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Antibody Aggregation Prediction

At present, protein aggregation still remains a main area of focus in the production of monoclonal antibodies. Increasing the intrinsic properties of antibodies can promote manufacturability, attrition rates, formulation, safety, titers, immunogenicity, and solubility. On account of the identification of aggregation-prone regions and their contribution to the thermodynamic stability of the protein, predicting and decreasing the aggregation propensity of monoclonal antibodies become available. With years of exploration in antibody engineering, Creative Biolabs has built a full-scale in silico technology platform. Based on our advanced platform, we offer high quality antibody aggregation prediction services for customers all over the world.

Aggregation-prone Regions

β-aggregation is the process of association of proteins, mainly via the formation of intermolecular beta-sheet structures through short aggregation-prone regions (APRs) of the polypeptide sequence. Although APRs are usually hydrophobic in nature, they need other key properties such as a high β-sheet propensity and a low net charge. Generally, strategies of aggregation prediction are geared toward the identification of APRs in the primary sequence. These prediction approaches built the theoretical aggregation potential of the protein in the unfolded situation, named the “intrinsic aggregation propensity”. For nucleate aggregation, an APR must be solvent exposed so as to generate stable interactions with other like sequences. Nevertheless, in most globular proteins, these APRs are buried inside the hydrophobic core of the native structure. In this way, they are prevented from triggering aggregation via the thermodynamic stability of the protein.

Antibody Aggregation PredictionFig 1. In silico analysis of aggregation propensity in antibody crystal structures. (van der Kant, 2017)


Based on previous studies, we assume that the distinction between a structural and a critical APR is mainly determined by the local thermodynamic stability of the region comprising the APR. A structural APR contributes to protein stability, therefore, it is only possible to trigger aggregation upon denaturation, whereas a critical APR may trigger aggregation under native states on account of local structural fluctuations. In order to measure thermodynamic stability, we utilize the empirical force field FoldX. Through combining the local contributions of all residues, FoldX is able to remove the free energy of folding of protein structure. Hence, it is well suited to determine local stability (called ΔGcontrib, in kcal/mol).


In order to evaluate the presence of APRs, the statistical thermodynamic algorithm TANGO is used. TANGO measure the intrinsic aggregation propensity of APRs as a Boltzmann distribution with competing secondary structural tendencies, for example, α-helical or β-hairpin structure. TANGO has a great advantage, which is it predicts APRs with well-defined sequence boundaries, that is, with a clear-cut separation between the APR and the surrounding residues. Moreover, TANGO enables high specificity and thus predicts few false-positive APRs, on account of our current purpose of identifying critical APRs.

With our comprehensive antibody aggregation prediction services, designing and engineering novel antibodies with desired therapeutic properties is available. We customize the service according to the specific requirements from the customers. We also provide other structure-based antibody reformatting services. Please contact us for more information and a detailed quote.


  1. van der Kant, (2017). “Prediction and reduction of the aggregation of monoclonal antibodies.” Journal of molecular biology, 429(8), 1244-1261.

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