In the modern age, computer-aided drug design plays a central role in the identification of new drug candidates both for academia and industry. One of the most successful computational approaches is docking-based virtual screening (VS), which is used to predict the interaction between a ligand, typically small molecules, and its molecular target either protein or nucleic acid. In general, the resulting ligand/protein complexes are evaluated and ranked according to a scoring function, which estimates the strength of the binding interaction. However, the approximation of the docking sampling methodologies produces many false positives and false negatives, that affect the drug design success rate. More accurate calculations such as molecular dynamics (MD) simulations, are often required to validate the docking results. Despite the numerous software available for the analysis of the VS and MD results, none of them allows handling both the large number of docking complexes (i.e., one protein with different ligands) and the MD trajectories. As a consequence, drug design can become a user-unfriendly and time demanding process with the investigator asked to learn different programs. In this scenario, the Drug Discovery Tool (DDT) was developed to overcome such limitation providing a fast and automated analysis platform for VS and MD calculations. DDT is designed as a graphics user interface (GUI) plugin for the Visual Molecular Dynamics (VMD) software and is able to manage a large number of ligand/protein complexes obtained from the AutoDock4 (AD4) docking program and the MD trajectories from the widely used software GROMACS and Amber. DDT delivers four main outcomes: - Ligand ranking based on a ligand/protein interaction energy score; - Ligand ranking based on the cluster analysis of the ligands’ binding poses; - Identification of the target’s residues forming the most occurring interactions with the ligands; - Plotting the ligands’ centre-of-mass coordinates in the Cartesian space. DDT allows saving the best ligand/protein complexes using a variety of user-defined options. Through its intuitive and user-friendly GUI, even a novel investigator can retrieve structural and energetics data on the ligand/protein binding complexes.