Plant acetyl CoA carboxylase (ACCase) has been an effective target for herbicides, such as aryloxypropionic acid analogues (FOPs) and cyclohexanediones (DIMs) in controlling grass weed populations and increasing crop yield. These herbicides block the transcarboxylation step at the CT domain of grass weeds, thus inhibiting the synthesis of an essential intermediate (malonyl Co-A) required for fatty acid synthesis. However, extensive use of herbicides has triggered point mutations at the active site (CT domain of ACCase) making several of the current herbicides insensitive. Thus, to combat the resistance complete knowledge of the binding site is necessary. In silico techniques aid as a cost effective tool for the virtual evaluation of the binding site and for assessing the required modification of current herbicides to increase their sensitivity. In our research we have selected three plant ACCases (wheat, pea & corn), which constitute a spectrum of sensitivity to these herbicides. Homology modeling has been performed using yeast ACCase (pdb ID: 1OD2) and MD simulation for the docking studies. Initially we limited our study to the N-terminal of CT domain, which contains most of the binding site. Selected herbicides (FOPs & DIMs) were docked at the active site and the docking scores revealed the order of inhibition to be pea &lt; wheat &lt; corn, which matches with the predicted inhibition order. However, since the herbicide active site is located at the interface of N and C-terminal domains, we now present modeling and MD simulation on both domains to gain a more complete insight into herbicide binding at the active site. Docking studies are performed on a virtual library of existing FOPs and DIMs, as well as modified herbicide analogues.

Computational modeling of inhibition of acetyl CoA carboxylase by cyclohexanedione and aryloxypropionic acid herbicides

2019 Fall National Meeting

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