Parkinson's is a neurodegenerative disease that lately is becoming more frequent, that is why this Masters' thesis has the aim of finding a list of drugs likely to become therapeutic
tools against Parkinson's disease by using computational techniques that reduce the time and costs of the search for new drugs. The methodology used starts with the search of
those key proteins in Parkinson's disease and proceeds with the search of the 3D structures which are used for a virtual screening and finding those ligands capable to bind to the protein cavities. These ligands are likely to be drugs against Parkinson's disease once their pharmacokinetic properties are analyzed.