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Chemistry Seminar - Directing biocatalyst design through structure-function hypotheses from ancestral phylogenetic reconstruction, molecular modeling and machine learning
Sunday, February 9, 2025 3:30pm to 5pm
Event Details
Protein sequences contain rich information about protein evolution that may be revealed from the establishment of phylogenetic ancestral trees. However, simple comparisons of protein sequences are often insufficient to inform biocatalyst discovery and design, but can now be augmented through the establishment of structural modeling workflows that provide “structural annotation” and hypothesis generation to inform strategies for ancestral resurrection in the search for optimal biocatalytic enzymes. Focusing on design questions centered around a family of fungal flavin mono-oxygenases, I will present a novel application of large-scale structure prediction through a pipeline based on AlphaFold2 together with cofactor modeling, substrate docking and machine learning to identify key residues controlling site-specific and stereo-selective asymmetric dearomatization reactions. I will discuss the pipeline we established and illustrate how we are using the structurally annotated ancestral tree to explore and inform mutational studies and prioritization of ancestral sequence resurrection for purposes of establishing a broadly substrate scoped biocatalyst.
Location
SCI 1.220
Department
- Natural Sciences & Mathematics
Hashtag
Contact Information
- Filippo Romiti
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