ANTISOMA: A Computational Pipeline for the Reduction of the Aggregation Propensity of Monoclonal Antibodies

Adv Exp Med Biol. 2020:1194:359-371. doi: 10.1007/978-3-030-32622-7_34.


Monoclonal antibodies (mAbs) constitute a promising class of therapeutics, since ca. 25% of all biotech drugs in development are mAbs. Even though their therapeutic value is now well established, human- and murine-derived mAbs do have deficiencies, such as short in vivo lifespan and low stability. However, the most difficult obstacle to overcome, toward the exploitation of mAbs for disease treatment, is the prevention of the formation of protein aggregates. ANTISOMA is a pipeline for the reduction of the aggregation tendency of mAbs through the decrease in their intrinsic aggregation propensity, based on an automated amino acid substitution approach. The method takes into consideration the special features of mAbs and aims at proposing specific point mutations that could lead to the redesign of those promising therapeutics, without affecting their epitope-binding ability. The method is available online at .

Keywords: In silico models; Monoclonal antibodies; Protein aggregation; mAbs.

MeSH terms

  • Animals
  • Antibodies, Monoclonal* / genetics
  • Antibodies, Monoclonal* / metabolism
  • Antibodies, Monoclonal* / therapeutic use
  • Computational Biology* / methods
  • Epitopes / genetics
  • Humans
  • Mice
  • Protein Aggregation, Pathological* / drug therapy


  • Antibodies, Monoclonal
  • Epitopes