Designing Protein Energy Landscapes

Saven, Jeffery G.

doi:10.1021/cr000058w

Cited by 48 publications

(27 citation statements)

References 236 publications

(518 reference statements)

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“…By using this minimal value and the entropy estimate above for the single pair, a contact will now be defined as minimally frustrated if its native energy is at the higher end of the distribution of decoy energies, having a frustration index as measured with a Z score of 0.78 or higher magnitude; that is, the majority (but by no means all) of other amino acid pairs in that position would be unfavorable. The fact that many variants of that pair also would lead to minimally frustrated interactions is consistent with the known sequence degeneracy of proteins (7). Conversely, a contact will be defined as highly frustrated if E 0 is at the other end of the distribution with a local frustration index lower than Ϫ1; that is, unlike for a minimally frustrated pair, most other amino acid pairs at that location would be more favorable for folding than the native ones by more than one standard deviation of that distribution.…”

Section: Resultssupporting

confidence: 59%

“…A global criterion for the landscape to be funneled to the native state emerges from this theory, which hinges on a ratio of the energy difference between the native structure from alternatives to the magnitude of the fluctuations of the decoy energies (3). This global Z-score criterion provides a practical, quantitative route to decoding effective energy functions for predicting protein structure from sequence (3,4), predicting folding intermediates (5,6), and designing de novo foldable proteins (7,8).…”

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confidence: 99%

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Localizing frustration in native proteins and protein assemblies

Ferreiro

Hegler

Komives

et al. 2007

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

313

441

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We propose a method of quantifying the degree of frustration manifested by spatially local interactions in protein biomolecules. This method of localization smoothly generalizes the global criterion for an energy landscape to be funneled to the native state, which is in keeping with the principle of minimal frustration. A survey of the structural database shows that natural proteins are multiply connected by a web of local interactions that are individually minimally frustrated. In contrast, highly frustrated interactions are found clustered on the surface, often near binding sites. These binding sites become less frustrated upon complex formation.protein folding ͉ protein function ͉ energy landscape

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Section: Resultssupporting

confidence: 59%

mentioning

confidence: 99%

Localizing frustration in native proteins and protein assemblies

Ferreiro

Hegler

Komives

et al. 2007

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

313

441

View full text Add to dashboard Cite

show abstract

“…For example, the optimal 5-letter alphabet is {IAGEK}, which is same as that observed in the molecular design experiment [60,91]. These groupings are further checked with simplified models [92,93].…”

Section: Simplification Based On Pairwise Interaction Between Amino Amentioning

confidence: 94%

Simplification of complexity in protein molecular systems by grouping amino acids: a view from physics

Wang

2016

Advances in Physics: X

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“…Directed protein design has been the subject of several recent reviews (Kraemer-Pecore et al, 2001;Saven, 2001;Street & Mayo, 1999).…”

Section: "Directed" Methods Of Protein Designmentioning

confidence: 99%

“…The design of proteins requires three main elements (Saven, 2001). One being a target structure or topology, which usually involves specifying the coordinates of atoms in the polypeptide backbone.…”

Section: Protein Designmentioning

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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Designing Protein Energy Landscapes

Cited by 48 publications

References 236 publications

Localizing frustration in native proteins and protein assemblies

Localizing frustration in native proteins and protein assemblies

Simplification of complexity in protein molecular systems by grouping amino acids: a view from physics

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

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