Systematic Selection of High‐Affinity ssDNA Sequences to Carbon Nanotubes

Author:

Lee Dakyeon12ORCID,Lee Jaekang1,Kim Woojin3,Suh Yeongjoo1,Park Jiwoo1,Kim Sungjee2,Kim YongJoo4,Kwon Sunyoung15,Jeong Sanghwa1ORCID

Affiliation:

1. School of Biomedical Convergence Engineering Pusan National University Yangsan 50612 Republic of Korea

2. Department of Chemistry Pohang University of Science and Technology Pohang 37673 Republic of Korea

3. Department of Materials Science and Engineering Kookmin University Seoul 02707 Republic of Korea

4. Department of Materials Science and Engineering Korea University Seoul 02841 Republic of Korea

5. Center for Artificial Intelligence Research Pusan National University Busan 46241 Republic of Korea

Abstract

AbstractSingle‐walled carbon nanotubes (SWCNTs) have gained significant interest for their potential in biomedicine and nanoelectronics. The functionalization of SWCNTs with single‐stranded DNA (ssDNA) enables the precise control of SWCNT alignment and the development of optical and electronic biosensors. This study addresses the current gaps in the field by employing high‐throughput systematic selection, enriching high‐affinity ssDNA sequences from a vast random library. Specific base compositions and patterns are identified that govern the binding affinity between ssDNA and SWCNTs. Molecular dynamics simulations validate the stability of ssDNA conformations on SWCNTs and reveal the pivotal role of hydrogen bonds in this interaction. Additionally, it is demonstrated that machine learning could accurately distinguish high‐affinity ssDNA sequences, providing an accessible model on a dedicated webpage (http://service.k‐medai.com/ssdna4cnt). These findings open new avenues for high‐affinity ssDNA‐SWCNT constructs for stable and sensitive molecular detection across diverse scientific disciplines.

Funder

Korea Institute for Advancement of Technology

Pusan National University

National Research Foundation of Korea

Publisher

Wiley

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