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Predicting Immunogenicity Risk in Biopharmaceuticals

Faculty of Pharmacy, Medical University of Sofia, 1000 Sofia, Bulgaria
Author to whom correspondence should be addressed.
Academic Editors: Jan Awrejcewicz and Dumitru Baleanu
Symmetry 2021, 13(3), 388;
Received: 4 February 2021 / Revised: 18 February 2021 / Accepted: 23 February 2021 / Published: 27 February 2021
(This article belongs to the Special Issue Biopharmaceuticals: Topics and Advances)
The assessment of immunogenicity of biopharmaceuticals is a crucial step in the process of their development. Immunogenicity is related to the activation of adaptive immunity. The complexity of the immune system manifests through numerous different mechanisms, which allows the use of different approaches for predicting the immunogenicity of biopharmaceuticals. The direct experimental approaches are sometimes expensive and time consuming, or their results need to be confirmed. In this case, computational methods for immunogenicity prediction appear as an appropriate complement in the process of drug design. In this review, we analyze the use of various In silico methods and approaches for immunogenicity prediction of biomolecules: sequence alignment algorithms, predicting subcellular localization, searching for major histocompatibility complex (MHC) binding motifs, predicting T and B cell epitopes based on machine learning algorithms, molecular docking, and molecular dynamics simulations. Computational tools for antigenicity and allergenicity prediction also are considered. View Full-Text
Keywords: immunogenicity; In silico; bioinformatics; machine learning; epitope immunogenicity; In silico; bioinformatics; machine learning; epitope
MDPI and ACS Style

Doneva, N.; Doytchinova, I.; Dimitrov, I. Predicting Immunogenicity Risk in Biopharmaceuticals. Symmetry 2021, 13, 388.

AMA Style

Doneva N, Doytchinova I, Dimitrov I. Predicting Immunogenicity Risk in Biopharmaceuticals. Symmetry. 2021; 13(3):388.

Chicago/Turabian Style

Doneva, Nikolet; Doytchinova, Irini; Dimitrov, Ivan. 2021. "Predicting Immunogenicity Risk in Biopharmaceuticals" Symmetry 13, no. 3: 388.

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