Facilitating crRNA Design by Integrating DNA Interaction Features of CRISPR‐Cas12a System

Abstract The CRISPR‐Cas12a system has gained significant attention as a rapid nucleic acid diagnostic tool due to its crRNA‐guided trans ‐cleavage activity. Accurately predicting the activity of different targets is significant to facilitate the crRNA availability but remains challenging. In this study, a novel approach is presented that combines molecular dynamics simulations and neural network modeling to predict the trans ‐cleavage activity. Unlike conventional tools that rely solely on the base sequences, our method integrated sequence features and molecular interaction features of DNA in the CRISPR‐Cas12a system, significantly improving prediction accuracy. Through feature importance analysis, key sequence features that influence Cas12a trans ‐cleavage activity are identified. Additionally, a crRNA‐DNA library with over 23 456 feature sequences from representative viruses and bacteria is established, and validated the high predictive accuracy of the model (Pearson's r = 0.9328) by screening crRNAs from reference targets. This study offers new insights into the molecular interactions of Cas12a/crRNA‐DNA and provides a reliable framework for optimizing crRNA design, facilitating the application of the CRISPR‐Cas12a in rapid nucleic acid diagnostics.