Background: A serious of actions have been taken to control the epidemic of the 2019-nCoV virus, and the effective therapeutic methods are in urgent needs to prevent infection. Fluoroquinolones are known synthetic group of antibiotics that have been the subject of many research interests. It was shown that this class of drugs could possess antiviral activity as a broad range of anti-infective activities. Based on these findings, we performed in silico molecular docking analysis to provide, for the first time, the basis for the potential evidence pointing ciprofloxacin and moxifloxacin ability to interact with COVID-19 Main Protease. Methods: In silico molecular docking analysis was applied to assess the possible ability of ciprofloxacin and moxifloxacin to interact with COVID-19 Main Protease (Mpro). Genetic Optimization for Ligand Docking (GOLD) 5.6.3 was used for the docking studies. Moreover, chloroquine and nelfinavir were used as positive controls for comparison. Findings: The obtained results pointed out that the tested antibiotics exert strong capacity for binding to COVID-19 Main Protease (Mpro). The analysis of the docking results showed that ciprofloxacin and moxifloxacin bound to the protein active site more strongly than native ligand. When comparing with positive controls, a detailed analysis of the ligand-protein interactions shows the tested fluoroquinolones exert a greater number of protein interactions than chloroquine and nelfinavir. It is worth emphasizing that ciprofloxacin binds to the protein with four strong hydrogen bonds (compared to one and two hydrogen bonds for chloroquine and nelfinavir, respectively) and a significant number of hydrophobic interactions. However, lower binding energy values were stated when compared to chloroquine and nelfinavir. Interpretation: Herein, for the first time, we have demonstrated that ciprofloxacin and moxifloxacin may interact with COVID-19 Main Protease (Mpro) which indicates that both fluoroquinolone antibiotics may be potential inhibitors of the tested protease. Funding Statement: Medical University of Silesia Grants no. KNW-1-037/K/9/O, KNW-1-055/K/9/O. Energy-minimization calculations have been carried out using resources provided by Wroclaw Centre for 818 Networking and Supercomputing (http://wcss.pl), Grant No. 382. Declaration of Interests: The authors declare no competing interests.