Structure-based design of novel polyhedral protein nanomaterials

Khmelinskaia, Alena; Wargacki, Adam J.; King, Neil P.

doi:10.1016/j.mib.2021.03.003

Cited by 25 publications

(24 citation statements)

References 62 publications

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“…We designed the JUPITER curriculum to address an ongoing scientific challenge: improving the success rate of current computational methods for the de novo design of self-assembling protein complexes using the Rosetta software suite. [22][23][24][25][26][27][28][29][30][31][32][33][34] These methods focus on docking oligomeric protein building blocks into target symmetric architectures (e.g., icosahedral point group symmetry), followed by protein-protein interface design to generate low-energy interfaces between the building blocks that drive assembly specifically to the target structure. While such assemblies are well-suited for molecular encapsulation or display applications such as cellular delivery and vaccine development, [34][35][36][37][38][39] current computational models do not allow us to confidently predict the success or stability of design models.…”

Section: Program Overviewmentioning

confidence: 99%

“…[22][23][24][25][26][27][28][29][30][31][32][33][34] These methods focus on docking oligomeric protein building blocks into target symmetric architectures (e.g., icosahedral point group symmetry), followed by protein-protein interface design to generate low-energy interfaces between the building blocks that drive assembly specifically to the target structure. While such assemblies are well-suited for molecular encapsulation or display applications such as cellular delivery and vaccine development, [34][35][36][37][38][39] current computational models do not allow us to confidently predict the success or stability of design models. Indeed, many designs aggregate or fail to assemble, due to misfolding or suboptimal assembly conditions.…”

Section: Program Overviewmentioning

confidence: 99%

“…33,40 Protein designers often test tens to hundreds of designs to find a handful of nanoparticles that assemble to the desired structure. 34,41,42 To better understand the pitfalls of current nanoparticle design methods, we aimed to computationally distinguish between successful and unsuccessful protein nanoparticle designs. While several published efforts to stabilize monomeric proteins demonstrated high success rates based on approaches using phylogenetic analysis, structure-based rational design, or sequence-based design, [43][44][45][46][47][48][49] none of these approaches addressed the stability of interfaces between multiple interacting proteins and its effect on design success.…”

Section: Program Overviewmentioning

confidence: 99%

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Increasing computational protein design literacy through cohort-based learning for undergraduate students

Yang

Divine

Kang

et al. 2022

Preprint

Self Cite

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Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work-study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and eliminated an important learning opportunity. To address these challenges, we created a paid, fully-remote, cohort-based research curriculum in computational protein design. Our curriculum used existing protein design methods as a platform to first educate and train undergraduate students and then to test research hypotheses. In the first phase, students learned computational methods to assess the stability of designed protein assemblies. In the second phase, students used a larger dataset to identify factors that could improve the accuracy of current protein design algorithms. This cohort-based program created valuable new research opportunities for undergraduates at our institute and enhanced the undergraduates' feeling of connection with the lab. Students learned transferable and useful skills such as literature review, programming basics, data analysis, hypothesis testing, and scientific communication. Our program provides a model of structured computational research training opportunities for undergraduate researchers in any field for organizations looking to expand educational access.

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Section: Program Overviewmentioning

confidence: 99%

Section: Program Overviewmentioning

confidence: 99%

Section: Program Overviewmentioning

confidence: 99%

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Increasing computational protein design literacy through cohort-based learning for undergraduate students

Yang

Divine

Kang

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…A promising approach to this issue is the use of templates based on self-assembling biological materials, such as nucleic acids and proteins [ 3 – 4 ]. Biological scaffolds can be programmed through predictable chemical interactions, such as DNA base pairing, disulfide bond formation, and metal coordination, to form complex, well-defined nanostructures [ 5 – 6 ]. Viruses and virus-like particles (VLPs) possess many advantageous properties for biotemplating applications [ 7 – 8 ].…”

Section: Introductionmentioning

confidence: 99%

Alcohol-perturbed self-assembly of the tobacco mosaic virus coat protein

Abu-Baker

Blum

2022

Beilstein J. Nanotechnol.

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The self-assembly of the tobacco mosaic virus coat protein is significantly altered in alcohol–water mixtures. Alcohol cosolvents stabilize the disk aggregate and prevent the formation of helical rods at low pH. A high alcohol content favours stacked disk assemblies and large rafts, while a low alcohol concentration favours individual disks and short stacks. These effects appear to be caused by the hydrophobicity of the alcohol additive, with isopropyl alcohol having the strongest effect and methanol the weakest. We discuss several effects that may contribute to preventing the protein–protein interactions between disks that are necessary to form helical rods.

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“…Native self-assembling PNPs are natural structures (ferritins, small heat shock proteins, vaults, encapsulins and lumazine synthase) that perform biological roles in living cells [14][15][16][17]; and virus-like particles (VLP) of which prominent examples are cowpea chlorotic mottle virus (CCMV), bacteriophage MS2, hepatitis B virus (HBV), bacteriophage P22 and many others [18]. De novo designed PNPs such as those developed by the Baker [19,20], Yeates [21] and King [22] groups are also self-assembling nanocages but they are developed by computational programming and simulations.…”

Section: Introductionmentioning

confidence: 99%

Bioengineering bacterial encapsulin nanocompartments as targeted drug delivery system

Steen

Khalife

Colant

et al. 2021

Synthetic and Systems Biotechnology

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The development of Drug Delivery Systems (DDS) has led to increasingly efficient therapies for the treatment and detection of various diseases. DDS use a range of nanoscale delivery platforms produced from polymeric of inorganic materials, such as micelles, and metal and polymeric nanoparticles, but their variant chemical composition make alterations to their size, shape, or structures inherently complex. Genetically encoded protein nanocages are highly promising DDS candidates because of their modular composition, ease of recombinant production in a range of hosts, control over assembly and loading of cargo molecules and biodegradability. One example of naturally occurring nanocompartments are encapsulins, recently discovered bacterial organelles that have been shown to be reprogrammable as nanobioreactors and vaccine candidates. Here we report the design and application of a targeted DDS platform based on the Thermotoga maritima encapsulin reprogrammed to display an antibody mimic protein called Designed Ankyrin repeat protein (DARPin) on the outer surface and to encapsulate a cytotoxic payload. The DARPin9.29 chosen in this study specifically binds to human epidermal growth factor receptor 2 (HER2) on breast cancer cells, as demonstrated in an in vitro cell culture model. The encapsulin-based DDS is assembled in one step in vivo by co-expressing the encapsulin-DARPin9.29 fusion protein with an engineered flavin-binding protein mini-singlet oxygen generator (MiniSOG), from a single plasmid in Escherichia coli. Purified encapsulin-DARPin_miniSOG nanocompartments bind specifically to HER2 positive breast cancer cells and trigger apoptosis, indicating that the system is functional and specific. The DDS is modular and has the potential to form the basis of a multi-receptor targeted system by utilising the DARPin screening libraries, allowing use of new DARPins of known specificities, and through the proven flexibility of the encapsulin cargo loading mechanism, allowing selection of cargo proteins of choice.

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Structure-based design of novel polyhedral protein nanomaterials

Cited by 25 publications

References 62 publications

Increasing computational protein design literacy through cohort-based learning for undergraduate students

Increasing computational protein design literacy through cohort-based learning for undergraduate students

Alcohol-perturbed self-assembly of the tobacco mosaic virus coat protein

Bioengineering bacterial encapsulin nanocompartments as targeted drug delivery system

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