Protlego: A Python package for the analysis and design of chimeric proteins

Abstract

AbstractMotivationGene duplication and recombination of protein fragments have led to the highly diverse protein space that we observe today. By mimicking this natural process, the design of protein chimeras via fragment recombination has proven experimentally successful and has opened a new era for the design of customizable proteins. The in-silico building of structural models for these chimeric proteins, however, remains a manual task that requires a considerable degree of expertise and is not amenable for high-throughput studies. Energetic and structural analysis of the designed proteins often require the use of several tools, each with their unique technical difficulties and available in different programming languages or web servers.ResultsWe have implemented a Python package that enables automated, high-throughput design of chimeras and their structural analysis. First, it is possible to fetch evolutionarily conserved fragments from a built-in database (also available at fuzzle.uni-bayreuth.de). These relationships can then be represented via networks or further selected for chimera construction via recombination. Designed chimeras or natural proteins are then scored and minimised with the Charmm and Amber forcefields and their diverse structural features can be analysed at ease. Here, we showcase Protlego’s pipeline by exploring the relationships between the P-loop and Rossmann superfolds and building and characterising their offspring chimeras. We believe that Protlego provides a powerful new tool for the protein design community.Availability and implementationProtlego is freely available at (https://hoecker-lab.github.io/protlego/) with tutorials and documentation.