Aptamers have a broad range of potential applications as probes in electrochemical sensors for the detection of small molecule toxins, explosives, and bio-toxins. The bottle neck is the identification of a specific aptamer against a desired target. This is a time consuming and costly process In addition, aptamers may require some elaboration for use in devices, potentially rending them unsuitable for molecular binding.
Researchers at West Virginia University (Peter M. Gannett, James P. Lewis, and Timothy Menzies) are using computational methods to reduce synthesis time by pruning candidate compounds prior to synthesis. Their goal is to develop advanced computational approaches that identify aptamers for specific molecular targets to accelerate the process of aptamer discovery and facilitate aptamer modification for practical applications.
Their approach combines knowledge of the two-dimensional structure and thermodynamic stability based on RNA sequence, calculation of the corresponding three-dimensional structures to prepare a library of RNAs, and docking of the library of RNAs with the desired small molecule. To reduce search time, they are developing a workbench of tools which include data mining tools as well as active learning tools to monitor the data mining to infer which compounds should be synthesized and characterized and which compounds to avoid, thus reducing the exploration time required to explore new aptamer candidates.
James P. Lewis1, Peter M. Gannett2, and Timothy Menzies3 1Department of Physics, West Virginia University, Morgantown, WV 26506-6315 2Robert C. Byrd Health Sciences Center, School of Pharmacy, Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506-9530 3Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506-6070
Dr. Lewis‘ research group uses computational materials science methodologies they developed to understand and develop nanomaterials.