Molecular docking and dynamics simulations of aptamers for sandwich-type detection of Trichomonas vaginalis
摘要
Aptamer-based biosensing has gained recognition in the scientific community for its analytical, diagnostic, and economic advantages, underscoring the need to innovate beyond conventional infectious disease detection methods such as PCR and immunoassays. Trichomoniasis, one of the most prevalent nonviral sexually transmitted infections worldwide, remains a global health concern due to the absence of more specific and sensitive diagnostic tools. To address this issue, the study employed advanced computational approaches to evaluate the potential use of aptamers, previously obtained through SELEX, for detecting the AP65 protein expressed on Trichomonas vaginalis cells. Molecular docking and molecular dynamics simulations were conducted to predict and analyze the presence and behavior of biomolecular interactions relevant to the design. Three capture probes and three reporter probes were initially screened through rigid docking of binary complexes. These were then further assessed to identify aptamer pairs that could form the most stable ternary complex through flexible docking. Of the four ternary complexes formed, three were subjected to molecular dynamics simulations to investigate their structural integrity over time. Additionally, the selected probes were assessed for cross-reactivity with other AP65 variants. Results showed that the AP65–A1–A63 complex had the most stable conformations, suggesting that the pairing of A1 as capture probe and A63 as reporter probe was the best option in the design of sandwich-type assays for detecting AP65. It was also found that the selected probes had significant affinity to other AP65 variants, which may potentially contribute to more efficient aptamer–protein interactions. This study demonstrated that the capture and reporter probes synthesized are promising candidates for trichomoniasis detection. It also provided essential preliminary findings to support the effective optimization of in vitro sandwich-type models for future point-of-care device development.