Computationally guided formulation of biologics with site-identification by ligand competitive saturation (SILCS)-biologics

Protein-based therapeutics are becoming increasingly important in the pharmaceutical industry, with 16 out of the total 50 FDA approved therapeutics in 2021 being peptide or protein biologics. Biologics typically require high concentrations of the active protein, which can lead to the aggregation of the protein and high viscosity due to protein-protein interaction (PPI). Formulation of biologics through the inclusion of excipient molecules can improve the stability, bioavailability, and manufacturability of biologics. However, despite the importance of the formulation of biologics excipients are often selected based on trial and error. Here, we present an approach based on site identification by ligand competitive saturation (SILCS) technology, termed SILCS-Biologics, that can computationally guide excipient selection for biologics formulations and its application. Using precomputed 3D SILCS FragMaps, representing protein-functional group interaction patterns, the SILCS-Biologics approach maps potential excipient binding sites and PPI probability for the entire protein surface at atomistic level detail, providing a range of data to explore structure-based hypothesis for excipient impact on protein stability, aggregation, and viscosity. We applied the SILCS-Biologics approach to a diverse set of therapeutically relevant proteins for which experimental hydrogen-deuterium exchange-mass spectrometry (HDX-MS) as well as protein stability, aggregation, and viscosity data are currently being collected. Computational data collected from SILCS-Biologics, including the distribution and predicted affinity of excipients and the relation of the interactions to predicted PPI, are compared to HDX-MS, stability, aggregation, and viscosity experiments to determine the SILCS-Biologics metrics key to predicting excipient binding and impact on protein behavior. The SILCS-Biologics approach constitutes a promising structure-based method to elucidate the mechanisms of protein-excipient interactions and ultimately optimize biologics formulations to enhance protein stability and minimize aggregation and viscosity.

Conflict of Interest: ADM is Co-founder and CSO of SilcsBio LLC