Advances in Protein-RNA aptamer recognition and modeling: Current trends and future perspectives

Abstract

RNA aptamers possess a remarkable ability to selectively target a diverse spectrum of biomolecules with exceptional affinity and specificity. Their distinctive physical and chemical attributes have driven extensive research into their therapeutic, diagnostic, and analytical applications. However, experimental approaches alone are insufficient to meet the growing demand. As a result, accurate and efficient computational methods are playing an increasingly vital role in RNA aptamer sequence design and structural modeling. Recent breakthroughs in biomolecular structure prediction, particularly through deep learning, have further spurred the development of innovative algorithms. In this review, we summarize current computational models for RNA aptamer structure prediction and design, highlighting recent advances in the field.