De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

By Po-Ssu Huang, K. Feldmeier, F. Parmeggiani, D. Velasco, Birte Höcker, David Baker. 2015

245 citations recorded by the source corpus.

Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of 4-fold symmetrical (β/α)8-barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of sidechain-backbone hydrogen bonding for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical with the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has only sampled a subset of the sequence space available to the TIM-barrel fold. The ability to de novo design TIM-barrels opens new possibilities for custom-made enzymes.

Subfields: Immunology, Oncology, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

Protein sequence design with a learned potential (2022, methodology): “5bvl is distant in sequence and structure from any known protein, and contains local structural features that differ signi ﬁ cantly from naturally occurring TIM-barrels 44 .”
The coming of age of de novo protein design (2016, background): “In the TIM barrel, the backbone design principles, together with the geometry of closed β-sheets, makes four-fold symmetry the highest that can be attained and forces the two α-helices in each α–β–α–β unit to differ in length 42 .”
Deep learning techniques have significantly impacted protein structure prediction and protein design. (2021, background): “…with designing proteins with novel structures and functions is that de novo protein design remains somewhat of an art form, as designers are often required to manually specify how the different secondary structure elements (SSEs) should pack in order to produce a well-folded protein [50,51 ,60].”
Recent advances in de novo protein design: Principles, methods, and applications (2021, methodology): “Symmetry was used to design a 4-fold ( colors ) symmetric TIM barrel (34) and repeat proteins (67).”
Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network (2023, methodology): “Crambin was characterized by thermal denaturation measured by 1 H-NMR 65 , while the other three were characterized by thermal and chemical denaturation measured by CD spectroscopy 66 – 68 (slow unfolding kinetics were reported for the designed three-helix bundle well).”
Protein sequence design with a learned potential (2020, methodology): “In the core region, which was noted as being highly convergent in the original study [7], designs were variable and yet densely packed (Figure 6c).”
A general-purpose protein design framework based on mining sequence–structure relationships in known protein structures (2018, unknown): “Nevertheless, despite all of these developments, and many examples of successful designs in the literature (18, 26-35), it is still the case that CPD methods are not robust.”
Hallucinating protein assemblies (2022, background): “While there have been a number of successes ( 8 – 10 ), current approaches require specification of the structure of the protomers in advance, and with the exception of parametrically designed helical bundles ( 11 , 12 ), have involved rigid body docking of previously characterized monomers into…”
Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion (2020, unknown): “An artificial TIM barrel designed with atomic-level accuracy was created previously using the Rosetta macromolecular and design platform (16, 17).”