This project aims to develop a tool that can considerably increase the precision of nucleic acid sequencing by enabling rational engineering of biological nanopores for sequencing applications. Although the methodology of nanopore sequencing has undergone major improvement with regard to transporting DNA and RNA molecules through the nanopore, sample preparation, base- calling algorithms, etc., relatively little has been published on improving the raw accuracy of nucleotide detection, which is the most commonly quoted deficiency of the nanopore sequencing method. This project will address this deficiency by developing a computational technology that will greatly simplify the design of custom nanopores for RNA and DNA sequencing, potentially leading to orders-of-magnitude improvement in row read accuracy. The key innovation of the project exploits recent methodological advances that have made plausible de novo prediction of nanopore current levels from simulations alone. To transform this methodological breakthrough into an accurate nanopore design tool, this project will examine and improve the simulation methodology guided by a set of experiments designed specifically to provide the information needed to improve the model. The practical utility of the method will be demonstrated by designing custom pores to detect biologically significant RNA modifications. The resulting computational method will be made available to the research community in the form of self-contained and well- documented software. This project will be realized by an interdisciplinary team that combines expertise in biological (UMass) nanopore experiment with theoretical and computation modeling (UIUC).The two PIs involved each have over 15 years of experience with research on nanopore technology, which includes synthesis and characterization of biological nanopores (Chen) and microscopic simulations of DNA and ion transport through biological nanopores (Aksimentiev).