pH-selective mutagenesis of protein-protein interfaces: in silico design of therapeutic antibodies with prolonged half-life.
Velin Z. Spassov,Lisa Yan +1 more
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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.read more
Citations
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On Human Disease-Causing Amino Acid Variants: Statistical Study of Sequence and Structural Patterns
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AB-Bind: Antibody binding mutational database for computational affinity predictions.
TL;DR: A diverse set of antibody binding data with accompanying structures that can be used to evaluate methods for modeling antibody interactions is reported, demonstrating the continuing need to develop and improve protein energy functions for affinity prediction.
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Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method
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Predicting the Impact of Missense Mutations on Protein–Protein Binding Affinity
TL;DR: An efficient computational approach based on a well-tested simulation protocol for predicting the effect of single and multiple missense mutations on protein–protein binding affinity achieves high speed and prediction accuracy and can be applied to large datasets generated by modern genomics initiatives.
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Journal ArticleDOI
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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.
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