We showed that the SAP can be calculated from alternatives such as Fab, Fc fragment simulations, implicit solvent models or from X-ray structures directly, albeit with some loss of accuracy

We showed that the SAP can be calculated from alternatives such as Fab, Fc fragment simulations, implicit solvent models or from X-ray structures directly, albeit with some loss of accuracy.18We also used SAP to determine aggregation-prone motifs in human IgG constant regions.19The SAP predictions of aggregation-prone regions were validated by substituting the high-SAP sites with charged amino acids through genetic engineering. for function, and many disease-related cellular processes are associated with protein destabilization. For example, a single amino acid substitution in hemoglobin leads to protein aggregation, and to sickle cell anemia.1Proteins have also become increasingly ACY-738 important as therapeutics2and of those, monoclonal antibodies currently represent the fastest growing class of therapeutics. 3The recent significant increase in the number of protein-based pharmaceuticals has created a new challenge. Many therapeutic proteins are manufactured and stored as liquid solutions at very high concentrations of the product. As the percent of aggregation increases, the efficacy of the product decreases, and undesired side effects such as immunological response upon administration may occur.4,5Thus, assuring stability of protein pharmaceuticals for the shelf-life of the product is imperative. There are two main approaches to stabilize, and hence extend the shelf life and overall efficacy, of protein drugs. One is to optimize the drug formulation, for example by ACY-738 adding stabilizing excipients.68A second approach is to alter the protein sequence itself, for example by substituting non-polar or polar amino acids with charged amino acids on the protein surface.9,10Although both approaches have been successfully used, many methods for stabilization require time- and resource-consuming trial-and-error experiments. At the same time, detailed predictive algorithms of aggregation are not available for large proteins such as antibodies. Existing computational methods analyze small proteins or search for specific structural motifs such as hydrophobicity or -sheet propensity. 1114These studies lack a detailed account of dynamically exposed and spatially close patches that can contribute to aggregation. Thus, we developed a microscopic tool to find patches responsible for aggregation. We find that many properties that ACY-738 are not taken into account in existing methods, such as protein dynamic fluctuations and spatial clustering of amino acids distant in the primary protein sequence, are important to obtain an accurate tool. Such a screening tool will be of great value for the developability assessment and stabilization of candidate protein drugs from the discovery phase. Our recent article, Design of Therapeutic Proteins with Enhanced Stability, describes a new, rational and simulation-based technology for the identification of aggregation hot-spots in proteins.15,16We call this technology Spatial Aggregation Propensity ATP7B (SAP). Each amino acid of the protein sequence is assigned a SAP value based on the amino acid hydrophobicity, the extent of surface exposure, the sum of hydrophobic contributions of other amino acids within a pre-assigned radius, and the sum of contributions from the dynamics of the computational simulations: Here, SAA is the solvent accessible area of side chain atoms contained within radius R from the central atom. SAA is computed at each simulation snapshot. SAA of side chain of ACY-738 fully exposed residue (say for amino acid X) is obtained by calculating the SAA of side chains of the middle residue in the fully extended conformation of tripeptide Ala-X-Ala. Residue Hydrophobicity is obtained from the hydrophobicity scale of Black and Mould. ACY-738 17The scale is normalized such that Glycine has a hydrophobicity of zero. Protein regions within radius R with high SAP values (0.0 < SAP < 0.5) usually correspond to hydrophobic amino acids of high exposure that spatially form a hydrophobic patch. Regions with low SAP values (0.5 < SAP < 0.0) usually correspond to hydrophilic amino acids surrounded by other polar residues. Although a certain SAP value accounts for a spatial region of radius R, this value is assigned to the central residue for convenience..