Treffer: A large multiscale detailed modelling of aptamers as anticancer therapeutics

Cancer remains a leading cause of death worldwide, characterized by uncontrolled cell growth and spread. The challenge of effectively treating cancer has spurred interest in novel therapeutic strategies that target specific biological or biochemical mechanisms involved in cancer progression. Although many enzymes have been labelled as inducers of cancer development, microRNAs (miRNAs) are also emerging as significant contributors to cancer progression. This is because miRNAs play a crucial role in regulating gene expression, while cancer develops and grows due to genetic mutations, variations, and alterations. Among these miRNAs, miRNA-10b is notable for its involvement in promoting cancer cell proliferation, migration, and metastasis across various cancers, including breast cancer, glioblastoma, and esophageal squamous cell carcinoma. For this reason, we propose inhibiting miRNA-10b using RNA aptamers as a novel and promising approach for developing new anti-cancer therapeutics. RNA aptamers are short, non-coded, synthetic, and single-stranded nucleic acid molecules capable of binding to a wide range of targets, including metal ions, chemical compounds, proteins, cells, and microorganisms. They are used for a range of applications due to their well-known specificity and selectivity, starting from drug delivery to diagnostics. In this project we aimed to design and discover novel RNA aptamers that can effectively inhibit miRNA-10b using advanced computational methods. However, major challenges were encountered due to the lack of databases or tools available to design and predict secondary and tertiary structures of RNA aptamers at a large scale. Furthermore, no tools were available to perform high throughput virtual screening of these aptamers against macromolecular targets at a large scale. Prompted by that, we developed the T_SELEX program, which encompasses the various algorithms and tools dedicated to designing RNA aptamer sequences, predicting their secondary and tertiary structures, and, lastly, virtually ...