Summary:
Monoclonal antibodies are used in treatment schemes for autoimmune,
cardiovascular and infectious diseases, kidney transplantation, and cancer. A
major drawback in the exploitation of antibodies is their tendency to form
aggregates. In this study, we investigated the susceptibility of a set of
monoclonal antibodies to form aggregates. We selected antibodies that have all
been approved by the FDA and are indicated for treatment of various types of
cancer. We collected the amino acid sequences of the antibodies and their
3D-structures that have been deposited in the RCSB PDB. AMYLPRED2 consensus
method was used to predict ‘aggregation-prone’ regions on the surface of these
proteins. Considering the 3D-structures of these antibodies, and the exposed
to the solvent amino acid residues of the protein, we tentatively replaced
amino acid residues with exposed side chains in the predicted ‘aggregation-
prone’ regions. These residues were substituted by others, resulting in
reduction of antibodies’ potential to form aggregates. We calculated new models
and in order to ensure that the side chains of them are still exposed and do
not have histeric hindrance, structure minimization was performed. This
computational study must be experimentally verified in order to ensure that
these substitutions decrease the antibodies’ tendency to form aggregates.
Keywords:
Monoclonal, Antibodies, Cancer, Aggregates, AMYLPRED2
