Identification of a Family of Glycoside Derivatives Biologically Active against Acinetobacter baumannii and Other MDR Bacteria Using a QSPR Model.

As the rate of discovery of new antibacterial compounds for multidrug-resistant bacteria is declining, there is an urge for the search for molecules that could revert this tendency. Acinetobacter baumannii has emerged as a highly virulent Gram-negative bacterium that has acquired multiple resistance mechanisms against antibiotics and is considered of critical priority. In this work, we developed a quantitative structure-property relationship (QSPR) model with 592 compounds for the identification of structural parameters related to their property as antibacterial agents against A. baumannii . QSPR mathematical validation (R2 = 70.27, RN = -0.008, a(R2) = 0.014, and δK = 0.021) and its prediction ability (Q2 LMO = 67.89, Q2 EXT = 67.75, a(Q2) = -0.068, δQ = 0.0, rm2¯ = 0.229, and Δrm2 = 0.522) were obtained with different statistical parameters; additional validation was done using three sets of external molecules (R2 = 72.89, 71.64 and 71.56). We used the QSPR model to perform a virtual screening on the BIOFACQUIM natural product database. From this screening, our model showed that molecules 32 to 35 and 54 to 68 , isolated from different extracts of plants of the Ipomoea sp., are potential antibacterials against A. baumannii . Furthermore, biological assays showed that molecules 56 and 60 to 64 have a wide antibacterial activity against clinically isolated strains of A. baumannii , as well as other multidrug-resistant bacteria, including Staphylococcus aureus , Escherichia coli , Klebsiella pneumonia , and Pseudomonas aeruginosa . Finally, we propose 60 as a potential lead compound due to its broad-spectrum activity and its structural simplicity. Therefore, our QSPR model can be used as a tool for the investigation and search for new antibacterial compounds against A. baumannii .