PROSPER protease substrates and cleavage site data

Full description

The collection consists of a biomedical database presented to the community via a web interface (“PROSPER”). The web interface provides the ability for users to perform in silico prediction of protease substrates and their cleavage sites for twenty-four different protease types, covering four major protease families; Aspartic (A), Cysteine (C), Metallo (M) and Serine (S). Within only one and a half years since its inception, PROSPER has attracted more than 4,000 unique visitors worldwide from 66 countries and 5,000 job submissions. As a recognition of these important contributions to the protease biology field, PROSPER has been highlighted as a significant bioinformatic tool at the official website of the International Proteolysis Society (IPS). Significance statement PROSPER (PROtease Specificity Prediction servER) contains an extensive database of proteases, which play a central role in "life and death" metabolic processes within biological organisms. These include neural, endocrine and cardiovascular signalling, digestion, degrading misfolded or unwanted proteins, immunity, cell division and apoptosis. The key to understanding the physiological role of a protease is to identify its natural substrates, with the end goal of not only enhancing the community's ability to predict the way in which specific proteases engage in metabolic processes, but to support the development of therapeutics that target specific protease-regulated pathways. Many proteases have the potential to cleave multiple proteins in different physiological compartments, and protein cleavage can be influenced by factors such as substrate sequence, substrate conformation and accessibility. Knowledge of the substrate specificity of a protease can dramatically improve the ability to predict target protein substrates, however at present this data can only be derived from experimental approaches. In the absence of such data, the targets of protease function cannot be deduced a priori from the structure or sequence of the protease. In order to address the problem of a priori substrate identification, PROSPER (an integrated server for the prediction of specific novel substrates and their cleavage sites) was developed by researchers at Monash University (led by Professor Whisstock and Dr. Song). The research community makes use of PROSPER to perform predictions, as opposed to running more time-consuming protease experiments in laboratories. With the results of making use of the data stored within, and made available through PROSPER, this web server is able to allow researchers to efficiently predict protease substrate cleavage, which is used to not only determine the efficacy of current therapeutic treatments, but provide evidence that can be used to support the development of new treatments and approaches to many serious maladies.