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Open AccessJournal ArticleDOI

pH-selective mutagenesis of protein-protein interfaces: in silico design of therapeutic antibodies with prolonged half-life.

Velin Z. Spassov, +1 more
- 01 Apr 2013 - 
- Vol. 81, Iss: 4, pp 704-714
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TLDR
A novel method for fast in silico mutagenesis of protein–protein complexes to calculate the effect of mutation as a function of pH and a computational strategy to search for mutations that can alter the pH‐dependent binding behavior of IgG to FcRn with the aim of improving the half‐life of therapeutic antibodies in the target organism.
Abstract
Understanding the effects of mutation on pH-dependent protein binding affinity is important in protein design, especially in the area of protein therapeutics. We propose a novel method for fast in silico mutagenesis of protein-protein complexes to calculate the effect of mutation as a function of pH. The free energy differences between the wild type and mutants are evaluated from a molecular mechanics model, combined with calculations of the equilibria of proton binding. The predicted pH-dependent energy profiles demonstrate excellent agreement with experimentally measured pH-dependency of the effect of mutations on the dissociation constants for the complex of turkey ovomucoid third domain (OMTKY3) and proteinase B. The virtual scanning mutagenesis identifies all hotspots responsible for pH-dependent binding of immunoglobulin G (IgG) to neonatal Fc receptor (FcRn) and the results support the current understanding of the salvage mechanism of the antibody by FcRn based on pH-selective binding. The method can be used to select mutations that change the pH-dependent binding profiles of proteins and guide the time consuming and expensive protein engineering experiments. As an application of this method, we propose a computational strategy to search for mutations that can alter the pH-dependent binding behavior of IgG to FcRn with the aim of improving the half-life of therapeutic antibodies in the target organism.

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Predicting the Impact of Missense Mutations on Protein–Protein Binding Affinity

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References
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Journal ArticleDOI

Comparative Protein Modelling by Satisfaction of Spatial Restraints

TL;DR: A comparative protein modelling method designed to find the most probable structure for a sequence given its alignment with related structures, which is automated and illustrated by the modelling of trypsin from two other serine proteinases.
Book ChapterDOI

Protein denaturation. C. Theoretical models for the mechanism of denaturation.

TL;DR: This chapter reviews theoretical models that might be constructed and equations that may be derived from them to understand the process of protein denaturation and finds that they can be predicted semiquantitatively.
Journal ArticleDOI

FcRn: the neonatal Fc receptor comes of age

TL;DR: The neonatal Fc receptor for IgG (FcRn) has been well characterized in the transfer of passive humoral immunity from a mother to her fetus and throughout life, FcRm protects IgG from degradation, thereby explaining the long half-life of this class of antibody in the serum.
Journal ArticleDOI

Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations.

TL;DR: The present energy function uses a minimum of computational resources and can therefore easily be used in protein design algorithms, and in the field of protein structure and folding pathways prediction where one requires a fast and accurate energy function.
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