Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming procedures. In silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools, a rational design of aptamers is demonstrated. This "smart" SELEX method is experimentally proved by choosing the best five aptamer candidates obtained from the design process and applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of five different aptamers leads to a significant difference in the sensor's response. This can be explained by considering the aptamers' conformational change due to their interaction with the target molecule. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were used to confirm the high selectivity of the designed aptamers. The proposed in silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers and potentially be applied to any target molecule.

Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors / Douaki, Ali; Garoli, Denis; Inam, A K M Sarwar; Angeli, Martina Aurora Costa; Cantarella, Giuseppe; Rocchia, Walter; Wang, Jiahai; Petti, Luisa; Lugli, Paolo. - In: BIOSENSORS. - ISSN 2079-6374. - 12:8(2022), pp. 574-593. [10.3390/bios12080574]

Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors

Garoli, Denis;Cantarella, Giuseppe;
2022

Abstract

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming procedures. In silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools, a rational design of aptamers is demonstrated. This "smart" SELEX method is experimentally proved by choosing the best five aptamer candidates obtained from the design process and applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of five different aptamers leads to a significant difference in the sensor's response. This can be explained by considering the aptamers' conformational change due to their interaction with the target molecule. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were used to confirm the high selectivity of the designed aptamers. The proposed in silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers and potentially be applied to any target molecule.
2022
12
8
574
593
Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors / Douaki, Ali; Garoli, Denis; Inam, A K M Sarwar; Angeli, Martina Aurora Costa; Cantarella, Giuseppe; Rocchia, Walter; Wang, Jiahai; Petti, Luisa; Lugli, Paolo. - In: BIOSENSORS. - ISSN 2079-6374. - 12:8(2022), pp. 574-593. [10.3390/bios12080574]
Douaki, Ali; Garoli, Denis; Inam, A K M Sarwar; Angeli, Martina Aurora Costa; Cantarella, Giuseppe; Rocchia, Walter; Wang, Jiahai; Petti, Luisa; Lugli, Paolo
File in questo prodotto:
File Dimensione Formato  
2022_biosensors-1780592.pdf

Open access

Tipologia: Versione pubblicata dall'editore
Dimensione 1.27 MB
Formato Adobe PDF
1.27 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1315760
Citazioni
  • ???jsp.display-item.citation.pmc??? 7
  • Scopus 15
  • ???jsp.display-item.citation.isi??? 15
social impact