Docking and PLS Studies on a Set of Thiophenes RNA Polymerase Inhibitors Against Staphylococcus aureus

Staphylococcus aureus lives in commensalism with the majority of the population, being recognized as an important pathogen in patients with chronic liver diseases and can cause a deadly infection. The use of antibiotics as rifampin for the chemotherapy of infections caused by S. aureus has resulted in the selection of mutants with resistance. In an attempt to combat resistant strains new research is continuously conducted, as example searching new biological targets or new inhibitors such as tiophenes derivatives that can inhibit the RNA polymerase enzyme. This work investigated the set of tiophenes, selected from of literature and with RNA polymerase enzyme inhibitory activity of S. aureus. After seeking further information on existing scientific literature, the compounds under study were applied the methodologies of PLS, docking and calculation of Molecular Interaction Fields (MIFs) using Pentacle and VolSurf programmes. In addition, a comparison was made with two tiophenes synthesized in our laboratory and which have been tested against the bacteria. Docking studies showed that active compounds had more interactions with the amino acids on active site when compared with rifampicin. The best model obtained in PLS, considering two LVs (latent variables), after leave-one-out-validation, exhibited the statistical parameters q(cv)(2) = 0.68 and r(2) = 0.85. External prediction model presented a r(ext)(2) = 0.67. The obtained model through PLS analyses was able to predict the behavior of compounds synthesized by us. So we extract structural features important for the activity of these compounds. In this paper, first we discussed the topics: S. aureus, tiophenes, RNA polymerase, docking and QSAR methodologies. Then we have selected a series of 56 tiophenes from literature, which have their biological activity tested against the RNA polymerase enzyme of S. aureus. The compounds were subsequently carried out for Partial Least Squares (PLS) Analysis.