Integration of biophysics and deep learning to understand species-specificity of fertilization and the rapid evolution of protein disorder

Project Summary Proteins often fold into three-dimensional shapes and operate as cellular machines with well-defined reaction mechanics – hence the common biochemical expression “structure is function.” However, this rule only applies to the slowest evolving portions of the human genome. Proteins that evolve more rapidly are typically less ordered, both enabling their accelerated evolution and expanding the biochemical landscape on which natural selection may act. Currently there exist few tools and conceptual frameworks to understand the sequence-function relationship of quickly evolving dynamical proteins. Across the tree of life, reproductive proteins evolve at extraordinary rates – typically faster than immune genes – and the Wilburn lab studies the biophysics and molecular evolution of species-specific fertilization in animals. The continuous coevolution of interacting sperm and egg proteins has selected for biochemical properties such as intrinsic disorder, weak binding affinities, etc. that complicate their study. High-field NMR spectroscopy is unique among structural methods in its ability to study such heterogenous protein systems, and I have pioneered NMR studies of fertilization proteins in a classic model of fertilization research (marine abalone). Over the next 5 years, we will interrogate the sequence-to-function relationships of gamete recognition proteins important for species-specific fertilization by pairing high throughput mutagenesis screens with targeted biophysical analyses to better understand the complex interplay of molecular dynamics with protein evolvability and interaction kinetics. NMR methods will be expanded to the study of mammalian fertilization proteins. To facilitate our own work and empower other researchers, deep learning-based analytical tools in evolutionary genomics, mass spectrometry proteomics, and NMR dynamics will be developed. The proposed research will provide an evolutionary framework to better understand the breadth of protein biochemistry encoded by the human genome, and includes diverse training opportunities for undergraduate, graduate students, and postdocs