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Computational Selectivity Analysis of Aptamer toward Oxidized Low-Density Lipoprotein

  • Suticha Chunta (Corresponding author)
  • , Soemwit Khongwichit
  • , Napat Prompat
  • , Aekkaraj Nualla-ong
  • , Maliwan Amatatongchai
  • , Peter A. Lieberzeit (Corresponding author)

Publications: Contribution to journal › Article › Peer Reviewed

Abstract

High target selectivity is a crucial factor in aptamer performance and practical applicability. The selectivity of four DNA aptamers (AP07, AP11, AP25, and AP29) toward oxidized low-density lipoprotein (oxLDL) was examined through computational prediction and experimental validation. Molecular dynamics simulations, combined with molecular mechanics generalized Born surface area (MM/GBSA) analysis, were employed to evaluate binding preferences against apolipoprotein (apo) B100 (apoB100) of native low-density lipoprotein (LDL), oxidized apoB100 of oxLDL, apoA1 of high-density lipoprotein (HDL), apoC1/apoE of very-low-density lipoprotein (VLDL), and albumin. Among the candidates, AP11 revealed the strongest predicted affinity and selectivity toward oxidized apoB100, exhibiting the lowest binding free energies of -344.52 +/- 18.37 kcal/mol. Experimental validation using an aptamer-based electrochemical assay confirmed the computational predictions, with AP11 displaying high selectivity for the entire oxLDL and cross-reactivity below 6% toward LDL, HDL, VLDL, and albumin. Structural analysis indicated that AP11 preserves key conformational motifs upon complex formation, contributing to the oxLDL-aptamer interaction. This integrated computational-experimental framework provides a robust strategy for evaluating and optimizing aptamer selectivity toward complex biomolecular targets.
Original languageEnglish
Pages (from-to)27603-27615
Number of pages13
JournalACS Omega
Volume11
Issue number18
Early online dateApr 2026
DOIs
Publication statusPublished - 12 May 2026

Funding

This research was supported by the National Science, Research and Innovation Fund (NSRF) and Prince of Songkla University (ref. no. MET6801275S). Soemwit Khongwichit was supported by the Faculty of Medical Technology Research Fund, Prince of Songkla University; the Graduate Fellowship (Ph.D.), Faculty of Science Research Fund, Prince of Songkla University (Contact no.1-2566-02-001); the Overseas Thesis Research Grant for Graduate Students, Graduate School, Prince of Songkla University (Contact no. OTR2567-002); and by the Ernst Mach Grant, weltweit, OeAD, Austria. Research reported in this publication was jointly supported by the ASEAN-European Academic University Network (ASEA-UNINET), the Austrian Federal Ministry of Education, Science and Research (BMBWF), and the OeAD - Austria’s Agency for Education and Internationalisation.

FundersFunder number
Prince of Songkla University1-2566-02-001, OTR2567-002

    Austrian Fields of Science 2012

    • 301302 Lipidomics research
    • 104027 Computational chemistry

    Keywords

    • HUMAN APOLIPOPROTEIN E3
    • RAMAN-SPECTROSCOPY
    • PROTEIN
    • SIMULATION

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