Probing chemical space with evolution and with computers
See more of Dr. Ellington's research on his website: The Ellington Lab
Abstract: How to sense and identify compounds is one of the key issues in analytical chemistry. Biology typically senses and identifies compounds using a raft of receptors, with varying degrees of specificity. We have developed facile methods for the selection of transcription factors that can recognize a wide variety of compounds, and are working towards understanding how evolution can be used to tune the specificity for these compounds. In essence, we are learning how to navigate fitness landscapes for structural recognition. In parallel, we are using machine learning methods to understand the space of chemical compounds, and how these relate to compound function. In essence, we are learning how to navigate structural and linguistic landscapes for functional recognition. We hope to eventually bring these two lines of inquiry together, to develop receptors that parse functional recognition of compounds and provide deeper insights into how structure maps to function.
Bio: Dr. Andrew Ellington received his B.S. in Biochemistry from Michigan State University in 1981, and his Ph.D. in Biochemistry and Molecular Biology from Harvard in 1988. His post-doctoral work was with Dr. Jack Szostak at Massachusetts General Hospital, where he developed methods for the in vitro selection of functional nucleic acids and coined the term 'aptamer.' He originally received the Office of Naval Research Young Investigator, Cottrell, and Pew Scholar awards, and later was a Vannevar Bush Faculty Fellow of the DoD and a Howard Hughes Professor. Dr. Ellington's lab works centers on the development of nucleic acid circuitry for point-of-care diagnostics, on accelerating the evolution of proteins and cells through the introduction of novel chemistries, and on machine learning methods for engineering proteins and understanding evolutionary landscapes.
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