Computational Design and Characterization of a Monomeric Helical Dinuclear Metalloprotein

Calhoun, Jennifer R.; Kono, Hidetoshi; Lahr, Steven J.; Wang, Wei; DeGrado, William F.; Saven, Jeffery G.

doi:10.1016/j.jmb.2003.10.004

Cited by 137 publications

(158 citation statements)

References 86 publications

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“…R and θ values, where the backbone atoms overlap, were discounted. In the context of a protein's nearest neighbors within each crystalline configuration, the site-specific probabilities of the 18 allowed amino acids, their side-chain conformations, and the weighted average energy over these sequence-rotamer states EðR; θÞ were estimated computationally (30,31,47). Effective solvation energy functions were not used (31), and no constraint was placed on the net charge of the protein.…”

Section: Resultsmentioning

confidence: 99%

“…In arriving at the sequence-structure energy landscape (Fig. 3A), a statistical thermodynamic method for calculating site-specific probabilities of the amino acids and the average energy over sequences was applied (30,31). The method uses the AMBER energy function (41) and a discrete rotamer library (62).…”

Section: Methodsmentioning

confidence: 99%

“…Computational protein design continues to advance (22)(23)(24)(25)(26)(27)(28)(29)(30)(31), and herein a strategy for designing a predetermined protein crystal structure is presented. A three-helix coiled-coil protein was designed de novo to form a polar, layered three-dimensional crystal having the P6 space group.…”

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confidence: 99%

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Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

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

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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%

Section: Methodsmentioning

confidence: 99%

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Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

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

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165

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“…Such an approach has been used in the design of a 114-residue four-helix metalloprotein (Calhoun et al, 2003). Secondly, the calculated probabilities may be used to guide a search algorithm.…”

Section: Probabilistic Approaches To Protein Designmentioning

confidence: 99%

“…Detailed descriptions of the energetic constraints have been discussed elsewhere (Calhoun et al, 2003;Kono & Saven, 2001) and are also presented in the Appendix.…”

Section: Statistical Theory Of Sequence Ensemblesmentioning

confidence: 99%

Progress in the development and application of computational methods for probabilistic protein design

Park

Kono²,

Wang

et al. 2005

Computers & Chemical Engineering

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. (2004). Progress in the development and application of computational methods for probabilistic protein design. Retrieved from http://repository.upenn.edu/cbe_papers/2 Progress in the development and application of computational methods for probabilistic protein design AbstractProteins exhibit a wide range of physical and chemical properties, including highly selective molecular recognition and catalysis, and are also key components in biological metabolic, catabolic, and signaling pathways. Given that proteins are well-structured and can now be rapidly synthesized, they are excellent targets for engineering of both molecular structure and biological function. Computational analysis of the protein design problem allows scientists to explore sequence space and systematically discover novel protein molecules. Nonetheless, the complexity of proteins, the subtlety of the determinants of folding, and the exponentially large number of possible sequences impede the search for peptide sequences compatible with a desired structure and function. Directed search algorithms, which identify directly a small number of sequences, have achieved some success in identifying sequences with desired structures and functions. Alternatively, one can adopt a probabilistic approach. Instead of a finite number of sequences, such calculations result in a probabilistic description of the sequence ensemble. In particular, by casting the formalism in the language of statistical mechanics, the site-specific amino acid probabilities of sequences compatible with a target structure may be readily identified. The computational probabilities are well suited for both de novo protein design of particular sequences as well as combinatorial, library-based protein engineering. The computed site-specific amino acid profile may be converted to a nucleotide base distribution to allow assembly of a partially randomized gene library. The ability to synthesize readily such degenerate oligonucleotide sequences according to the prescribed distribution is key to constructing a biased peptide library genuinely reflective of the computational design. Herein we illustrate how a standard DNA synthesizer can be used with only a slight modification to the synthesis protocol to generate a pool of degenerate DNA sequences, which encodes a predetermined amino acid distribution with high fidelity. AbstractProteins exhibit a wide range of physical and chemical properties, including highly selective molecular recognition and catalysis, and are also key components in biological metabolic, catabolic, and signaling pathways. Given that proteins are well-structured and can now be rapidly synthesized, they are excellent targets for engineering of both molecular structure and biological function. Computational analysis of the protein design problem allows scientists to explore sequence space and systematically discover novel protein molecules. Nonetheless, the complexity of proteins, the subtlety of the determinants of folding, and the exponentially large number of possible se...

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Structure and Phase Stability of Binary Zintl-Phase Compounds: Lithium–Group 13 Intermetallics and Metal-Doped Group 14 Clathrate Compounds

et al. 2002

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Eine neuartige Methode zur Selbstorganisation von Monomeren und zur Steuerung der Struktur eines De‐novo‐Helixbündelproteins wird beschrieben. Ein Guanin(G)‐reiches Oligodesoxynucleotidgerüst bildet einen H‐verbrückten DNA‐Quadruplex in Gegenwart von K+‐Gegenionen und induziert so eine helicale Struktur und eine vierfache Stöchiometrie in konjugierten, amphiphilen Peptidsequenzen. Das DNA‐Gerüst ist vielversprechend für den schnellen Aufbau künstlicher Proteine.

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Computational Design and Characterization of a Monomeric Helical Dinuclear Metalloprotein

Cited by 137 publications

References 86 publications

Computational design of a protein crystal

Computational design of a protein crystal

Progress in the development and application of computational methods for probabilistic protein design

Structure and Phase Stability of Binary Zintl-Phase Compounds: Lithium–Group 13 Intermetallics and Metal-Doped Group 14 Clathrate Compounds

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