Abstract

Interest in the design and manufacture of RNA and DNA aptamers as apta-biosensors for the early diagnosis of blood infections and other inflammatory conditions has increased considerably in recent years. The practical utility of these aptamers depends on the detailed knowledge about the putative interactions with their target proteins. Therefore, understanding the aptamer-protein interactions at the atomic scale can offer significant insights into the optimal apta-biosensor design. In this study, we consider one RNA and one DNA aptamer that were previously used as apta-biosensors for detecting the infection biomarker protein TNF-α, as an example of a novel computational workflow for selecting the aptamer candidate with the highest binding strength to a target. We combine information from the binding free energy calculations, molecular docking, and molecular dynamics simulations to investigate the interactions of both aptamers with TNF-α. The results reveal that the RNA aptamer has a more stable structure relative to the DNA aptamer. Interaction of aptamers with TNF-α does not have any negative effect on its structure. The results of molecular docking and molecular dynamics simulations suggest that the RNA aptamer has a stronger interaction with the protein. Also, these findings illustrate that basic residues of TNF-α establish more atomic contacts with the aptamers compared to acidic or pH-neutral ones. Furthermore, binding energy calculations show that the interaction of the RNA aptamer with TNF-α is thermodynamically more favorable. In total, the findings of this study indicate that the RNA aptamer is a more suitable candidate for using as an apta-biosensor of TNF-α and, therefore, of greater potential use for the diagnosis of blood infections. Also, this study provides more information about aptamer-protein interactions and increases our understanding of this phenomenon.

Highlights

  • Severe blood infections leading to sepsis are one of the major causes of death, especially among hospitalized patients [1, 2]

  • In order to investigate the stability of conformations arrived at by our molecular dynamics (MD) simulations, the Root-Mean-Square Deviation (RMSD) value was computed for C-α in Tumor necrosis factor-α (TNF-α) and the backbone atoms of aptamers

  • We investigated the interactions of RNA and DNA aptamers with TNF-α at the atomic scale by binding free energy calculations, molecular docking, and MD simulations

Read more

Summary

Introduction

Severe blood infections leading to sepsis are one of the major causes of death, especially among hospitalized patients [1, 2]. Patients suffering from blood infections are characterized by complex pathophysiology and heterogeneous phenotypes with respect to response to treatment, symptoms, and outcomes. Blood infections are clinically difficult to diagnose due to the multiple factors contributing to their emergence [3], and definitive diagnosis techniques, risk determination tools, treatment selections, and evaluation methods, or outcome prediction procedures are to be found for these infections [4]. Ideal biomarkers are characterized by fast kinetics, high affinity and BioMed Research International specificity, detectability by automated technologies, and inexpensive bedside testing [4]. Many protein biomarkers have been identified that can be used to detect blood infections, such as C-reactive protein (CRP) [5], Interleukin 6 (IL-6) [6], Procalcitonin (PCT) [7], Interleukin 10 (IL-10) [8], Interferon-gamma (IFN-γ) [8], and tumor necrosis factoralpha (TNF-α) [9,10,11]

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call