GGrantIndex
← Search

CAREER: Resolving the Influence of Biologically Relevant Microenvironments on Amyloid Aggregation

$630,029FY2022BIONSF

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

Amyloids are proteins that aggregate into highly ordered structures and exhibit signature aggregation pathways that drive these proteins to functional or cytotoxic activities. Some amyloids, like β-endorphin (βE), are signaling molecules and do not have any known cytotoxic activities. Others, like islet amyloid polypeptide (IAPP) and α-synuclein (αS) participate in both functional and cytotoxic cellular activities. Completing the demonstration of a spectrum of functional to cytotoxic states, amyloid-β (Aβ) is a known cytotoxic amyloid with no clear functional purpose. Taken together, amyloids constitute a very curious class of proteins that are evolutionarily and structurally connected. By studying amyloid aggregation events in membrane environments at the atomistic level, we can identify key molecular properties that drive the spectrum of functionality and cytotoxicity of these peptides. Molecular dynamics (MD) simulations offer a cost-effective and atomistic technique to probe these aggregation events in complex membrane environments that mimic cellular environments. Using the topic of protein-structure function relationship of amyloids, coupled with computational techniques, we will further create accessible, scalable, and sustainable undergraduate research opportunities and K-12 outreach programs that enhance biochemical and data science knowledge to students to prepare them for the workforce. Collectively, systematic investigation of membrane impact on amyloids using cutting-edge simulation techniques will provide essential knowledge on biophysical events that result in essential biological function that can be utilized for materials and drug discovery routes. Notoriously difficult to resolve and work with in vitro and in vivo, amyloid proteins remain a challenge to characterize given their transient, metastable structural folding pathways and a “superficially similar” degree of comparison in microscopy studies. A notable amyloid-world hypothesis has arisen in which the earliest biological information transfer was mediated by amyloid proteins, encrypting environmental information through structural changes to pass onto progeny molecular entities. Given the duality of multifaceted functionality and cytotoxicity of amyloids and their role in biological information transfer, it is crucial to understand the influence of microenvironments on the biophysics of amyloid aggregation. We hypothesize that lipid membrane composition and glycosaminoglycans presence will impact and remodel aggregation events of amyloids. Relatedly, amyloid structural morphologies and sequence-specific motifs will indicate position on the spectrum of functional to cytotoxic amyloids. Utilizing cutting-edge molecular dynamics (MD) simulations, that include classical, replica exchange, and polarizable MD, we will simulate aggregation events of oligomeric amyloids in various membrane environments. Conformational dynamics will be explored utilizing transition networks and Markov state models. This proposed work will push the capabilities of MD simulations to atomistically explore protein aggregation pathways and interconnect various amyloidogenic species (β-endorphin (βE, islet amyloid polypeptide (IAPP), α-synuclein (αS), and amyloid-β (Aβ)), to biological implications and phenomena. Utilization of data-rich, computational methods will further the integrated data and research literacy education components of this work given the ability to connect computational and algorithmic thinking with biology via local, regional, and global education programs that enhance the computational skillsets of K-12 students, undergraduates, and the community. 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.

View original record on NSF Award Search →