Development and Application of Multi-scale Modeling to Biomolecular Association

University Of California-Riverside, Riverside CA

Investigators

Abstract

Accurate and timely molecular recognition is fundamental to all biological processes. In metabolic assembly (or disassembly) lines, sequential participants are thought to co-localize to maximize the rate at which a final product can emerge from a multi-step pathway. The investigator proposes to computationally simulate biosynthetic pathway networks in an effort to understand how, despite the complexity of the cellular milieu, binding partners are able to find each other, and biosynthetic pathway flux can be maximized. Through iterations of experiments with collaborators and computation, the investigator will model and predict the effects of co-localization of enzyme activities (the participants) on pathway flux. The overarching goal of the work is to develop software that allows one to accurately simulate how molecular partners find each other in the complex environment of the cell. The work has application to biosensor development, as sensors must also be able to detect their specific targets in a congested and chaotic environment. The project will also contribute to the training of graduate and undergraduate students. A summer workshop will be organized to train students from local community colleges, universities and high schools. Molecular association, in which two or more molecules must find one another, is the first critical step for all biochemical catalysis and (bio)sensing techniques. The project combines multi-level simulations, theoretical work and experimental collaboration to investigate molecular recognition and kinetic enhancements in multi-enzyme systems. To accelerate the overall product synthesis rate, several factors may be considered in designing a multi-enzyme scaffold, including geometry, local charge distribution, and network motions. The design of biosensors is informed by the binding mechanisms of a target and probe. The project explores novel ideas and incorporates results from experiments, atomistic molecular dynamics (MD), and Brownian dynamics (BD) simulations to investigate multi-enzyme nanostructures and large-scale membrane bound biosensors, either in vitro or a cell-like environment. The results offer insight into multi-enzyme and biosensor systems that will inform engineering and biosensor design. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.