Develop light-oxygen-voltage (LOV) sensing optogenetics tools through novel computational approaches with experimental validation

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SUMMARY Optogenetics is a powerful technique that integrates the use of light (optics) and genetic engineering. Light- oxygen-voltage (LOV) domains are light-responsive circadian clock regulation proteins and serve as a novel platform for the optogenetic tools development. Delineating allosteric mechanisms of various LOV domains is critical for such development. Molecular dynamics (MD) simulations are the main computational tools to reveal allosteric mechanisms as spatial-temporal information at the atomic level. However, there are two major road- blocks to the currently available MD simulation methods to elucidate LOV domain mechanisms: 1) limited time scale; 2) lack of kinetic information. Many enhanced sampling methods were developed to implicitly increase the accessible time scale of dynamics simulations, but are not suitable for simulations of protein allosteric mecha- nisms due to the requirement of constructing reaction coordinates a priori. To address this issue, we recently applied deep learning methods, named autoencoders, to develop novel dimensionality reduction models for al- losteric proteins. The main advantage of these models is the ability to accurately regenerate protein tertiary structure from the low dimensional space, a.k.a. latent space. There is also a lack of kinetics models for protein conformational changes underlying allostery. We developed a directed kinetic transition network (DKTN) model during the previous award period to model kinetics of protein conformational change based on MD simulations. Based on our recent work, in this application, we will continue to develop two new methods, the auto-encoded latent space (AELS) sampling methods and machine learning based directed kinetic transition network (ML- DKTN) methods, and apply these novel methods to elucidate the LOV domain mechanisms. With the experi- mental validation, we will further develop key mutants of the selected LOV domains as new optogenetic tools. We expect to develop a set of efficient computational tools to obtain allosteric function-related conformational ensembles and kinetics models. We will apply these tools to build conformational ensembles and kinetics models for key LOV domains proteins and their mutants to delineate their underlying allosteric mechanisms. These the- oretical models could provide direct guidance for the further development of optogenetic tools based on the selected LOV domains. The promising mutants identified in the proposed study will be subjected to experimental verification through biophysical characterization. The proposed research activities will also provide unique train- ing activities for motivated undergraduate and graduate students with various backgrounds to contribute to scientific research and improve their research, interpersonal, and communication skills.