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Abstract
To explore alternative abaucin antibiotics predicting nanomolar affinities against Acinetobacter baumannii, thousands of virtual abaucin-derived molecules were randomly generated and selected. For this, alphafold-modeled A.baumannii lipoprotein outer membrane localization (Lol) complex proteins were targeted by DataWarrior "build evolutionary libraries". Abaucin-children libraries were generated from the abaucin-parent iteratively selecting those predicting higher affinities to the most probable A.baumannii LolCE docking-cavity. To improve accuracies, ~4000 abaucin-children docking-scores were consensed with those from AutoDockVina. The resulting laydown table provided with filter sliders would allow user-criteria to be applied. One example explored candidates predicting both higher nanomolar affinities to A.baumannii LolCE (to favor putative antibiotics) and lower affinities to E.coli LolCE (to favor narrow-bacterial spectrum hits). Despite being highly hypothetical, some of these abaucin-derived chemotypes may constitute another step towards exploring possible improvements for anti-A.baumannii antibiotics.
Supplementary materials
Title
- 4312AbaucinChildrenLibrary.dwar.
Description
A DW table containing 4312 adaucin-children. It was provided with threshold filters to their DW and ADV / LELP-corrected docking-scores to A.baumannii and to E.coli LolCE, including each of their molecular weights and clogP properties.
Actions
Title
- toxicprediction.dwam
Description
A DW macro file to eliminate all toxic children from any *.sdf file, rename the resulting files and save them into the corresponding dwar and sdf files.
Actions
