Periodic Reporting for period 3 - 3DPROTEINPUZZLES (Shape-directed protein assembly design)
Reporting period: 2021-06-01 to 2022-11-30
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.
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 36 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 a computational pipeline for the design of protein capsids, using a new design approach called shape-directed protein design. The protocol identifies a proteins that have the right geometric shape to assemble into capsids with with the desired geometry. Then the position of the individual proteins with the assembly, considering the symmetry, is optimized. This is followed by redesign of the sequence at positions in the proteins that forms the interfaces within the assembly. In the context of this project we have developed new methodology for shape-based alignment of proteins with a method called ZEAL, developed a new protein-protein docking method called EVODOCK, and extended EVODOCK to handle the complex symmetries of container proteins.
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, bacterial cell sorting and next generation sequencing. We have demonstrated that our in vivo assay, consisting of two fluorescent outputs, is able to distinguish stable from unstable proteins. Then we expanded the method to enable comparison of lots of protein variants within the same experiments by combining the stability assay with cell sorting and DNA sequencing, and showed that the approach can be used to select for more stable proteins.
The experimental and computational methodology developed so far in this project can be of great value to researchers outside this project, and to find applications in the industrial setting as well.
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, bacterial cell sorting and next generation sequencing. We have demonstrated that our in vivo assay, consisting of two fluorescent outputs, is able to distinguish stable from unstable proteins. Then we expanded the method to enable comparison of lots of protein variants within the same experiments by combining the stability assay with cell sorting and DNA sequencing, and showed that the approach can be used to select for more stable proteins.
The experimental and computational methodology developed so far in this project can be of great value to researchers outside this project, and to find applications in the industrial setting as well.
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.