Sequencing technologies are producing a huge amount of data at a very fast rate. Human curators can't perform experiments for 3D structure analysis at the same pace. Automated electronic annotation of sequences exploits different mathematical and computational methodologies to extend properties of known protein sequences to others. Different communities are interested in this approach: researchers working on proteins can use electronic annotations to start testing hypotheses. On the other hand, experimental curators are interested in the features to look for, i.e. which function or process is the most probable in the protein they are going to investigate. In this way, the experiment can be targeted towards a specific and more detailed set of features. Researchers apply many computational methods to solve this problem, and often a combination of multiple strategies can achieve better performances. The purpose of this workshop is to present the state of the art in computational methods for protein sequence annotation, aiming to inspire the creation of even more precise and clever techniques, thus improving electronic annotation of protein sequences.