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Ab initio coordination chemistry for nickel chelation motifs.

ABSTRACT: Chelation therapy is one of the most appreciated methods in the treatment of metal induced disease predisposition. Coordination chemistry provides a way to understand metal association in biological structures. In this work we have implemented coordination chemistry to study nickel coordination due to its high impact in industrial usage and thereby health consequences. This paper reports the analysis of nickel coordination from a large dataset of nickel bound structures and sequences. Coordination patterns predicted from the structures are reported in terms of donors, chelate length, coordination number, chelate geometry, structural fold and architecture. The analysis revealed histidine as the most favored residue in nickel coordination. The most common chelates identified were histidine based namely HHH, HDH, HEH and HH spaced at specific intervals. Though a maximum coordination number of 8 was observed, the presence of a single protein donor was noted to be mandatory in nickel coordination. The coordination pattern did not reveal any specific fold, nevertheless we report preferable residue spacing for specific structural architecture. In contrast, the analysis of nickel binding proteins from bacterial and archeal species revealed no common coordination patterns. Nickel binding sequence motifs were noted to be organism specific and protein class specific. As a result we identified about 13 signatures derived from 13 classes of nickel binding proteins. The specifications on nickel coordination presented in this paper will prove beneficial for developing better chelation strategies.

SUBMITTER: Sudan RJ

PROVIDER: S-EPMC4435748 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Ab initio coordination chemistry for nickel chelation motifs.

Sudan R Jesu Jaya RJ Kumari J Lesitha Jeeva JL Sudandiradoss C C

PloS one 20150518 5

Chelation therapy is one of the most appreciated methods in the treatment of metal induced disease predisposition. Coordination chemistry provides a way to understand metal association in biological structures. In this work we have implemented coordination chemistry to study nickel coordination due to its high impact in industrial usage and thereby health consequences. This paper reports the analysis of nickel coordination from a large dataset of nickel bound structures and sequences. Coordinati ...[more]

PMID: 25985439

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Project description:BackgroundMicroRNAs (miRNAs) are short, non-coding RNA molecules that are directly involved in post-transcriptional regulation of gene expression. The mature miRNA sequence binds to more or less specific target sites on the mRNA. Both their small size and sequence specificity make the detection of completely new miRNAs a challenging task. This cannot be based on sequence information alone, but requires structure information about the miRNA precursor. Unlike comparative genomics approaches, ab initio approaches are able to discover species-specific miRNAs without known sequence homology.ResultsMiRPred is a novel method for ab initio prediction of miRNAs by genome scanning that only relies on (predicted) secondary structure to distinguish miRNA precursors from other similar-sized segments of the human genome. We apply a machine learning technique, called linear genetic programming, to develop special classifier programs which include multiple regular expressions (motifs) matched against the secondary structure sequence. Special attention is paid to scanning issues. The classifiers are trained on fixed-length sequences as these occur when shifting a window in regular steps over a genome region. Various statistical and empirical evidence is collected to validate the correctness of and increase confidence in the predicted structures. Among other things, we propose a new criterion to select miRNA candidates with a higher stability of folding that is based on the number of matching windows around their genome location. An ensemble of 16 motif-based classifiers achieves 99.9 percent specificity with sensitivity remaining on an acceptable high level when requiring all classifiers to agree on a positive decision. A low false positive rate is considered more important than a low false negative rate, when searching larger genome regions for unknown miRNAs. 117 new miRNAs have been predicted close to known miRNAs on human chromosome 19. All candidate structures match the free energy distribution of miRNA precursors which is significantly shifted towards lower free energies. We employed a human EST library and found that around 75 percent of the candidate sequences are likely to be transcribed, with around 35 percent located in introns.ConclusionOur motif finding method is at least competitive to state-of-the-art feature-based methods for ab initio miRNA discovery. In doing so, it requires less previous knowledge about miRNA precursor structures while programs and motifs allow a more straightforward interpretation and extraction of the acquired knowledge.

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Ab initio coordination chemistry for nickel chelation motifs.

Publications

Ab initio coordination chemistry for nickel chelation motifs.

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