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Record W6981693607

Exploring Ligand Structure and Thermodynamics of the Malachite Green RNA Aptamer

2012· dissertation· en· W6981693607 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2012
Typedissertation
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsDivalent metalLigand (biochemistry)MyoglobinContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

RNA aptamers are in vitro sequences of RNA that have a high affinity for their target ligand. They have applications in therapeutics, biosensors and molecular machines. While the practical applications of aptamers are increasing, it is important to study their structure and thermodynamics to improve the understanding of these molecular tools. The malachite green aptamer (MGA) provides a model system to study the interactions between aptamer and ligand that do not involve hydrogen bonding between ligand and receptor. While the original application of this aptamer was abandoned, study of the MGA binding pocket revealed an electronegative environment that was harnessed for catalysis. MGA binding also supported the notion that aptamers bind by adaptive binding. Adaptive binding is the ability of molecules to mold themselves around the structure of a ligand thereby incorporating it into their three-dimensional fold. \nTo further expand our understanding of MGA binding and to clarify conflicting reports of affinities, we conducted isothermal calorimetry binding studies. The results reveal that the entropy of complex formation plays a large role in determining binding affinity and ligand specificity. This data combined with previous structural studies show that metal ions are required to stabilize the complexes with non-native ligands, whereas, the complex with the original selection target is stable at low salt and in the absence of divalent metal ions. Next, competitive binding studies using isothermal titration calorimetry were conducted with the aim of understanding the adaptive nature of RNA. The results of these studies reveal that there are limits to the adaptability of the aptamer. Binding of one type of ligand reduces the affinity of the aptamer pocket to a differently shaped ligand, even if this second ligand has a significantly higher affinity. \nThe ability of MGA to change ligand preference based on buffer conditions, and the previously reported catalysis suggested that RNA may have a potential supporting multiple functions in the same molecule. To investigate this possibility we attempted to select an aptamer that supports both ligand binding and catalysis. By conducting both a DNA and RNA selection we hoped to add to the \niv \ncollection of DNA and RNA aptamers selected for the same target. There are currently too few of these to determine if any correlation can be made between DNA and RNA sequences that bind the same target. The target of the selection was fluorescein diacetate (FDA), which was chosen with the aim that it would allow the exploration of the inherent potential of the selected aptamer to cleave FDA to fluorescein. The RNA selection proved to be more successful and an attempt was made to characterize the binding of the aptamer to its target fluorescein diacetate. Unfortunately there were complications with the binding assays, but future work is proposed that should address the issues. \nIn order to expand the MGA catalytic repertoire attempts were made to synthesize new ligands that could exploit the catalytic potential of the MGA binding pocket. Unfortunately these attempts were unsuccessful, however further attempts are recommended. The MGA used in this study was transcribed in vitro using T7 RNA polymerase. This process is known to add extra nucleotides to the end of the transcription product. Attempts were made to eliminate the n+1 product by introducing a ribozyme or DNAzyme. These were met with difficulties resulting in low yield, however mass spectrometry revealed that n and n+1 MGA bind to ligand. This, along with secondary structure prediction suggests that MGA n+1 behaves the same as n. \nOverall, the results presented here provide insights into the capabilities of RNA aptamers with respect to ligand binding and catalysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.170
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueUWSpace (University of Waterloo)→Same topicAmerican and British Literature Analysis→French-language works237,207→