Index of papers in PLOS Comp. Biol. that mention
  • free energy
Xiliang Zheng, Jin Wang
Abstract
We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor.
Abstract
The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus nonnative binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of nonnative states versus the roughness measured by the variance of the free energy landscape around its mean.
Abstract
The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecu-lar recognition and function through small-molecule evolution and chemical genetics.
Introduction
In this way, one can characterize the re-ceptor-ligand system and obtain the important statistical information and distributions on the relevant physical properties or observables of the system such as the binding free energy , equilibrium constants, and specificity.
Theory and Analytical Models
Since Log K is proportional to the free energy difference between the native and nonnative states termed as the stability or affinity, this infers that the free energy also has a distribution.
Theory and Analytical Models
The experimental features on binding indicate that the appropriate physical variable is the free energy of binding of ligands to the receptor, not the energy.
Theory and Analytical Models
As a result, the free energy stability or affinity for each specific sequence of ligand can be obtained.
free energy is mentioned in 57 sentences in this paper.
Topics mentioned in this paper:
Lucas A. Defelipe, Esteban Lanzarotti, Diego Gauto, Marcelo A. Marti, Adrián G. Turjanski
QM/MM methods
Determination of the reaction free energy profile using QM(DFTB)/MM and Multiple steered molecular dynamics (MSMD) strategy.
QM/MM methods
To determine the free energy of the reaction we used the MSMD method [56,57] which allows to link non equilibrium pulling trajectories with equilibrium properties like the free energy, and has been extensively used in our group to determine free energy profiles[57—60].
QM/MM methods
AG(>L) and W(>L) are the change in free energy and the external work performed on the system as it evolves from k 2 k0 to k, respectively.
Results
Secondly, we analyzed the “forbidden” conformation and finally, we determined the free energy profile of the sulfenic acid to cyclic sulfenyl amide reaction using QM/MM methods in human PTPlB.
Results
We initially analyzed the free energy difference between the forbidden-psi conformation and allowed helix conformation.
Results
3B allows an estimation of how much energy proteins must pay to constraint the Cys in the reactive (forbidden-psi) conformation using the Ramachandran plot derived free energy , estimated it around 5.5 kcal/mol.
free energy is mentioned in 19 sentences in this paper.
Topics mentioned in this paper:
Jian Tian, Jaie C. Woodard, Anna Whitney, Eugene I. Shakhnovich
Entropy of the native state is an important contributor to stability
The theoretical analysis of the unfolding simulations relates the effect of mutations on the equilibrium between folded and unfolded states to the effect of mutations on free energy of the folded and transition states.
Introduction
The unfolding temperature, Tm, at which the free energy of the folded and unfolded states coincide (AG 2 0) serves as a common measure of protein stability.
Introduction
Other existing techniques to rationally design proteins with improved stability have involved optimization of charge-charge interactions [23], saturation mutagenesis of residues with high crystallographic B-factors [24], methods based on protein simulation and calculation of free energies [25—27] and comparison to homologous proteins including the ultra-stable proteins of thermophiles [28,29].
Predicting the effects of mutations on protein stability from non-equilibrium unfolding simulations
Although the idea of obtaining equilibrium free energy differences from non-equilibrium measurements is not new [35], and protein stabilities have been calculated from molecular dynamics simulations using the Iarzynski equality, e.g., [36—38] , such simulations require application of an external steering force; in the present paper we report the use of multi-temperature Monte-Carlo unfolding simulations in obtaining protein stabilities.
Predicting the effects of mutations on protein stability from non-equilibrium unfolding simulations
Assuming two-state unfolding kinetics [39—42] we can estimate the characteristic time required to cross the unfolding free energy barrier (in fact it is the time spent in the native state waiting for sufficient thermal fluctuation to cross the barrier) as:
Predicting the effects of mutations on protein stability from non-equilibrium unfolding simulations
Where T137 is first-passage time from the folded to the unfolded state, AG# is the free energy barrier between the folded state and the transition state for unfolding (see Fig.
free energy is mentioned in 8 sentences in this paper.
Topics mentioned in this paper:
Tomáš Trnka, Stanislav Kozmon, Igor Tvaroška, Jaroslav Koča
Introduction
Their results are based on QM/MM Car-Parrinello molecular dynamics, using the metadynamics method to improve CV sampling and calculate free energy profiles, and support a single displacement with a two-step mechanism.
Introduction
[16] However, enhanced sampling methods like metadynamics provide correct free energy data only after the system reaches the regime of free diffusion along the reaction path.
Path optimisation
14 kcal mol‘1 is in very good agreement with the phenomenological free energy barrier of approx 17 kcal mol_1, that can be calculated using transition state theory from the experimentally determined kcat value of 3.70 s_1.
Path optimisation
Finally, it has to be noted that the results are based purely on potential energy data While the real physical process is controlled by free energy .
Path optimisation
The depth of the minimum may thus be significantly affected by the entropic effects included in free energy .
free energy is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Pedro Saa, Lars K. Nielsen
Dissecting enzyme catalysis: assessing the impact of reaction molecularity
To eXplore the consequences of this tradeoff in enzymatic reactions, we uniformly sampled the kinetic space of three ordered mechanisms following different molecularities: Uni-Uni, BiBi and Ter-Ter, under different Gibbs free energy differences and a constant reference flux.
E-glc-atp
high substrate concentrations and almost no products, a reference Gibbs free energy difference of - 100 kI/mol was used.
Parameterization and sampling of the catalytic mechanism
Where AG, represents the Gibbs free energy difference of reaction, R denotes the universal gas constant, T is the absolute temperature and vref denotes the reaction reference flux.
Revealing the impact of thermodynamics on enzyme kinetics
substrate and product elasticities, at different Gibbs free energy differences ranging from -1 (close to equilibrium) to -80 kI/mol (practically irreversible).
Sampling functional contributions: catalytic and regulatory effects
In the case of the conformational transitions, the change of the Gibbs free energy of conformations between the R and T states is constrained by the ligand affinity of the two states.
free energy is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Miriam C. Klein-Flügge, Steven W. Kennerley, Ana C. Saraiva, Will D. Penny, Sven Bestmann
Bayesian parameter estimation and model comparison
Importantly, the algorithm also provides the free energy P, which is an approximation to the model evidence.
Bayesian parameter estimation and model comparison
This free energy approach yields better model scores than does the Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC) [95].
Bayesian parameter estimation and model comparison
The optimal set of parameters, i.e., that obtained from the initialization that resulted in the maximal free energy , is reported in this manuscript.
free energy is mentioned in 4 sentences in this paper.
Topics mentioned in this paper: