Literature DB >> 27973814

Role of Molecular Flexibility and Colloidal Descriptions of Proteins in Crowded Environments from Small-Angle Scattering.

Maria Monica Castellanos1,2, Nicholas J Clark1, Max C Watson1, Susan Krueger1, Arnold McAuley3, Joseph E Curtis1.   

Abstract

Small-angle scattering is a powerful technique to study molecular conformation and interactions of proteins in solution and in amorphous solids. We have investigated the role of multiple protein configurations in the interaction parameters derived from small-angle scattering for proteins in concentrated solutions. In order to account for the wide configurational space sampled by proteins, we generate ensembles of atomistic structures for lysozyme and monoclonal antibodies, representing globular and flexible proteins, respectively. While recent work has argued that a colloidal approach is inadequate to model proteins, because of the large configurational space that they sample in solution, we find a range of length scales where colloidal models can be used to describe solution scattering data while simultaneously accounting for structural flexibility. We provide insights to determine the length scales where isotropic colloidal models can be used, and find smoothly varying sets of interaction parameters that encompass ensembles of structures. This approach may play an important role in the definition of long-range interactions in coarse-grained models of flexible proteins with experimental scattering constraints. Additionally, we apply the decoupling approximation to ensembles of lysozyme structures with atomistic detail and observe remarkably different results when using geometric solids, such as ellipsoids. The insights from this study provide guidelines for the analysis of small-angle scattering profiles of proteins in crowded environments.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27973814     DOI: 10.1021/acs.jpcb.6b10637

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  7 in total

1.  Predicting Protein-Protein Interactions of Concentrated Antibody Solutions Using Dilute Solution Data and Coarse-Grained Molecular Models.

Authors:  Cesar Calero-Rubio; Ranendu Ghosh; Atul Saluja; Christopher J Roberts
Journal:  J Pharm Sci       Date:  2017-12-21       Impact factor: 3.534

2.  Estimating and leveraging protein diffusion on ion-exchange resin surfaces.

Authors:  Ohnmar Khanal; Vijesh Kumar; Fabrice Schlegel; Abraham M Lenhoff
Journal:  Proc Natl Acad Sci U S A       Date:  2020-03-16       Impact factor: 11.205

3.  Evaluating the Effects of Hinge Flexibility on the Solution Structure of Antibodies at Concentrated Conditions.

Authors:  Marco A Blanco; Harold W Hatch; Joseph E Curtis; Vincent K Shen
Journal:  J Pharm Sci       Date:  2018-12-26       Impact factor: 3.534

4.  Predicting structural properties of fluids by thermodynamic extrapolation.

Authors:  Nathan A Mahynski; Sally Jiao; Harold W Hatch; Marco A Blanco; Vincent K Shen
Journal:  J Chem Phys       Date:  2018-05-21       Impact factor: 3.488

Review 5.  Investigating Structure and Dynamics of Proteins in Amorphous Phases Using Neutron Scattering.

Authors:  Maria Monica Castellanos; Arnold McAuley; Joseph E Curtis
Journal:  Comput Struct Biotechnol J       Date:  2016-12-21       Impact factor: 7.271

6.  Effects of Monovalent Salt on Protein-Protein Interactions of Dilute and Concentrated Monoclonal Antibody Formulations.

Authors:  Amy Y Xu; Nicholas J Clark; Joseph Pollastrini; Maribel Espinoza; Hyo-Jin Kim; Sekhar Kanapuram; Bruce Kerwin; Michael J Treuheit; Susan Krueger; Arnold McAuley; Joseph E Curtis
Journal:  Antibodies (Basel)       Date:  2022-03-31

7.  Characterization of Monoclonal Antibody-Protein Antigen Complexes Using Small-Angle Scattering and Molecular Modeling.

Authors:  Maria Monica Castellanos; James A Snyder; Melody Lee; Srinivas Chakravarthy; Nicholas J Clark; Arnold McAuley; Joseph E Curtis
Journal:  Antibodies (Basel)       Date:  2017-12-15
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.