PROSPER protease substrates and cleavage site data

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.

本数据集为一套通过网页界面（PROSPER）向学术共同体开放的生物医学数据库。该网页界面支持用户针对24种不同蛋白酶类型开展蛋白酶底物及其切割位点的计算机模拟预测（in silico），涵盖天冬氨酸蛋白酶（Aspartic, A）、半胱氨酸蛋白酶（Cysteine, C）、金属蛋白酶（Metallo, M）与丝氨酸蛋白酶（Serine, S）四大蛋白酶家族。

自上线以来仅一年半时间，PROSPER便已吸引来自全球66个国家的4000余名独立访客，累计提交5000余次分析任务。鉴于其在蛋白酶生物学领域的重要贡献，PROSPER已被国际蛋白质水解学会（International Proteolysis Society, IPS）官方网站列为重要的生物信息学工具。

研究意义阐述
PROSPER（蛋白酶特异性预测服务器，PROtease Specificity Prediction servER）收录了海量蛋白酶相关数据集，蛋白酶在生物体内的"生死"代谢过程中发挥核心作用，涵盖神经、内分泌与心血管信号传导、食物消化、错误折叠或冗余蛋白的降解、免疫应答、细胞分裂以及细胞凋亡等过程。阐明蛋白酶生理功能的核心在于鉴定其天然底物，其终极目标不仅在于提升学界预测特定蛋白酶参与代谢过程的能力，更为靶向蛋白酶调控通路的治疗药物开发提供支撑。

诸多蛋白酶可在不同生理区间内切割多种蛋白，而蛋白切割过程会受到底物序列、底物构象与可及性等多种因素的影响。掌握蛋白酶的底物特异性可显著提升靶蛋白底物的预测效率，但目前此类数据仅能通过实验手段获取。若缺乏此类数据，则无法通过蛋白酶的结构或序列先验地推导其功能靶点。

为解决底物的先验鉴定难题，由惠斯托克教授与宋博士领衔的莫纳什大学研究团队开发了PROSPER——一款用于预测新型特异性底物及其切割位点的整合型服务器。学界可借助PROSPER完成预测任务，无需在实验室开展耗时良久的蛋白酶实验。依托PROSPER存储并开放共享的数据集，该网页服务器可帮助研究人员高效预测蛋白酶的底物切割情况，这不仅可用于评估当前治疗方案的有效性，还可为诸多重症新型治疗手段的开发提供有力证据支持。

搜集汇总

背景与挑战

背景概述

PROSPER蛋白酶底物和切割位点数据集是一个生物医学数据库，通过Web界面提供对24种蛋白酶类型的底物和切割位点的计算机预测，涵盖四大蛋白酶家族。该数据集自推出以来已广泛用于全球研究，支持蛋白酶功能预测和疗法开发，被国际蛋白水解学会认可为重要工具。