While structural symmetry is a prevailing feature of homo-oligomeric proteins, asymmetry provides unique mechanistic opportunities. We present the crystal structure of full-length TRAP1, the mitochondrial Hsp90 molecular chaperone, in a catalytically active closed state. The TRAP1 homodimer adopts a distinct, asymmetric conformation, where one protomer is reconfigured via a helix swap at the middle:C-terminal domain (MD:CTD) interface. This interface plays a critical role in client binding. Solution methods validate the asymmetry and show extension to Hsp90 homologs. Point mutations that disrupt unique contacts at each MD:CTD interface reduce catalytic activity and substrate binding and demonstrate that each protomer needs access to both conformations. Crystallographic data on a dimeric NTD:MD fragment suggests that asymmetry arises from strain induced by simultaneous NTD and CTD dimerization. The observed asymmetry provides the potential for an additional step in the ATPase cycle, allowing sequential ATP hydrolysis steps to drive both client remodeling and client release.

A strategy for acquiring structural information from sparsely isotopically labeled large proteins is illustrated with an application to the E. coli heat-shock protein, HtpG (high temperature protein G), a 145 kDa dimer. It uses ¹³C-alanine methyl labeling in a perdeuterated background to take advantage of the sensitivity and resolution of Methyl-TROSY spectra, as well as the backbone-centered structural information from ¹H-¹³C residual dipolar couplings (RDCs) of alanine methyl groups. In all, 40 of the 47 expected crosspeaks were resolved and 36 gave RDC data. Assignments of crosspeaks were partially achieved by transferring assignments from those made on individual domains using triple resonance methods. However, these were incomplete and in many cases the transfer was ambiguous. A genetic algorithm search for consistency between predictions based on domain structures and measurements for chemical shifts and RDCs allowed 60% of the 40 resolved crosspeaks to be assigned with confidence. Chemical shift changes of these crosspeaks on adding an ATP analog to the apo-protein are shown to be consistent with structural changes expected on comparing previous crystal structures for apo- and complex- structures. RDCs collected on the assigned alanine methyl peaks are used to generate a new solution model for the apo-protein structure.

NMR is a valuable experimental tool in the structural biologist's toolkit to elucidate the structures, functions, and motions of biomolecules. The progress of machine learning, particularly in structural biology, reveals the critical importance of large, diverse, and reliable datasets in developing new methods and understanding in structural biology and science more broadly. Biomolecular NMR research groups produce large amounts of data, and there is renewed interest in organizing these data to train new, sophisticated machine learning architectures and to improve biomolecular NMR analysis pipelines. The foundational data type in NMR is the free-induction decay (FID). There are opportunities to build sophisticated machine learning methods to tackle long-standing problems in NMR data processing, resonance assignment, dynamics analysis, and structure determination using NMR FIDs. Our goal in this study is to provide a lightweight, broadly available tool for archiving FID data as it is generated at the spectrometer, and grow a new resource of FID data and associated metadata. This study presents a relational schema for storing and organizing the metadata items that describe an NMR sample and FID data, which we call Spectral Database (SpecDB). SpecDB is implemented in SQLite and includes a Python software library providing a command-line application to create, organize, query, backup, share, and maintain the database. This set of software tools and database schema allow users to store, organize, share, and learn from NMR time domain data. SpecDB is freely available under an open source license at https://github.rpi.edu/RPIBioinformatics/SpecDB.