Analyzing Secondary Structure Patterns in DNA Aptamers Identified via CompELS.
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ABSTRACT:
SUBMITTER: Sullivan R
PROVIDER: S-EPMC6515186 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Aptamers have a spectrum of applications in biotechnology and drug design, because of the relative simplicity of experimental protocols and advantages of stability and specificity associated with their structural properties. However, to understand the structure-function relationships of aptamers, robust structure modeling tools are necessary. Several such tools have been developed and extensively tested, although most of them target various forms of biological RNA. In this study, we tested the performance of three tools in application to DNA aptamers, since DNA aptamers are the focus of many studies, particularly in drug discovery. We demonstrated that in most cases, the secondary structure of DNA can be reconstructed with acceptable accuracy by at least one of the three tools tested (Mfold, RNAfold, and CentroidFold), although the G-quadruplex motif found in many of the DNA aptamer structures complicates the prediction, as well as the pseudoknot interaction. This problem should be addressed more carefully to improve prediction accuracy.
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Project description:DNA aptamers are synthetic, single-stranded DNA oligonucleotides selected by SELEX methods for their binding with specific ligands. Here we present ethidium binding results for three related DNA aptamers (PDB code: 1OLD, 1DB6, and 2ARG)that bind L-argininamide (L-Arm). The ligand bound form of each aptamer's structure has been reported and each are found to be composed primarily of two domains consisting of a stem helical region and a loop domain that forms a binding pocket for the cognate ligand. Previous thermodynamic experiments demonstrated that the DNA aptamer 1OLD undergoes a large conformational ordering upon binding to L-Arm. Here we extend those linkage binding studies by examining the binding of the heterocyclic intercalator ethidium to each of the three aptamers by fluorescence and absorption spectrophotometric titrations. Our results reveal that ethidium binds to each aptamer with DeltaG degree's in the range of -8.7 to -9.4 kcal/mol. The stoichiometry of binding is 2:1 for each aptamer and is quantitatively diminished in the presence of L-Arm as is the overall fluorescence intensity of ethidium. Together, these results demonstrate that a portion of the bound ethidium is excluded from the aptamer in the presence of a saturating amount of L-Arm. These results demonstrate the utility of ethidium and related compounds for the probing of non-conventional DNA structures and reveal an interesting fundamental thermodynamic linkage in DNA aptamers. Results are discussed in the context of the thermodynamic stability and structure of each of the aptamers examined.
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Project description:Aptamers are single-stranded nucleic acids that fold into defined tertiary structures to bind target molecules with high specificities and affinities. DNA aptamers have garnered much interest as recognition elements for biodetection and diagnostic applications due to their small size, ease of discovery and synthesis, and chemical and thermal stability. Here we describe the design and application of a short DNA molecule capable of both protein target binding and amplifiable bioreadout processes. Because both recognition and readout capabilities are incorporated into a single DNA molecule, tedious conjugation procedures required for protein-DNA hybrids can be omitted. The DNA aptamer is designed to be amplified directly by either polymerase chain reaction (PCR) or rolling circle amplification (RCA) processes, taking advantage of real-time amplification monitoring techniques for target detection. A combination of both RCA and PCR provides a wide protein target dynamic range (1 microM to 10 pM).
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Project description:BackgroundDNA repair is the general term for the collection of critical mechanisms which repair many forms of DNA damage such as methylation or ionizing radiation. DNA repair has mainly been studied in experimental and clinical situations, and relatively few information-based approaches to new extracting DNA repair knowledge exist. As a first step, automatic detection of DNA repair proteins in genomes via informatics techniques is desirable; however, there are many forms of DNA repair and it is not a straightforward process to identify and classify repair proteins with a single optimal method. We perform a study of the ability of homology and machine learning-based methods to identify and classify DNA repair proteins, as well as scan vertebrate genomes for the presence of novel repair proteins. Combinations of primary sequence polypeptide frequency, secondary structure, and homology information are used as feature information for input to a Support Vector Machine (SVM).ResultsWe identify that SVM techniques are capable of identifying portions of DNA repair protein datasets without admitting false positives; at low levels of false positive tolerance, homology can also identify and classify proteins with good performance. Secondary structure information provides improved performance compared to using primary structure alone. Furthermore, we observe that machine learning methods incorporating homology information perform best when data is filtered by some clustering technique. Analysis by applying these methodologies to the scanning of multiple vertebrate genomes confirms a positive correlation between the size of a genome and the number of DNA repair protein transcripts it is likely to contain, and simultaneously suggests that all organisms have a non-zero minimum number of repair genes. In addition, the scan result clusters several organisms' repair abilities in an evolutionarily consistent fashion. Analysis also identifies several functionally unconfirmed proteins that are highly likely to be involved in the repair process. A new web service, INTREPED, has been made available for the immediate search and annotation of DNA repair proteins in newly sequenced genomes.ConclusionDespite complexity due to a multitude of repair pathways, combinations of sequence, structure, and homology with Support Vector Machines offer good methods in addition to existing homology searches for DNA repair protein identification and functional annotation. Most importantly, this study has uncovered relationships between the size of a genome and a genome's available repair repertoire, and offers a number of new predictions as well as a prediction service, both which reduce the search time and cost for novel repair genes and proteins.
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Project description:Schistosomiasis is a major parasitic disease caused by blood flukes of the genus Schistosoma. Several million people all over the world are estimated to suffer from severe morbidity as a consequence of schistosomiasis. The worm's eggs, which cause the symptoms of schistosomiasis, are generally used to diagnose the disease. In this study, we employed egg-based systematic evolution of ligands by exponential enrichment (egg-SELEX) and identified a panel of ssDNA aptamers specifically binding to eggs derived from S. japonicum. Among these, two aptamers LC6 and LC15 exhibited strong binding to and specific recognition of S. japonicum eggs, but not eggs from Fasciolopsis buski, Enterobius, Ascaris or Clonorchis sinensis. Furthermore, tissue imaging results revealed that LC15 could recognize S. japonicum eggs laid in liver tissues with a detection ratio of 80.5%. Collectively, therefore, we obtained useful aptamers specifically recognizing S. japonicum eggs, which will facilitate the development of an effective tool for both schistosomiasis diagnosis and drug delivery.
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