Computational Methods for Large Scale RNA Design
Optimization methods meet physics and biological discovery.
We start our RNA project journey, Thanks NSF!!!
NSF funded project: Collaborative Research: FET: Small: Hierarchical Computational Framework for large scale RNA Design Pathway Discovery through Data and Experiments.
RNA nanostructure design has received unprecedented attention due to the number of emerging applications in different scientific fields, such as diagnostics, therapeutics, synthetic biology, biological materials, and molecular programming. However, the design and synthesis of long RNA molecules with improved stability, programmable geometries, and controllable functions is an incredibly challenging task. The difficulties of large RNA design are due to their long sequences and complex interactions between bases. In addition, once a structure is designed, conducting experiments is time-consuming and expensive. It is invaluable to develop a platform with effective design algorithms and tools for RNA design with high efficiency and accuracy. This project will advance national health prosperity and welfare, providing the required knowledge for the design and synthesis of long RNAs with the desired functionalities and improved stabilities. These RNAs will have an important potential impact in applications such as drug delivery and cancer therapy. The team will develop new computational methods enabling support to the discovery of next-generation nanostructure in a more efficient and informed manner. This multidisciplinary project will tackle two main challenges for the development of the design of RNA structures. (i) Perform optimization without explicit knowledge of a reward function. (ii) Scale the methods in (i) to high-dimensional cases. A bio-inspired concept of tile is employed to create a computationally efficient algorithmic framework to generate and explore tiles, which will be evaluated using expert-driven rollout over chains of tiles. The produced algorithms will be subsequently validated using existing RNA databases. New RNA building blocks will be proposed and constructed through the algorithmic framework, to be validated as an assistant tool to the design of single-stranded RNA origami structures with increasing size and complexity that could potentially rival the natural RNA machineries or designer DNA nanostructures.
Our first paper is currently under review: https://www.biorxiv.org/content/10.1101/2021.01.18.427087v1.abstract
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