Project Grant R44GM134781

This $165,123 project grant from the National Science Foundation's Mathematical and Physical Sciences program will support the development of new computational methods and software tools for predicting polymorphic crystal structures of organic molecules and elucidating phase transition mechanisms. Mark Tuckerman of New York University and Jerome Delhommelle of the University of North Dakota will create a topological theory for crystal structure generation based solely on molecular order...

This Project Grant award from the National Science Foundation's (NSF) Division of Chemistry (CFDA 47.049 - Mathematical and Physical Sciences) provides $600,000 to Arizona State University (ASU) to support theoretical modeling and computational research on the linear and nonlinear mobility of proteins, electrical conductivity of protein complexes, and the role of water at biological interfaces. The key products and services to be delivered through this 3-year award (June 2025 - May 2028)...

This Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049), in the amount of $642,000, will fund research at Northwestern University to develop novel hybrid protein-DNA supramolecular structures. The key objectives are to: (1) design generalizable strategies for site-specific DNA functionalization to control proteins in 1D arrays; (2) create dynamic, DNA-driven 2D protein lattices; and (3) utilize DNA interactions to facilitate...

This five-year, $616,685 National Science Foundation project grant will fund research at Arizona State University to elucidate the synergistic effects of composition, porosity, and structural rigidity on the mechanics of metallic organic frameworks (MOFs). MOFs are porous hybrid materials consisting of metallic ions connected by organic linkers to form a vast reinforced network with potential for industrial CO2 capture, separation, and storage applications. The grant will support an integrated...

The National Science Foundation (NSF) awarded a $595,476 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to The Johns Hopkins University. The grant will support a 3-year research project to study and develop a new class of immobilization substrates, namely mesoporous protein crystals, for critical element separation. The project aims to obtain a comprehensive understanding of protein crystals as substrates for immobilizing metal-binding proteins (MBPs) to...

This $221,000 National Science Foundation project grant funds research at the University of Texas at Dallas to develop a control theoretic framework for modeling protein folding and unfolding pathways. The goal is to enable accurate in silico prediction of protein conformational dynamics with applications in computer-aided drug design, nano-machine control, and treatment of protein misfolding diseases. The researchers will apply optimization-based nonlinear control methods to guide protein...

This Project Grant awarded by the National Science Foundation's (NSF) Division of Chemistry under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) provides $378,025 to support the development of a new polarizable implicit solvent model for efficient and accurate modeling of RNA structure and function. The principal investigators, Xuhui Huang of the University of Wisconsin, Madison and Pengyu Ren of the University of Texas, Austin, will derive a new form of the...

This Project Grant award of $175,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a modular framework for modeling the binding of peptides and proteins to cell membranes. The key products to be delivered include: A software "mover" implemented in the Rosetta C++ codebase to predict the placement of proteins and peptides in cell membranes, an application of this mover compatible...

This three-year, $338,355 Project Grant from the National Science Foundation's Division of Chemistry and Mathematical and Physical Sciences program will support the development of new machine learning methods to design DNA and RNA aptamers for molecular targets. Principal Investigator Petr Sulc of Arizona State University will use restricted Boltzmann machine architectures to analyze sequences from selection experiments and naturally occurring non-coding RNAs to extract structural and sequence...

This National Science Foundation Project Grant of $536,946 will support research at the University of California, San Diego from September 2022 through August 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The award will fund the development of rigorous scientific theories and powerful computational tools to model biomolecular interactions. Researchers will design advanced numerical methods to simulate drug and protein binding/unbinding kinetics, incorporating molecular...