ArticleJournal of pharmaceutical sciences2009
Using empirical phase diagrams to understand the role of intramolecular dynamics in immunoglobulin G stability.
Article in Journal of pharmaceutical sciences, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Novel insights in linking solvent relaxation dynamics and protein conformations utilizing red edge excitation shift approach.Emerging topics in life sciences · 2021Review
- Toward Biotherapeutics Formulation Composition Engineering using Site-Identification by Ligand Competitive Saturation (SILCS).Journal of pharmaceutical sciences · 2021Article
- Challenges and Opportunities for the Subcutaneous Delivery of Therapeutic Proteins.Journal of pharmaceutical sciences · 2018Review
- Assessment of physical stability of an antibody drug conjugate by higher order structure analysis: impact of thiol- maleimide chemistry.Pharmaceutical research · 2014Article
- Understanding the relevance of local conformational stability and dynamics to the aggregation propensity of an IgG1 and IgG2 monoclonal antibodies.Protein science : a publication of the Protein Society · 2013Article
- Comparison of the structural stability and dynamic properties of recombinant anthrax protective antigen and its 2-fluorohistidine-labeled analogue.Journal of pharmaceutical sciences · 2012Article
- Improved data visualization techniques for analyzing macromolecule structural changes.Protein science : a publication of the Protein Society · 2012Article
- pH effects on binding between the anthrax protective antigen and the host cellular receptor CMG2.Protein science : a publication of the Protein Society · 2012Article
- Multidimensional methods for the formulation of biopharmaceuticals and vaccines.Journal of pharmaceutical sciences · 2011Review
- Probing residue-specific interactions in the stabilization of proteins using high-resolution NMR: a study of disulfide bond compensation.Journal of pharmaceutical sciences · 2010Article
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Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Understanding the relationship between protein dynamics and stability is of paramount importance to the fields of biology and pharmaceutics. Clarifying this relationship is complicated by the large amount of experimental data that must be generated and analyzed if motions that exist over the wide range of timescales are to be included. To address this issue, we propose an approach that utilizes a multidimensional vector-based empirical phase diagram (EPD) to analyze a set of dynamic results acquired across a temperature-pH perturbation plane. This approach is applied to a humanized immunoglobulin G1 (IgG1), a protein of major biological and pharmaceutical importance whose dynamic nature is linked to its multiple biological roles. Static and dynamic measurements are used to characterize the IgG and to construct both static and dynamic EPDs. Between pH 5 and 8, a single, pH-dependent transition is observed that corresponds to thermal unfolding of the IgG. Under more acidic conditions, evidence exists for the formation of a more compact, aggregation resistant state of the immunoglobulin, known as A-form. The dynamics-based EPD presents a considerably more detailed pattern of apparent phase transitions over the temperature-pH plane. The utility and potential applications of this approach are discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.