Structural specificity in coiled-coil interactions

Grigoryan, Gevorg; Keating, Amy E.

doi:10.1016/j.sbi.2008.04.008

Cited by 267 publications

(293 citation statements)

References 58 publications

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“…In many applications of protein design, designability of a structure is made accessible by using structures from naturally occurring proteins (24,27,32,33), but here both the structure of the protein as well as its crystalline ordering are specified de novo. A trimeric coiled-coil protein is designed to fold into a stable unit that then further assembles into a crystalline structure.…”

Section: Resultsmentioning

confidence: 99%

Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

158

165

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Protein crystals have catalytic and materials applications and are central to efforts in structural biology and therapeutic development. Designing predetermined crystal structures can be subtle given the complexity of proteins and the noncovalent interactions that govern crystallization. De novo protein design provides an approach to engineer highly complex nanoscale molecular structures, and often the positions of atoms can be programmed with sub-Å precision. Herein, a computational approach is presented for the design of proteins that self-assemble in three dimensions to yield macroscopic crystals. A three-helix coiled-coil protein is designed de novo to form a polar, layered, three-dimensional crystal having the P6 space group, which has a "honeycomb-like" structure and hexameric channels that span the crystal. The approach involves: (i) creating an ensemble of crystalline structures consistent with the targeted symmetry; (ii) characterizing this ensemble to identify "designable" structures from minima in the sequencestructure energy landscape and designing sequences for these structures; (iii) experimentally characterizing candidate proteins. A 2.1 Å resolution X-ray crystal structure of one such designed protein exhibits sub-Å agreement [backbone root mean square deviation (rmsd)] with the computational model of the crystal. This approach to crystal design has potential applications to the de novo design of nanostructured materials and to the modification of natural proteins to facilitate X-ray crystallographic analysis.M olecular design provides powerful tools for exploring how molecular properties dictate macroscopic structure and function. One of the most precise forms of self-organization, crystallization achieves orientation and symmetry across many length scales and can be leveraged to engineer materials with well-defined molecular order (1). In addition to their central role in structure determination, molecular crystals have many applications, including nanoparticle templating (2, 3), nonlinear optical devices (4), molecular scaffolding (5), and porous frameworks (6). A predictive understanding of how to achieve self-assembled macroscale structure and desired properties remains challenging, however, particularly when large, conformationally flexible molecules are employed.Small synthetic molecules have been designed that display complementary functional groups in a manner consistent with a chosen crystal structure. Intermolecular contacts are often patterned using strong, directional interactions (e.g., hydrogen bonding, metalcoordination, and electrostatic interactions) (7). The constituent molecules, however, are typically small and synthetic, thus limiting size, shape, and functionality. Hence, simultaneously achieving functional properties and the presentation of complementary intermolecular interactions that confer a targeted crystal structure can be difficult. Commonly, weak intermolecular forces stabilize crystalline ordering, and as a result, quantitative, predictive approaches to crystal de...

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Section: Resultsmentioning

confidence: 99%

Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

158

165

View full text Add to dashboard Cite

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“…S6A). The atypical presence of polar residues at heptad-repeat positions a and d (i.e., Ser-117 and Thr-127 at positions a and d, respectively), together with the atypical lack of intra-and inter-helical electrostatic interactions between residues at heptad-repeat positions e and g, are likely to reduce coiled-coil stability (22). The single substitution of Thr-127 by Leu, a hydrophobic residue that is particularly favored at position d of the heptad sequence, is not sufficient by itself to stabilize the coiled coil, as judged by NMR analysis of the CAP-T127L mutant (Fig.…”

Section: Substitutions Resulting In Constitutively Active Phenotype Smentioning

confidence: 99%

Structural basis for cAMP-mediated allosteric control of the catabolite activator protein

Popovych

Tzeng

Tonelli

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

198

278

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“…Over-and underrepresentation of geometries within select structural motifs has also been associated with designability (10,26). A simple example is the α-helical coiled coil, a ubiquitous protein domain in which two or more helices wrap around each other (52). Geometric parameters in natural coiled coils fall within well-defined ranges (10), also corresponding to structures designed either de novo or rationally (52)(53)(54).…”

Section: Significancementioning

confidence: 99%

“…A simple example is the α-helical coiled coil, a ubiquitous protein domain in which two or more helices wrap around each other (52). Geometric parameters in natural coiled coils fall within well-defined ranges (10), also corresponding to structures designed either de novo or rationally (52)(53)(54). On the other hand, the majority of parameter space, much of it entirely plausible from the perspective of molecular mechanics, does not appear to contain folded states for natural or designed sequences.…”

Section: Significancementioning

confidence: 99%

Tertiary alphabet for the observable protein structural universe

Mackenzie

Zhou

Grigoryan

2016

Proc. Natl. Acad. Sci. U.S.A.

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Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.tertiary motif | structural degeneracy | protein structural universe | sequence-structure relationships | structural modularity I n this work, we aim to decompose the protein structure space into its basic elements as a way of understanding its design principles and describing its limits. Reductionist representations of protein structure have been of long-standing interest (1), with many studies having shown degeneracy at various structural levels (2-5). Features ranging from backbone or side-chain dihedral angles (6, 7) to domains and folds (8, 9) have been classified, and structural basins of attraction have been found in select motifs (10-17), offering a glimpse of a modular space with frequently repeating elements. The reason behind this modularity appears to be a combination of evolutionary history and the fundamental physics of structure. In particular, degeneracy at the level of domains, folds, and functional modules is likely strongly influenced by evolution, whereby such elements recur in different proteins often because of a common ancestor (18,19). On the other hand, statistics of more detailed structural features are better explained from the thermodynamic perspective. For example, observed Ramachandran backbone dihedral angle preferences are largely determined...

show abstract

Structural specificity in coiled-coil interactions

Cited by 267 publications

References 58 publications

Computational design of a protein crystal

Computational design of a protein crystal

Structural basis for cAMP-mediated allosteric control of the catabolite activator protein

Tertiary alphabet for the observable protein structural universe

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