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

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.