The early stages of drug discovery is a long and costly process. A way to reduce the time, resources, and financial investment spent is to apply computational tools. With the tremendous progress and achievements in computational chemistry, the application of computational tools in the drug lead discovery and design has increased. Today, computational chemistry is considered a highly valuable and well established tool in drug discovery. A variety of computational chemistry methods are used for guiding molecular design and finding new potential drugs and targets. Some examples of these methods are molecular dynamics simulations, free energy calculations, virtual screening, structure-activity relationship analysis, and so on. Despite the fact that computational chemistry technics are widely used in industry and academic environment, there is still room for improvement. Here, I present several studies in which I developed and applied computational chemistry tools in drug discovery problems. The first study is the development of a tool as part of the Open Force Field consortium to learn chemical perception of force fields typing rules. Secondly, I describe my work on using a new hybrid method to calculate free energies of small molecules. Thirdly, I present a binding mode prediction study to help the understanding of structure-activity relationship in lissoclimides. Lastly, I present a study applying molecular dynamic simulation to guide the redesigning of a macrocyclic peptide.