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Fragon: rapid high-resolution structure determination from ideal protein fragments.

ABSTRACT: Correctly positioning ideal protein fragments by molecular replacement presents an attractive method for obtaining preliminary phases when no template structure for molecular replacement is available. This has been exploited in several existing pipelines. This paper presents a new pipeline, named Fragon, in which fragments (ideal ?-helices or ?-strands) are placed using Phaser and the phases calculated from these coordinates are then improved by the density-modification methods provided by ACORN. The reliable scoring algorithm provided by ACORN identifies success. In these cases, the resulting phases are usually of sufficient quality to enable automated model building of the entire structure. Fragon was evaluated against two test sets comprising mixed ?/? folds and all-? folds at resolutions between 1.0 and 1.7?Å. Success rates of 61% for the mixed ?/? test set and 30% for the all-? test set were achieved. In almost 70% of successful runs, fragment placement and density modification took less than 30?min on relatively modest four-core desktop computers. In all successful runs the best set of phases enabled automated model building with ARP/wARP to complete the structure.

SUBMITTER: Jenkins HT

PROVIDER: S-EPMC5947761 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Fragon: rapid high-resolution structure determination from ideal protein fragments.

Jenkins Huw T HT

Acta crystallographica. Section D, Structural biology 20180302 Pt 3

Correctly positioning ideal protein fragments by molecular replacement presents an attractive method for obtaining preliminary phases when no template structure for molecular replacement is available. This has been exploited in several existing pipelines. This paper presents a new pipeline, named Fragon, in which fragments (ideal α-helices or β-strands) are placed using Phaser and the phases calculated from these coordinates are then improved by the density-modification methods provided by ACORN ...[more]

PMID: 29533228

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Project description:Structural genomic projects envision almost routine protein structure determinations, which are currently imaginable only for small proteins with molecular weights below 25,000 Da. For larger proteins, structural insight can be obtained by breaking them into small segments of amino acid sequences that can fold into native structures, even when isolated from the rest of the protein. Such segments are autonomously folding units (AFU) and have sizes suitable for fast structural analyses. Here, we propose to expand an intuitive procedure often employed for identifying biologically important domains to an automatic method for detecting putative folded protein fragments. The procedure is based on the recognition that large proteins can be regarded as a combination of independent domains conserved among diverse organisms. We thus have developed a program that reorganizes the output of BLAST searches and detects regions with a large number of similar sequences. To automate the detection process, it is reduced to a simple geometrical problem of recognizing rectangular shaped elevations in a graph that plots the number of similar sequences at each residue of a query sequence. We used our program to quantitatively corroborate the premise that segments with conserved sequences correspond to domains that fold into native structures. We applied our program to a test data set composed of 99 amino acid sequences containing 150 segments with structures listed in the Protein Data Bank, and thus known to fold into native structures. Overall, the fragments identified by our program have an almost 50% probability of forming a native structure, and comparable results are observed with sequences containing domain linkers classified in SCOP. Furthermore, we verified that our program identifies AFU in libraries from various organisms, and we found a significant number of AFU candidates for structural analysis, covering an estimated 5 to 20% of the genomic databases. Altogether, these results argue that methods based on sequence similarity can be useful for dissecting large proteins into small autonomously folding domains, and such methods may provide an efficient support to structural genomics projects.

Dataset Information

Fragon: rapid high-resolution structure determination from ideal protein fragments.

Publications

Fragon: rapid high-resolution structure determination from ideal protein fragments.

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