Abstract
Biotherapeutics are an important class of molecules for the treatment of a wide range of diseases. They include low molecular weight peptides, highly engineered protein scaffolds and monoclonal antibodies. During their discovery and development, assessments of the biophysical attributes is critical to understanding the solution behavior of therapeutic proteins and for de-risking liabilities. Thus, methods that can quantify, characterize, and provide a basis to inform risks and drive the selection of more optimal antibody and alternative scaffolds are needed. Nuclear Magnetic Resonance (NMR) spectroscopy is a technique that provides a means to probe antibody and antibody-like molecules in solution, at atomic resolution, under any formulated conditions. Here, all samples were profiled at natural abundance requiring no isotope enrichment. We present a numerical approach that quantitates two-dimensional methyl spectra. The approach was tested with a reference dataset that contained different types of antibody and antibody-like molecules. This dataset was processed through a procedure we call a Random Sampling of NMR Peaks for Covariance Analysis. This analysis revealed that the first two components were well correlated with the hydrodynamic radius of the molecules included in the reference set. Higher-order principal components were also linked to dynamic features between different tethered antibody-like molecules and contributed to decisions around candidate selection. The reference set provides a basis to characterize molecules with unknown solution behavior and is sensitive to the behavior of a molecule formulated under different conditions. The approach is independent of protein design, scaffold, formulation and provides a facile method to quantify solution behavior.