeri
PPO2 showed high-level
in vitro
resistance to different PPO inhibitors relative to the wild type. The G399A mutation is very likely to confer resistance to other weed species under selection imposed by the extensive agricultural use of PPO-inhibiting herbicides.
BACKGROUND
Trifluoromethyloxadiazoles (TFMOs) are selective inhibitors of class II histone deacetylases (HDACs). To date, class II HDACs have not been addressed as target enzymes by commercial fungicides.
RESULTS
Antifungal testing of a broad variety of TFMOs against several important plant pathogens showed activity against only rusts, and especially Phakopsora pachyrhizi, the cause of Asian soybean rust. A structure–activity relationship was established, leading to highly active fungicides that inhibit fungal class II and HOS3‐type HDACs of Aspergillus nidulans. Studies of the enzyme–inhibitor binding mode using protein structural information based on the crystal structure of human HDAC4 argue that TFMOs inhibit these enzymes only after undergoing hydration.
CONCLUSION
Fungal class II HDACs are potential target enzymes for the control of at least some biotrophic crop diseases, in particular Asian soybean rust. As with any novel mode‐of‐action, class II HDAC fungicides would offer the potential to control fungal isolates that show reduced sensitivity toward existing commercial fungicides.
Force fields form the basis for classical molecular simulations and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small molecule force field. In this report industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4 and SMIRNOFF99Frosst. We analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.
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