AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

• Main Authors: Dario Ruiz-Ciancio (Author), Suresh Veeramani (Author), Rahul Singh (Author), Eric Embree (Author), Chris Ortman (Author), Kristina W. Thiel (Author), William H. Thiel (Author)
• Format: Book
• Published: Elsevier, 2024-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative systematic evolution of ligands by exponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Here we present AptamerRunner, an aptamer sequence and/or structure clustering algorithm that synergistically integrates computational analysis with visualization and expertise-directed decision making. The visual integration of networked aptamers with ranking data, such as fold enrichment or scoring algorithm results, represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner have broad-reaching implications for aptamer researchers across a wide range of disciplines.

Item Description

2162-2531
10.1016/j.omtn.2024.102358