Abstract
Motivation It is becoming routine to design protein structures de novo, with many interesting and useful examples in the literature. However, most sequences of designed proteins could be classed as failures when characterised in the lab, usually as a result of low expression, misfolding, aggregation or lack of function. This high attrition rate makes protein design unreliable and costly. These limitations could potentially be addressed if it were quick and easy to generate a set of high-quality metrics and information regarding designs, which could be used to make reproducible and data-driven decisions about which designs to characterise experimentally.
Results We present DE-STRESS (DEsigned STRucture Evaluation ServiceS), a web application for the evaluation of structural models of designed and engineered proteins. DE-STRESS has been designed to be simple, intuitive to use and responsive. It provides a wealth of information regarding designs, as well as tools to help contextualise the results and formally describe the properties that a design requires to be fit for purpose.
Availability DE-STRESS is available for non-commercial use, without registration, through the following website: https://pragmaticproteindesign.bio.ed.ac.uk/de-stress/. Source code for the application is available on GitHub: https://github.com/wells-wood-research/de-stress. The data used to generate reference sets is available through a GraphQL API, with the following URL: https://pragmaticproteindesign.bio.ed.ac.uk/big-structure/graphql.
Competing Interest Statement
The authors have declared no competing interest.