Literature DB >> 21184609

Computational design and biophysical characterization of aggregation-resistant point mutations for γD crystallin illustrate a balance of conformational stability and intrinsic aggregation propensity.

Erinc Sahin1, Jacob L Jordan, Michelle L Spatara, Andrea Naranjo, Joseph A Costanzo, William F Weiss, Anne Skaja Robinson, Erik J Fernandez, Christopher J Roberts.   

Abstract

γD crystallin is a natively monomeric eye-lens protein that is associated with hereditary juvenile cataract formation. It is an attractive model system as a multidomain Greek-key protein that aggregates through partially folded intermediates. Point mutations M69Q and S130P were used to test (1) whether the protein-design algorithm RosettaDesign would successfully predict mutants that are resistant to aggregation when combined with informatic sequence-based predictors of peptide aggregation propensity and (2) how the mutations affected relative unfolding free energies (ΔΔG(un)) and intrinsic aggregation propensity (IAP). M69Q was predicted to have ΔΔG(un) ≫ 0, without significantly affecting IAP. S130P was predicted to have ΔΔG(un) ∼ 0 but with reduced IAP. The stability, conformation, and aggregation kinetics in acidic solution were experimentally characterized and compared for the variants and wild-type (WT) protein using circular dichroism and intrinsic fluorescence spectroscopy, calorimetric and chemical unfolding, thioflavin-T binding, chromatography, static laser light scattering, and kinetic modeling. Monomer secondary and tertiary structures of both variants were indistinguishable from WT, while ΔΔG(un) > 0 for M69Q and ΔΔG(un) < 0 for S130P. Surprisingly, despite being the least conformationally stable, S130P was the most resistant to aggregation, indicating a significant decrease of its IAP compared to WT and M69Q.

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Year:  2011        PMID: 21184609     DOI: 10.1021/bi100978r

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


  19 in total

1.  Modulating non-native aggregation and electrostatic protein-protein interactions with computationally designed single-point mutations.

Authors:  C J O'Brien; M A Blanco; J A Costanzo; M Enterline; E J Fernandez; A S Robinson; C J Roberts
Journal:  Protein Eng Des Sel       Date:  2016-05-09       Impact factor: 1.650

2.  Predicting unfolding thermodynamics and stable intermediates for alanine-rich helical peptides with the aid of coarse-grained molecular simulation.

Authors:  Cesar Calero-Rubio; Bradford Paik; Xinqiao Jia; Kristi L Kiick; Christopher J Roberts
Journal:  Biophys Chem       Date:  2016-07-22       Impact factor: 2.352

3.  Orthogonal high-throughput thermal scanning method for rank ordering protein formulations.

Authors:  Vishal C Nashine; Andrew M Kroetsch; Erinc Sahin; Rong Zhou; Monica L Adams
Journal:  AAPS PharmSciTech       Date:  2013-09-04       Impact factor: 3.246

Review 4.  Therapeutic protein aggregation: mechanisms, design, and control.

Authors:  Christopher J Roberts
Journal:  Trends Biotechnol       Date:  2014-06-04       Impact factor: 19.536

5.  Two-dimensional IR spectroscopy and segmental 13C labeling reveals the domain structure of human γD-crystallin amyloid fibrils.

Authors:  Sean D Moran; Ann Marie Woys; Lauren E Buchanan; Eli Bixby; Sean M Decatur; Martin T Zanni
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-10       Impact factor: 11.205

6.  Kinetic Stability of Long-Lived Human Lens γ-Crystallins and Their Isolated Double Greek Key Domains.

Authors:  Ishara A Mills-Henry; Shannon L Thol; Melissa S Kosinski-Collins; Eugene Serebryany; Jonathan A King
Journal:  Biophys J       Date:  2019-06-14       Impact factor: 4.033

7.  Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation.

Authors:  Marco A Blanco; Erinc Sahin; Anne S Robinson; Christopher J Roberts
Journal:  J Phys Chem B       Date:  2013-12-10       Impact factor: 2.991

Review 8.  Non-Arrhenius protein aggregation.

Authors:  Wei Wang; Christopher J Roberts
Journal:  AAPS J       Date:  2013-04-25       Impact factor: 4.009

Review 9.  The βγ-crystallins: native state stability and pathways to aggregation.

Authors:  Eugene Serebryany; Jonathan A King
Journal:  Prog Biophys Mol Biol       Date:  2014-05-14       Impact factor: 3.667

10.  Reduction of the C191-C220 disulfide of α-chymotrypsinogen A reduces nucleation barriers for aggregation.

Authors:  William F Weiss; Aming Zhang; Magdalena I Ivanova; Erinc Sahin; Jacob L Jordan; Erik J Fernandez; Christopher J Roberts
Journal:  Biophys Chem       Date:  2013-11-28       Impact factor: 2.352

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