Antibacterial drug efficacy decrease is a consistent problem in both basic and advanced medicine. Every year, an approximately 214,000 infants die caused by antibacterial-resistant bacteria. As a consequence, the development of commonly available drugs is essential. For considerations such as high accuracy, reducing time and effort, and high cost, the starting from a theoretical chemical study to find alternative treatments is preferable. In this study 683 Quinoline derivatives are designed and controlled by chemical programs that obey the laws of quantum chemistry and classical mechanics. Using Molecular Docking and ΔG, the best 69 Quinoline derivatives were determined. Compounds (H1-H20) showed distinct activity against the New Delhi Metallo-β-Lactamase-1 protein from Klebsiella pneumoniae were H1(ΔG =-8.115). (G1-G20) against Gyrase B from E. coli were G1 (ΔG =-9.611). (W1-W20) against S1:DHFR from Staphylococcus aureus were W1 (ΔG =-8.254). (N1-N20) against Azobenzene from Bacillus subtilis reductase were N1 (ΔG =-6.69). Several compounds have also shown activity against more than one protein like H2 (N15W17). A DFT study was followed to find HOMO (-0.20 to -0.26 eV), LUMO (-0.06 to -0.11 eV), Gap (0.10 to 0.17 eV) for the studied derivatives. These values have been used to determine several molecular properties such as Ionization Potential, Softness and Hardness. Drug-Likeness Predictions (ADME) were applied to show that it obeyed Lipinski's Rule in terms of molecular mass, log P, Hydrogen bonding donors and acceptors. It was found that all the values obtained are within the acceptable values for the use of suggested Quinoline derivatives as medicine