Could Acinetobacter baumannii Lol-abaucin docking be improved?

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.

Star-shaped conformers generated by co-evolutionary docking predict cross-fitting glycoprotein trimer pre-fusion interfaces on VHSV fish rhabdovirus

“…The AutoDockVina (ADV) 46 algorithms (available at the PyRx-0.98/1.0 package) were employed to i) compare affinities between ADV and DWBEL-conformers, ii) quantify ADV-conformer affinities in ~ nM, iii) identify PyMol nearby amino acids in docked complexes between gpGVHSV and ADV-conformers [32][33][34][35] and iv) confirm the gpGVHSV cavities targeted by ADV-conformers. The ADV algorithm was selected among the numerous alternative docking programs because of higher accuracies and ongoing improvements 27,28,36,37 .…”

Tailoring evolved-ligands to Plasmodium circumsporozoite-protein

“…How the affinity and targeted cavities were confirmed? As in our most recent work 16 , the AutoDockVina (ADV) 46 and OpenBabel using mmff94s force-field algorithms (PyRx-0.98/1.0 packages) were employed because of their high accuracies and world-wide ongoing improvements 10,11,28,29 . ADV was employed to: i) initial identification of CSP ligands (L) and cavities (C), ii) quantify ADV-conformer affinities in ~ nM, iii) identify nearby amino acids in ADV docked complexes and iv) confirm the CSP cavities targeted by ADV-conformers.…”