Ribonucleic acid (RNA) molecules are not passive information carriers but molecules with versatile chemical and physical properties that can be exploited for therapeutic, synthetic biology, materials, bio-sensing, and engineering applications. Underlying all these applications are the dynamics which encompass a large number of modes, span vast spatiotemporal scales, and are connected to the intrinsic structural features (e.g. base-pairing) and some extrinsic factors (e.g. ligand binding). While equilibrium fluctuations in biomolecules such as RNA are inherent, it is the large-scale conformational transitions that play a dominant role in interfacial processes such as biomolecular recognition. Such dynamic properties are encoded in the physical free energy landscapes of biomolecules, the robust sampling of which can provide key thermodynamic and kinetic information on functional conformational ensembles of RNA molecules. The PI plans to look at conformational dynamics and interfacial interactions in small RNA molecules to enable their use for the above mentioned applications.
The research proposed is broadly concerned with two questions: (1) What physical variables are responsible for local and global conformational transitions in RNA molecules? and (2) How do these conformational transitions facilitate interfacial interactions of RNA with a diverse group of ligands (small molecules, short peptides, and globular proteins)? To gain a holistic view of the dynamics and interactions, the modeling and simulation effort will be integrated with spectroscopic (nucleic magnetic resonance) and imaging (electron cryo-microscopy) data. Understanding the details of how biomolecules undergo large-scale structural changes to elicit function is an unsolved problem. It is known that biomolecules are flexible and understanding their dynamics may provide insights into their function. Though, it is challenging to characterize such dynamic motions because no single computational or experimental technique can resolve motions at all spatiotemporal scales. The proposed computational approaches use physical free-energy landscapes in a reduced set of coordinates (while maintaining the all atom representation) as opposed to all degrees-of-freedom. The combination of computational and experimental techniques could establish new approaches to study these dynamics at a wide spectrum of time and length scales.
The educational plan will bring molecular theories, numerical algorithms, and visualization tools to a broad spectrum of STEM students and educators. It could impact and meet the Next Generation Science Standards and broaden participation in engineering and biophysics, through a broader educational initiative devoted to impart "visuospatial" thinking as a key skill via workshops on a freely-available software tool that will be further developed and disseminated via training of a wide spectrum of STEM population (students, teachers, and faculty). The students will travel to regional and national conferences, and will be exposed to international mentoring and multicultural experiences through partnerships with flagship engineering schools in India.
