Methods to identify macromolecule binding and aggregation prone regions in proteins and uses therefor

Abstract

The present invention provides methods and computational tools based, at least in part, on computer simulations that identify macromolecule binding regions and aggregation prone regions of a protein. Substitutions may then be made in these aggregation prone regions to engineer proteins with enhanced stability and / or a reduced propensity for aggregation. Similarly, substitutions may then be made in these macromolecule binding regions to engineer proteins with altered binding affinity for the macromolecule.

Description

BACKGROUND OF THE INVENTION[0001]Understanding and controlling protein stability has been a coveted endeavor to Biologists, Chemists, and Engineers. The first link between amino acid substitution and disease (Ingram. Nature. 1957, 180(4581):326-8.) offered a new and essential perspective on protein stability in health and disease. The recent tremendous increase of protein-based pharmaceuticals has created a new challenge. Therapeutic proteins are stored in liquid for several months at very high concentrations. The percent of non-monomeric species increases with time. As aggregates form, not only the efficacy of the product decreases, but side effects such as immunological response upon administration may occur. Assuring stability of protein pharmaceuticals for the shelf-life of the product is imperative.[0002]Because of their potential in the cure of various diseases, antibodies currently constitute the most rapidly growing class of human therapeutics (Carter. Nature Reviews Immunol...

AI Technical Summary

Benefits of technology

[0014]The present invention provides methods and computational tools based, at least in part, on computer simulations that identify aggregation prone regions of a protein. Substitutions may then be made in these aggregation prone regions to engineer proteins with enhanced stability and / or a reduced propensity for aggregation.

Problems solved by technology

The recent tremendous increase of protein-based pharmaceuticals has created a new challenge.

As aggregates form, not only the efficacy of the product decreases, but side effects such as immunological response upon administration may occur.

However, these antibodies are thermodynamically unstable under these conditions and degrade due to aggregation.

The aggregation in turn leads to a decrease in antibody activity making the drug ineffective and can even generate an immunological response.

However, the main limitation of the seven-parameter model is that all residues in the sequence were given same relative importance.

Although, it is not possible to calculate absolute rates of aggregation with TANGO, it provides a qualitative comparison between peptides or proteins differing significantly in sequence.

More detailed models, such as the intermediate resolution model followed but suffered from the same inability to accurately represent protein secondary and tertiary structures.

The explicit model is more accurate but also more computationally demanding.

However, because such a procedure is very computationally demanding, especially for large proteins such as antibodies there does not appear to be full antibody atomistic simulation in the literature.

Although these additives enable proteins to be stabilized to some degree in solution, they suffer from certain disadvantages such as the necessity of additional processing steps for additive removal.

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