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Ametoctradin is an agricultural fungicide that selectively inhibits the cytochrome bc

The bacterial ribosome is a major target of naturally occurring thiopeptides antibiotics. Studying thiopeptide (e.g. thiostrepton) binding to the GAR's 23S·L11 ribosomal subunit using docking methods is challenging. Regarding the target, the binding site is composed of a flexible protein-RNA nonbonded interface whose available crystal structure is of medium resolution. Regarding the ligands, the thiopeptides are chemically complex, flexible, and contain macrocycles. In this study we developed a combined MD-docking-MD workflow that allows us to study thiopeptide-23S·L11 binding. It is shown that docking thiostrepton-like ligands to an MD-refined receptor structure instead of the medium resolution crystal leads to better convergence to the native-like docking pose and a better reproduction of experimental binding affinities. By applying an energy decomposition analysis, we identify key structural binding elements within GAR's rRNA-protein binding site and within the ligand structures.

Ametoctradin is an agricultural fungicide that inhibits the mitochondrial bc1 complex of oomycetes. The bc1 complex has two quinone binding sites that can be addressed by inhibitors. Depending on their binding sites and binding modes, the inhibitors show different degrees of cross-resistance that need to be considered when designing spray programmes for agricultural fungicides. The binding site of ametoctradin was unknown.Cross-resistance analyses, the reduction of isolated Pythium sp. bc1 complex in the presence of different inhibitors and molecular modelling studies were used to analyse the binding site and binding mode of ametoctradin. All three approaches provide data supporting the argument that ametoctradin binds to the Pythium bc1 complex similarly to stigmatellin.The binding mode of ametoctradin differs from other agricultural fungicides such as cyazofamid and the strobilurins. This explains the lack of cross-resistance with strobilurins and related inhibitors, where resistance is mainly caused by G143A amino acid exchange. Accordingly, mixtures or alternating applications of these fungicides and ametoctradin can help to minimise the risk of the emergence of new resistant isolates.

With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria’s L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained. Electronic supplementary material The online version of this article (doi:10.1007/s00894-012-1563-4) contains supplementary material, which is available to authorized users.