Compact Structure Patterns in Proteins

Chitturi, Bhadrachalam; Shi, Shuoyong; Kinch, Lisa N.; Grishin, Nick V.

doi:10.1016/j.jmb.2016.07.022

Cited by 23 publications

(18 citation statements)

References 67 publications

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“…Focusing on the methods that rely on structural information, Grishin and colleagues (20) recently proposed a method to enumerate constructively all idealised parallel/antiparallel arrangements of up to 5 SSEs. This work proposed a systematic enumeration of all possible parallel/antiparallel arrangements using a 3D lattice model.…”

Section: Resultsmentioning

confidence: 99%

“…Early definitions of supersecondary structures relied strongly on experts spotting and naming them (4,12). With the steady growth of the wwPDB, several methods have been developed to identify automatically, with varying operational definitions, a library of substructures that form what can be considered as the 3D building blocks of protein structures (8,(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25). However, these approaches yielded limited libraries containing mostly short oligopeptide fragments or assemblies of typically 2 to 4 secondary structural elements.…”

Section: Introductionmentioning

confidence: 99%

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Universal architectural concepts underlying protein folding patterns

Lesk

Subramanian²,

Allison³

et al. 2018

Preprint

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What is the architectural 'basis set' of the observed universe of protein structures? Using information-theoretic inference, we answer this question with a comprehensive dictionary of 1,493 substructural concepts. Each concept represents a topologically-conserved assembly of helices and strands that make contact. Any protein structure can be dissected into instances of concepts from this dictionary. We dissected the world-wide protein data bank and completely inventoried all concept instances. This yields an unprecedented source of biological insights. These include: correlations between concepts and catalytic activities or binding sites, useful for rational drug design; local amino-acid sequence-structure correlations, useful for ab initio structure prediction methods; and information supporting the recognition and exploration of evolutionary relationships, useful for structural studies. An interactive site, PROÇODIC, at http://lcb.infotech.monash.edu.au/prosodic (click) provides access to and navigation of the entire dictionary of concepts, and all associated information.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Universal architectural concepts underlying protein folding patterns

Lesk

Subramanian²,

Allison³

et al. 2018

Preprint

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“…A number of connectivity rules have been determined. In a small number of consecutive SSEs, β‐hairpin, α‐hairpin, βαβ‐unit, or Greek‐key motifs are preferable, while β‐X‐β units should be right‐handed, and “split β‐turns” are unfavorable . Loop crossing is unfavorable as the spatial position of loops .…”

Section: Introductionmentioning

confidence: 99%

“…In a small number of consecutive SSEs, b-hairpin, a-hairpin, bab-unit, or Greekkey motifs are preferable, [19][20][21] while b-X-b units should be right-handed, 12,22,23 and "split b-turns" are unfavorable. 24 Loop crossing is unfavorable as the spatial position of loops. 25 Recently, it was demonstrated that these constraints strongly limit the number of folds.…”

Section: Introductionmentioning

confidence: 99%

Rules for connectivity of secondary structure elements in protein: Two–layer αβ sandwiches

2017

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In protein structures, the fold is described according to the spatial arrangement of secondary structure elements (SSEs: α-helices and β-strands) and their connectivity. The connectivity or the pattern of links among SSEs is one of the most important factors for understanding the variety of protein folds. In this study, we introduced the connectivity strings that encode the connectivities by using the types, positions, and connections of SSEs, and computationally enumerated all the connectivities of two-layer αβ sandwiches. The calculated connectivities were compared with those in natural proteins determined using MICAN, a nonsequential structure comparison method. For 2α-4β, among 23,000 of all connectivities, only 48 were free from irregular connectivities such as loop crossing. Of these, only 20 were found in natural proteins and the superfamilies were biased toward certain types of connectivities. A similar disproportional distribution was confirmed for most of other spatial arrangements of SSEs in the two-layer αβ sandwiches. We found two connectivity rules that explain the bias well: the abundances of interlayer connecting loops that bridge SSEs in the distinct layers; and nonlocal β-strand pairs, two spatially adjacent β-strands located at discontinuous positions in the amino acid sequence. A two-dimensional plot of these two properties indicated that the two connectivity rules are not independent, which may be interpreted as a rule for the cooperativity of proteins.

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“…These applications motivate the study of MIS, MDS and other graph theoretic problems on layered graphs. In general, graph theoretic problems, like subgraph isomorphism, and its variations have extensive applications in computational biology, e.g., references [31,32].…”

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confidence: 99%

Layered Graphs: Applications and Algorithms

et al. 2018

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The computation of distances between strings has applications in molecular biology, music theory and pattern recognition. One such measure, called short reversal distance, has applications in evolutionary distance computation. It has been shown that this problem can be reduced to the computation of a maximum independent set on the corresponding graph that is constructed from the given input strings. The constructed graphs primarily fall into a class that we call layered graphs. In a layered graph, each layer refers to a subgraph containing, at most, some k vertices. The inter-layer edges are restricted to the vertices in adjacent layers. We study the MIS, MVC, MDS, MCV and MCD problems on layered graphs where MIS computes the maximum independent set; MVC computes the minimum vertex cover; MDS computes the minimum dominating set; MCV computes the minimum connected vertex cover; and MCD computes the minimum connected dominating set. MIS, MVC and MDS run in polynomial time if k = Θ(log | V |). MCV and MCD run in polynomial time if k = O((log | V |) α), where α < 1. If k = Θ((log | V |) 1+), for > 0, then MIS, MVC and MDS run in quasi-polynomial time. If k = Θ(log | V |), then MCV and MCD run in quasi-polynomial time.

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Compact Structure Patterns in Proteins

Cited by 23 publications

References 67 publications

Universal architectural concepts underlying protein folding patterns

Universal architectural concepts underlying protein folding patterns

Rules for connectivity of secondary structure elements in protein: Two–layer αβ sandwiches

Layered Graphs: Applications and Algorithms

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