Topology independent protein structural alignment

Dundas, Joe; Binkowski, T.A.; DasGupta, Bhaskar; Liang, Jie

doi:10.1186/1471-2105-8-388

Cited by 26 publications

(22 citation statements)

References 41 publications

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“…branch-and-bound, branch-and-cut, branch-and-price, cutting plane (Nemhauser and Wolsey, 1988)], metaheuristic techniques (Glover and Kochenberger, 2003; Vazirani, 2001), as well as approximation algorithms (Vazirani, 2001). MIPs have being successfully applied to a broad range of problems including bioinformatics (Floudas and Pardalos, 2000), protein design (Fung et al , 2005) and structural alignment (Dundas et al , 2007). …”

Section: Methodsmentioning

confidence: 99%

Optimization of minimum set of protein–DNA interactions: a quasi exact solution with minimum over-fitting

et al. 2009

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Motivation: A major limitation in modeling protein interactions is the difficulty of assessing the over-fitting of the training set. Recently, an experimentally based approach that integrates crystallographic information of C2H2 zinc finger–DNA complexes with binding data from 11 mutants, 7 from EGR finger I, was used to define an improved interaction code (no optimization). Here, we present a novel mixed integer programming (MIP)-based method that transforms this type of data into an optimized code, demonstrating both the advantages of the mathematical formulation to minimize over- and under-fitting and the robustness of the underlying physical parameters mapped by the code.Results: Based on the structural models of feasible interaction networks for 35 mutants of EGR–DNA complexes, the MIP method minimizes the cumulative binding energy over all complexes for a general set of fundamental protein–DNA interactions. To guard against over-fitting, we use the scalability of the method to probe against the elimination of related interactions. From an initial set of 12 parameters (six hydrogen bonds, five desolvation penalties and a water factor), we proceed to eliminate five of them with only a marginal reduction of the correlation coefficient to 0.9983. Further reduction of parameters negatively impacts the performance of the code (under-fitting). Besides accurately predicting the change in binding affinity of validation sets, the code identifies possible context-dependent effects in the definition of the interaction networks. Yet, the approach of constraining predictions to within a pre-selected set of interactions limits the impact of these potential errors to related low-affinity complexes.Contact: ccamacho@pitt.edu; droleg@pitt.eduSupplementary information: Supplementary data are available at Bioinformatics online.

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Section: Methodsmentioning

confidence: 99%

Optimization of minimum set of protein–DNA interactions: a quasi exact solution with minimum over-fitting

et al. 2009

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“…By assembling Fox1 in silico we have identified a novel MCO folding paradigm; our analyses confirm the presence of the first ferroxidase known in the Kingdom Plantae; and they establish the blueprint for function-based protein modeling that succeeds where a sequence alignment approach demonstrably fails to generate the structure of a functional protein. Our method is essentially topology-independent structural alignment [31] and is complementary to algorithms designed to identify circular permutations of domain shuffling in the evolution of multi-domain proteins [32, 33], a mechanism of MCO evolution that has been ignored in phylogenetic studies to date.…”

Section: Introductionmentioning

confidence: 99%

The Fox1 ferroxidase of Chlamydomonas reinhardtii: a new multicopper oxidase structural paradigm

Terzulli

Kosman

2008

J Biol Inorg Chem

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Multicopper oxidases (MCO) contain at least four copper atoms arrayed in three distinct ligand fields supported by two canonical structural features: 1) multiples of the cupredoxin fold; and 2) four unique sequence elements that include the 10 histidine and one cysteine ligands to the four copper atoms. Ferroxidases are a sub-family of MCO proteins that contain residues supporting a specific reactivity towards ferrous iron; these MCOs play a vital role in iron metabolism in bacteria, algae, fungi and mammals. In contrast to the fungal ferroxidases, e.g. Fet3p from Saccharomyces cerevisiae, the mammalian ceruloplasmin (Cp) is twice as large (six versus three cupredoxin domains) and contains three type 1, or "blue" copper sites. Chlamydomonas reinhardtii expresses a putative ferroxidase, Fox1, which has sequence similarity to human Cp (hCp). Eschewing the standard sequence-based modeling paradigm, a function-based model of the Fox1 protein has been constructed which replicates hCp's six Cu-site ligand arrays with an overall root mean square deviation of 1.4 Å. Analysis of this model has led also to assignment of motifs in Fox1 that are unique to ferroxidases, the strongest evidence to date that the well-characterized fungal high-affinity iron uptake system is essential to iron homeostasis in green algae. The model of Fox1 also establishes a sub-family of MCO proteins with a non-canonical Cu-ligand organization. These diverse structures suggest alternate mechanisms for intramolecular electron transfer and require a new trajectory for the evolution of the MCO superfamily.

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“…The above procedure is another version of the maximum weight independent set problem (Binkowski et al 2004;Dundas et al 2007). The set created by the first popped vertex is guaranteed to be within a factor of 1/2.89 from the optimal solution.…”

Section: Generate Candidate Secondary Structures With Pk2dmentioning

confidence: 99%

“…The constraints of the IP problem are formulated to encode the nonconflicting condition between the selected stems. We have adapted a method originally developed for protein structural alignment by Dundas et al (2007) to solve this IP problem. This approach is based on an approximation algorithm for scheduling split interval graphs (Bar-Yehuda et al 2002).…”

Section: Generate Candidate Secondary Structures With Pk2dmentioning

confidence: 99%

Prediction of geometrically feasible three-dimensional structures of pseudoknotted RNA through free energy estimation

Jian¹,

Dundas²,

Lin³

et al. 2009

RNA

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Accurate free energy estimation is essential for RNA structure prediction. The widely used Turner's energy model works well for nested structures. For pseudoknotted RNAs, however, there is no effective rule for estimation of loop entropy and free energy. In this work we present a new free energy estimation method, termed the pseudoknot predictor in three-dimensional space (pk3D), which goes beyond Turner's model. Our approach treats nested and pseudoknotted structures alike in one unifying physical framework, regardless of how complex the RNA structures are. We first test the ability of pk3D in selecting native structures from a large number of decoys for a set of 43 pseudoknotted RNA molecules, with lengths ranging from 23 to 113. We find that pk3D performs slightly better than the Dirks and Pierce extension of Turner's rule. We then test pk3D for blind secondary structure prediction, and find that pk3D gives the best sensitivity and comparable positive predictive value (related to specificity) in predicting pseudoknotted RNA secondary structures, when compared with other methods. A unique strength of pk3D is that it also generates spatial arrangement of structural elements of the RNA molecule. Comparison of three-dimensional structures predicted by pk3D with the native structure measured by nuclear magnetic resonance or X-ray experiments shows that the predicted spatial arrangement of stems and loops is often similar to that found in the native structure. These close-tonative structures can be used as starting points for further refinement to derive accurate three-dimensional structures of RNA molecules, including those with pseudoknots.

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Topology independent protein structural alignment

Cited by 26 publications

References 41 publications

Optimization of minimum set of protein–DNA interactions: a quasi exact solution with minimum over-fitting

Optimization of minimum set of protein–DNA interactions: a quasi exact solution with minimum over-fitting

The Fox1 ferroxidase of Chlamydomonas reinhardtii: a new multicopper oxidase structural paradigm

Prediction of geometrically feasible three-dimensional structures of pseudoknotted RNA through free energy estimation

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