Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gibbs free energy of protein-protein interactions correlates with ATP production in cancer cells.

ABSTRACT: In this paper, we analyze several cancer cell types from two seemingly independent angles: (a) the over-expression of various proteins participating in protein-protein interaction networks and (b) a metabolic shift from oxidative phosphorylation to glycolysis. We use large data sets to obtain a thermodynamic measure of the protein-protein interaction network, namely the associated Gibbs free energy. We find a strong inverse correlation between the percentage of energy production via oxidative phosphorylation and the Gibbs free energy of the protein networks. The latter is a measure of functional dysregulation within the cell. Our findings corroborate earlier indications that signaling pathway upregulation in cancer cells is linked to the metabolic shift known as the Warburg effect; hence, these two seemingly independent characteristics of cancer phenotype may be interconnected.

SUBMITTER: Golas SM

PROVIDER: S-EPMC6917683 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Gibbs free energy of protein-protein interactions correlates with ATP production in cancer cells.

Golas Stefan M SM Nguyen Amber N AN Rietman Edward A EA Tuszynski Jack A JA

Journal of biological physics 20191216 4

In this paper, we analyze several cancer cell types from two seemingly independent angles: (a) the over-expression of various proteins participating in protein-protein interaction networks and (b) a metabolic shift from oxidative phosphorylation to glycolysis. We use large data sets to obtain a thermodynamic measure of the protein-protein interaction network, namely the associated Gibbs free energy. We find a strong inverse correlation between the percentage of energy production via oxidative ph ...[more]

PMID: 31845118

Similar Datasets

PCR cycles affect gibbs free energy bias

Project description:We amplified DNA fragments randomly sheared from PER1 BAC library with four different PCR cycles (3, 6, 12, and 18 cycles). We report the effect of Gibbs free energy bias to coverage significantly increases with additional number of PCR cycles, especially for fragments with high Gibbs free energy (usually corresponding to low GC content).

2020-05-06 | GSE149914 | GEO

Gibbs free energy as a measure of complexity correlates with time within C. elegans embryonic development.

Project description:We investigate free energy behavior in the nematode Caenorhabditis elegans during embryonic development. Our approach utilizes publicly available gene expression data, which gives us a picture of developmental changes in protein concentration and, resultantly, chemical potential and free energy. Our results indicate a clear global relationship between Gibbs free energy and time spent in development and provide thermodynamic indicators of the large-scale biological events of cell division and differentiation.

| S-EPMC5696307 | biostudies-literature

PCR cycles affect gibbs free energy bias

Project description:PCR cycles affect gibbs free energy bias

| PRJNA630479 | ENA

Free energy decomposition of protein-protein interactions.

Project description:A free energy decomposition scheme has been developed and tested on antibody-antigen and protease-inhibitor binding for which accurate experimental structures were available for both free and bound proteins. Using the x-ray coordinates of the free and bound proteins, the absolute binding free energy was computed assuming additivity of three well-defined, physical processes: desolvation of the x-ray structures, isomerization of the x-ray conformation to a nearby local minimum in the gas-phase, and subsequent noncovalent complex formation in the gas phase. This free energy scheme, together with the Generalized Born model for computing the electrostatic solvation free energy, yielded binding free energies in remarkable agreement with experimental data. Two assumptions commonly used in theoretical treatments; viz., the rigid-binding approximation (which assumes no conformational change upon complexation) and the neglect of vdW interactions, were found to yield large errors in the binding free energy. Protein-protein vdW and electrostatic interactions between complementary surfaces over a relatively large area (1400--1700 A(2)) were found to drive antibody-antigen and protease-inhibitor binding.

| S-EPMC1301550 | biostudies-other

Limits of Free Energy Computation for Protein-Ligand Interactions.

Project description:A detailed error analysis is presented for the computation of protein-ligand interaction energies. In particular, we show that it is probable that even highly accurate computed binding free energies have errors that represent a large percentage of the target free energies of binding. This is due to the observation that the error for computed energies quasi-linearly increases with the increasing number of interactions present in a protein-ligand complex. This principle is expected to hold true for any system that involves an ever increasing number of inter or intra-molecular interactions (e.g. ab initio protein folding). We introduce the concept of best-case scenario errors (BCS(errors)) that can be routinely applied to docking and scoring exercises and used to provide errors bars for the computed binding free energies. These BCS(errors) form a basis by which one can evaluate the outcome of a docking and scoring exercise. Moreover, the resultant error analysis enables the formation of an hypothesis that defines the best direction to proceed in order to improve scoring functions used in molecular docking studies.

| S-EPMC2866028 | biostudies-literature

Gibbs Sampler-Based ?-Dynamics and Rao-Blackwell Estimator for Alchemical Free Energy Calculation.

Project description:?-dynamics is a generalized ensemble method for alchemical free energy calculations. In traditional ?-dynamics, the alchemical switch variable ? is treated as a continuous variable ranging from 0 to 1 and an empirical estimator is utilized to approximate the free energy. In the present article, we describe an alternative formulation of ?-dynamics that utilizes the Gibbs sampler framework, which we call Gibbs sampler-based ?-dynamics (GSLD). GSLD, like traditional ?-dynamics, can be readily extended to calculate free energy differences between multiple ligands in one simulation. We also introduce a new free energy estimator, the Rao-Blackwell estimator (RBE), for use in conjunction with GSLD. Compared with the current empirical estimator, the advantage of RBE is that RBE is an unbiased estimator and its variance is usually smaller than the current empirical estimator. We also show that the multistate Bennett acceptance ratio equation or the unbinned weighted histogram analysis method equation can be derived using the RBE. We illustrate the use and performance of this new free energy computational framework by application to a simple harmonic system as well as relevant calculations of small molecule relative free energies of solvation and binding to a protein receptor. Our findings demonstrate consistent and improved performance compared with conventional alchemical free energy methods.

| S-EPMC5828534 | biostudies-literature

Gibbs Free Energy Calculation of Mutation in PncA and RpsA Associated With Pyrazinamide Resistance.

Project description:A central approach for better understanding the forces involved in maintaining protein structures is to investigate the protein folding and thermodynamic properties. The effect of the folding process is often disturbed in mutated states. To explore the dynamic properties behind mutations, molecular dynamic (MD) simulations have been widely performed, especially in unveiling the mechanism of drug failure behind mutation. When comparing wild type (WT) and mutants (MTs), the structural changes along with solvation free energy (SFE), and Gibbs free energy (GFE) are calculated after the MD simulation, to measure the effect of mutations on protein structure. Pyrazinamide (PZA) is one of the first-line drugs, effective against latent Mycobacterium tuberculosis isolates, affecting the global TB control program 2030. Resistance to this drug emerges due to mutations in pncA and rpsA genes, encoding pyrazinamidase (PZase) and ribosomal protein S1 (RpsA) respectively. The question of how the GFE may be a measure of PZase and RpsA stabilities, has been addressed in the current review. The GFE and SFE of MTs have been compared with WT, which were already found to be PZA-resistant. WT structures attained a more stable state in comparison with MTs. The physiological effect of a mutation in PZase and RpsA may be due to the difference in energies. This difference between WT and MTs, depicted through GFE plots, might be useful in predicting the stability and PZA-resistance behind mutation. This study provides useful information for better management of drug resistance, to control the global TB problem.

| S-EPMC7160322 | biostudies-literature

Insights into Membrane Protein-Lipid Interactions from Free Energy Calculations.

Project description:Integral membrane proteins are regulated by specific interactions with lipids from the surrounding bilayer. The structures of protein-lipid complexes can be determined through a combination of experimental and computational approaches, but the energetic basis of these interactions is difficult to resolve. Molecular dynamics simulations provide the primary computational technique to estimate the free energies of these interactions. We demonstrate that the energetics of protein-lipid interactions may be reliably and reproducibly calculated using three simulation-based approaches: potential of mean force calculations, alchemical free energy perturbation, and well-tempered metadynamics. We employ these techniques within the framework of a coarse-grained force field and apply them to both bacterial and mammalian membrane protein-lipid systems. We demonstrate good agreement between the different techniques, providing a robust framework for their automated implementation within a pipeline for annotation of newly determined membrane protein structures.

| S-EPMC6785801 | biostudies-literature

Quantifying Nonnative Interactions in the Protein-Folding Free-Energy Landscape.

Project description:Protein folding is a central problem in biological physics. Energetic roughness is an important aspect that controls protein-folding stability and kinetics. The roughness is associated with conflicting interactions in the protein and is also known as frustration. Recent studies indicate that an addition of a small amount of energetic frustration may enhance folding speed for certain proteins. In this study, we have investigated the conditions under which frustration increases the folding rate. We used a Cα structure-based model to simulate a group of proteins. We found that the free-energy barrier at the transition state (ΔF) correlates with nonnative-contact variation (ΔA), and the simulated proteins are clustered according to their fold motifs. These findings are corroborated by the Clementi-Plotkin analytical model. As a consequence, the optimum frustration regime for protein folding can be predicted analytically.

| S-EPMC4968343 | biostudies-literature

Cell-free expression of RuBisCO for ATP production in the synthetic cells.

Project description:Recent advances in bottom-up synthetic biology have made it possible to reconstitute cellular systems from non-living components, yielding artificial cells with potential applications in industry, medicine and basic research. Although a variety of cellular functions and components have been reconstituted in previous studies, sustained biological energy production remains a challenge. ATP synthesis via ribulose-1,5-diphosphate carboxylase/oxygenase (RuBisCO), a central enzyme in biological CO2 fixation, holds potential as an energy production system, but its feasibility in a cell-free expression system has not yet been tested. In this study, we test RuBisCO expression and its activity-mediated ATP synthesis in a reconstituted Escherichia coli-based cell-free translation system. We then construct a system in which ATP is synthesized by RuBisCO activity in giant vesicles and used as energy for translation reactions. These results represent an advance toward independent energy production in artificial cells. Graphical Abstract.

| S-EPMC10750972 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data