Protein interfaces are of biomedical relevance not only as drug targets but also in cellular aggregates. Cells use liquid-liquid phase transitions involving proteins and other macromolecules to locally sequester components and thereby regulate many processes. The dense liquid like phases of non-enveloped organelles or cellular bodies are a way to change the cytosolic activity of the aggregated species. We will study the mechanisms of protein solubility and phase separations as an organizing principle to characterize protein aggregation and recognition. We will consider the contributions of each of the amino acids to the formation of protein-protein interfaces in various states of aggregation from dimers to phase separated systems. Theoretical analyses of large scale computer simulations will be used to compare with experimental data. The change in the free energy of solution with respect to concentration of proteins and peptides has been difficult to compute. We will make use of our new computational tools to study concentration driven phenomena for peptides and proteins. We can calculate the solubility limits and analyze the change in solution free energy along the aggregation/nucleation coordinate. We hypothesize there is a relationship among protein solution states involved in aggregation and those in recognition between proteins. Solubility is a stringent test of the balance of solvation and protein interactions in current force fields. By analyzing the mechanism in terms of contributions of the solubility of each of the amino acids to the aggregation, we will build more reliable and accurate models of the nonpolar van der Waals solvation components of the mechanism using our new perturbative analysis methods. This is not a protein interface prediction project, but rather we seek to understand the relationship between how any interface, ordered or disordered, is made and the components of the underlying free energy surface driving solubility.

Public Health Relevance

In biology, aggregation in cells is a regulatory mechanism with many uses, which has not been well characterized theoretically even though the experimental literature is growing rapidly. We propose to consider the relation of the solubility o proteins and amino acid constituents to the mechanism of interface formation. We will compare several types of protein interfaces from dimer to crystal to disordered aggregate, not to predict specific interfaces, but rather to understand the relationship between how any interface, ordered or disordered, is made and the components of the underlying free energy surface driving solubility.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM037657-25
Application #
9270022
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
1988-08-01
Project End
2020-05-31
Budget Start
2017-06-01
Budget End
2018-05-31
Support Year
25
Fiscal Year
2017
Total Cost
$299,608
Indirect Cost
$102,108
Name
University of Texas Medical Br Galveston
Department
Biochemistry
Type
Schools of Medicine
DUNS #
800771149
City
Galveston
State
TX
Country
United States
Zip Code
77555
Seckfort, Danielle; Montgomery Pettitt, B (2018) Price of disorder in the lac repressor hinge helix. Biopolymers :e23239
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Ou, Shu-Ching; Drake, Justin A; Pettitt, B Montgomery (2017) Nonpolar Solvation Free Energy from Proximal Distribution Functions. J Phys Chem B 121:3555-3564
Kolawole, Abimbola O; Smith, Hong Q; Svoboda, Sophia A et al. (2017) Norovirus Escape from Broadly Neutralizing Antibodies Is Limited to Allostery-Like Mechanisms. mSphere 2:
Zhang, Cheng; Drake, Justin A; Ma, Jianpeng et al. (2017) Optimal updating magnitude in adaptive flat-distribution sampling. J Chem Phys 147:174105
Chen, Chuanying; Pettitt, B Montgomery (2016) DNA Shape versus Sequence Variations in the Protein Binding Process. Biophys J 110:534-544
Zhang, Cheng; Lai, Chun-Liang; Pettitt, B Montgomery (2016) Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace. Mol Simul 42:1079-1089

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