Computational Modeling of Peptide – Aptamer Binding in Biosensor Applications

Rhinehardt, Kristen L.; Mohan, Ram; Srinivas, Mohan; Kelkar, Ajit D.

doi:10.7763/ijbbb.2013.v3.292

Cited by 1 publication

(2 citation statements)

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“…A preliminary study of molecular dynamics modeling was previously discussed for a similar system based on MUC1 peptide. 46 Modeling of the natural progression of peptide−aptamer binding in a solvent identifies key features such as orientation and location of the aptamer in the binding event, thus providing insights for biosensor development. A series of extensive molecular dynamics (MD) simulations of MUC1 and MUC1-G peptides and aptamer combinations in solvent were conducted.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Molecular dynamics is a computational methodology commonly used to study many biomolecules. ,− A detailed molecular dynamics modeling analysis of individual MUC1 peptide, MUC1-G peptide, and anti-MUC1 aptamer systems in solvent and their interactions are presented and discussed in the present paper. A preliminary study of molecular dynamics modeling was previously discussed for a similar system based on MUC1 peptide …”

Section: Introductionmentioning

confidence: 99%

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Molecular Dynamics Simulation Analysis of Anti-MUC1 Aptamer and Mucin 1 Peptide Binding

2015

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Aptasensors utilize aptamers as bioreceptors. Aptamers are highly efficient, have a high specificity and are reusable. Within the biosensor the aptamers are immobilized to maximize their access to target molecules. Knowledge of the orientation and location of the aptamer and peptide during binding could be gained through computational modeling. Experimentally, the aptamer (anti-MUC1 S2.2) has been identified as a bioreceptor for breast cancer biomarker mucin 1 (MUC1) protein. However, within this protein lie several peptide variants with the common sequence APDTRPAP that are targeted by the aptamer. Understanding orientation and location of the binding region for a peptide-aptamer complex is critical in their biosensor applicability. In this study, we investigate through computational modeling how this peptide sequence and its minor variants affect the peptide-aptamer complex binding. We use molecular dynamics simulations to study multiple peptide-aptamer systems consisting of MUC1 (APDTRPAP) and MUC1-G (APDTRPAPG) peptides with the anti-MUC1 aptamer under similar physiological conditions reported experimentally. Multiple simulations of the MUC1 peptide and aptamer reveal that the peptide interacts between 3' and 5' ends of the aptamer but does not fully bind. Multiple simulations of the MUC1-G peptide indicate consistent binding with the thymine loop of the aptamer, initiated by the arginine residue of the peptide. We find that the binding event induces structural changes in the aptamer by altering the number of hydrogen bonds within the aptamer and establishes a stable peptide-aptamer complex. In all MUC1-G cases the occurrence of binding was confirmed by systematically studying the distance distributions between peptide and aptamers. These results are found to corroborate well with experimental study reported in the literature that indicated a strong binding in the case of MUC1-G peptide and anti-MUC1 aptamer. Present MD simulations highlight the role of the arginine residue of MUC1-G peptide in initiating the binding. The addition of the glycine residue to the peptide, as in the case of MUC1-G, is shown to yield a stable binding. Our study clearly demonstrates the ability of MD simulations to obtain molecular insights for peptide-aptamer binding, and to provide details on the orientation and location of binding between the peptide-aptamer that can be instrumental in biosensor development.

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Section: ■ Introductionmentioning

confidence: 99%