Biobetters From an Integrated Computational/Experimental Approach

Abstract

Biobetters are new drugs designed from existing peptide or protein-based therapeutics by improving their properties such as affinity and selectivity for the target epitope, and stability against degradation. Computational methods can play a key role in such design problems—by predicting the changes that are most likely to succeed, they can drastically reduce the number of experiments to be performed. Here we discuss the computational and experimental methods commonly used in drug design problems, focusing on the inverse relationship between the two, namely, the more accurate the computational predictions means the less experimental effort is needed for testing. Examples discussed include efforts to design selective analogs from toxin peptides targeting ion channels for treatment of autoimmune diseases and monoclonal antibodies which are the fastest growing class of therapeutic agents particularly for cancers and autoimmune diseases.

Glycan Profile Analysis of Engineered Trastuzumab with Rationally Added Glycosylation Sequons Presents Significantly Increased Glycan Complexity

“…To tackle this issue, numerous strategies have been developed and are the subject of intense exploration. These approaches can be broadly classified into two main categories: those that enhance the intrinsic stability of the protein to prevent aggregation throughout the manufacturing process [12][13][14][15], and those that improve the formulation of the final product by the optimization of pH, ionic strength and the incorporation of stabilizing agents [16][17][18].…”

“…It is widely believed that surface-exposed hydrophobic regions in proteins can lead to self-association and initiate the formation of larger aggregates [8,12]. To tackle this, in silico methods have been developed to screen and identify aggregationprone regions (APR) [12,15,21,22]. Exposed hydrophobic amino acids in APRs can then be replaced with more hydrophilic or charged residues through mutagenesis [10,12,13].…”

In silico and in vivo analyses of the mutated human tissue plasminogen activator (mtPA) and the antithetical effects of P19 silencing suppressor on its expression in two Nicotiana species

“…This is the first study in which the in silico prediction of a mutated enzyme activity is analyzed in the plant. Such in silico (computational) studies have the potential to reduce the guesswork drastically and to facilitate the development of the optimal biobetter since these studies inspect the validation of the complex structure with the best binding mode to design the biobetters 33 . A biobetter refers to a recombinant protein drug with structural and/or functional changes which improve them in one or more characteristics compared to the original 33 – 35 .…”

“…Such in silico (computational) studies have the potential to reduce the guesswork drastically and to facilitate the development of the optimal biobetter since these studies inspect the validation of the complex structure with the best binding mode to design the biobetters 33 . A biobetter refers to a recombinant protein drug with structural and/or functional changes which improve them in one or more characteristics compared to the original 33 – 35 . To test the feasibility of producing a higher level of the new mutated form of the tPA protein, we transiently expressed the recombinant full-mtPA via Agrobacterium -mediated system in both N .…”