<i>Ab initio</i> protein structure assembly using continuous structure fragments and optimized knowledge‐based force field

Xu, Dong; Zhang, Yang

doi:10.1002/prot.24065

Cited by 828 publications

(778 citation statements)

References 61 publications

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“…RaptorX 77 was used for prediction of secondary structure and disorder. QUARK 78 was used for ab initio modelling of the C-terminal domain, and the DALI server 79 was used for 3D homology searches of this region. Models were manually inspected and evaluated using the PyMOL program (http://pymol.org).…”

Section: Article Researchmentioning

confidence: 99%

The genome of Chenopodium quinoa

Jarvis

Lightfoot

et al. 2017

Nature

601

706

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Quinoa (Chenopodium quinoa Willd., 2n = 4x = 36) is a highly nutritious crop that is adapted to thrive in a wide range of agroecosystems. It was presumably first domesticated more than 7,000 years ago by pre-Columbian cultures and was known as the 'mother grain' of the Incan Empire 1 . Quinoa has adapted to the high plains of the Andean Altiplano (> 3,500 m above sea level), where it has developed tolerance to several abiotic stresses [2][3][4] . Quinoa has gained international attention because of the nutritional value of its seeds, which are gluten-free, have a low glycaemic index 5 , and contain an excellent balance of essential amino acids, fibre, lipids, carbohydrates, vitamins, and minerals 6 . Quinoa has the potential to provide a highly nutritious food source that can be grown on marginal lands not currently suitable for other major crops. This potential was recognized when the United Nations declared 2013 as the International Year of Quinoa, this being one of only three times a plant has received such a designation.Despite its agronomic potential, quinoa is still an underutilized crop 7 , with relatively few active breeding programs 8 . Breeding efforts to improve the crop for important agronomic traits are needed to expand quinoa production worldwide. To accelerate the improvement of quinoa, we present here the allotetraploid quinoa genome. We demonstrate the utility of the genome sequence by identifying a gene that probably regulates the presence of seed triterpenoid saponin content. Moreover, we sequenced the genomes of additional diploid and tetraploid Chenopodium species to characterize genetic diversity within the primary germplasm pool for quinoa and to understand sub-genome evolution in quinoa. Together, these resources provide the foundation for accelerating the genetic improvement of the crop, with the objective of enhancing global food security for a growing world population. Sequencing, assembly and annotationWe sequenced and assembled the genome of the coastal Chilean quinoa accession PI 614886 (BioSample accession code SAMN04338310) using single-molecule real-time (SMRT) sequencing technology from Pacific Biosciences (PacBio) and optical and chromosome-contact maps from BioNano Genomics 9 and Dovetail Genomics 10 . The assembly contains 3,486 scaffolds, with a scaffold N50 of 3.84 Mb and 90% of the assembled genome contained in 439 scaffolds (Table 1). The total assembly size of 1.39 gigabases (Gb) is similar to the reported size estimates of the quinoa genome (1.45-1.50 Gb (refs 11,12)). To combine scaffolds into pseudomolecules, an existing linkage map from quinoa 13 was integrated with two new linkage maps. The resulting map (Extended Data Fig. 1) of 6,403 unique markers spans a total length of 2,034 centimorgans (cM) and consists of 18 linkage groups (Supplementary Table 7), corresponding to the haploid chromosome number of quinoa. Pseudomolecules (hereafter referred to as chromosomes, which are numbered according to a previously published single-nucleotide polymorphism (SNP) linkage ...

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Section: Article Researchmentioning

confidence: 99%

The genome of Chenopodium quinoa

Jarvis

Lightfoot

et al. 2017

Nature

601

706

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“…We used the EcoGene 3.0 (41), which contained the QUARK prediction method (42), to predict the secondary structure of proteins without reported 3D structures.…”

Section: Methodsmentioning

confidence: 99%

Identification of 2-oxohistidine Interacting Proteins Using E. coli Proteome Chips

Lin

Tsai

Liu

et al. 2016

Molecular & Cellular Proteomics

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Cellular proteins are constantly damaged by reactive oxygen species generated by cellular respiration. Because of its metal-chelating property, the histidine residue is easily oxidized in the presence of Cu/Fe ions and H 2 O 2 via metal-catalyzed oxidation, usually converted to 2-oxohistidine. We hypothesized that cells may have evolved antioxidant defenses against the generation of 2-oxohistidine residues on proteins, and therefore there would be cellular proteins which specifically interact with this oxidized side chain. Using two chemically synthesized peptide probes containing 2-oxohistidine, high-throughput interactome screening was conducted using the E. coli K12 proteome microarray containing >4200 proteins. Ten interacting proteins were identified, and successfully validated using a third peptide probe, fluorescence polarization assays, as well as binding constant measurements. We discovered that 9 out of 10 identified proteins seemed to be involved in redox-related cellular functions. We also built the functional interaction network to reveal their interacting proteins. The network showed that our interacting proteins were enriched in oxido-reduction processes, ion binding, and carbon metabolism. A consensus motif was identified among these 10 bacterial interacting proteins based on bioinformatic analysis, which also appeared to be present on human S100A1 protein. Besides, we found that the consensus binding motif among our identified proteins, including bacteria and human, were located within ␣-helices and faced the outside of proteins. The combination of chemically engineered peptide probes with proteome microarrays proves to be an efficient discovery platform for protein interactomes of unusual post-translational modifications, and sensitive enough to detect even the insertion of a single oxygen atom in this case.

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“…As an alternative, "coarse grained" ab initio protein structure predictors, also called fragment-based, have been developed. Methods such as FRAGFOLD [12], Rosetta [13], I-TASSER [14], and QUARK [15] have demonstrated the strength of such approach. Regardless of the fragments' length used by those methods, their popularity is supported by three main points: (1) since the "smallest element" considered in computation is a set of amino acids instead of a single one, entropy in conformational search space is decreased in a dramatic way, (2) short sub-sequences converge towards a relatively limited number of sub-structures and (3) usage of Monte Carlo simulations instead of Molecular Dynamics ones has allowed making those methods much faster than pure ab initio ones.…”

Section: Introductionmentioning

confidence: 99%

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta

Abbass

Nebel²

2017

PPL

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Protein structure prediction is considered a main challenge in computational biology. The biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy, therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered as the most competitive method when it comes to targets with no homologues. Relying on fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling candidate fragments. Generally, the structure with the lowest energy score, also known as first model, is chosen to be the "predicted one".A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta's model "refinement" phase. Usage of the standard number of 3-mers -i.e. 200 -has been shown to degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore, a new prediction pipeline is proposed for Rosetta where the "refinement" phase is customised according to a target's structural class prediction. Over 8% improvement in terms of first model structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3-mers.

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Ab initio protein structure assembly using continuous structure fragments and optimized knowledge‐based force field

Cited by 828 publications

References 61 publications

The genome of Chenopodium quinoa

The genome of Chenopodium quinoa

Identification of 2-oxohistidine Interacting Proteins Using E. coli Proteome Chips

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta

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