Deciphering Complex Protein Energy Landscapes at Atomic Resolution with Novel AI-Enhanced and Advanced High-Pressure NMR Tools – EnergyLandByNMR

Proteins are inherently dynamic and adopt multiple conformations, often transiently, to perform their functions. Many current biophysical techniques overlook these elusive conformational states. However, despite their low population, these states play crucial roles in various biological processes. The "EnergyLandByNMR" project seeks to address this gap by moving beyond static 3D pictures to probe the atomic-level conformational dynamics of proteins. By marrying advanced NMR spectroscopy with AI-driven computational techniques, the proposed research aims to unravel the complex exchange processes characteristic of biomolecules. The core objectives of this project include: 1) designing enhanced CEST experiments optimized for detecting complex exchange dynamics; 2) employing machine learning methodologies to effectively analyze intricate chemical exchange NMR data; and 3) incorporating pressure-responsive kinetic models into the ChemEx software to leverage the potential of high-pressure NMR in probing protein free energy landscape. A specific application of this integrated methodology will be the study of the ATP-binding domain in the human HSP90 chaperone, a key therapeutic target. Given HSP90's role in tumor proliferation, a deeper understanding of its dynamic conformational landscape and the ways ligands can influence it could revolutionize therapeutic ligand design. In essence, "EnergyLandByNMR" strives to offer a comprehensive, dynamic perspective on biomolecular energy landscapes, setting the stage for sophisticated drug development and pushing the boundaries of structural biology.