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Shape-directed protein assembly design

Periodic Reporting for period 1 - 3DPROTEINPUZZLES (Shape-directed protein assembly design)

Reporting period: 2018-06-01 to 2019-11-30

Large protein complexes carry out some of the most complex functions in biology. Such structures are often assembled spontaneously from individual components through the process of self-assembly. If self-assembled protein complexes could be engineered it would enable a wide range of applications in biomedicine, nanotechnology and materials science. These include targeted delivery of protein drugs into cells and specific compartments in cells, nanoreactors for efficient synthesis molecules using enzymes and synthesis of highly uniform nanoparticles. Such advances would be highly beneficial in developing new approaches for medical treatment and ecologically sustainable production of chemicals.

Current approaches for protein self-assembly design does not result in the assemblies with the required structural complexity to encode many of the sophisticated functions found in nature. Although impressive-looking protein containers have rationally been designed they have shortcomings such as large pores on the surface and lack of mechanism to assemble and disassemble the containers when loading them with molecules. Current methods also provide a very limited pool of building blocks for design of containers because the design starts from protein complexes, which are not as abundant as proteins consisting of single chains.

In this project, we propose a new protein design paradigm, shape directed protein design, in order to address shortcomings of the current methodology. The proposed method combines geometric shape matching and computational protein design. Using this approach, we will de novo design assemblies with a wide variety of structural states, including protein complexes with cyclic and dihedral symmetry as well as icosahedral protein capsids built from novel protein building blocks. The design efforts is also supported by the development of a high-throughput method to measure the stability of containers directly in cells, without having to purify them. This enables screening of thousands of protein variants and the possibility to improve designed proteins by mimicking evolution.
The first 18 months of this project has focused on developing the fundamental tools required to carry out the goals of this project. On the computational side we have developed methods for geometrical shape matching and comparison between matched proteins. We have also developed tools for design of proteins in the framework of the Rosetta macromolecular modelling package, the preeminent method for computational protein design. This include methods to model the complex symmetry of protein containers and approaches to carry out efficient molecular docking of proteins with this type of symmetry.

On the experimental side we have developed a pipeline for screening of protein variants in terms of stability inside bacterial cells. This involves developing methods for DNA library generation and bacterial cell sorting. We are now testing a first iteration of the method on simpler model system, including monomeric proteins.

A software for geometric alignment of proteins identified in with shape-matching techniques is being finalized and a manuscript will be submitted shortly about this. The graphical software, called ZEAL, will be released shortly as an open source program that can be installed on mac and pc.
The project has two components that are beyond the state of the art. On the computational side we develop a new paradigm in protein design, shape-based protein design. This will enable design of highly complex protein complexes with engineering of proteins custom-design geometrical shape. On the experimental side we develop a high-throughput assay in which millions of proteins can be screened for stability and protein expression. This will be broadly applicable in many areas of protein engineering.
Software develop for alignment of proteins matched by geometric shape-matching