arXiv subjects

F. Marty Ytreberg

Publications and source records attributed to F. Marty Ytreberg.

14 recordsLinked to original sources

arXiv2010

Computational Estimates of Binding Affinities for Estrogen Receptor Isoforms in Rainbow Trout

Molecular dynamics simulations were used to determine the binding affinities between between the hormone 17 beta-estradiol (E2) and different estrogen receptor (ER) isoforms in the rainbow trout, Oncorhynchus mykiss. Previous phylogenetic analysis indicates that a whole genome duplication prior to the divergence of ray-finned fish led to two distinct ER beta isoforms, ER beta 1 and ER beta 2, and the recent whole genome duplication in the ancestral salmonid created two ER alpha isoforms, ER alpha 1 and ER alpha 2. The objective of our computational studies is to provide insight into the underlying evolutionary pressures on these isoforms. For the ER alpha subtype our results show that E2 binds preferentially to ER alpha 1 over ER alpha 2. Tests of lineage specific dN/dS ratios indicate that the ligand binding domain of the ER alpha 2 gene is evolving under relaxed selection relative to all other ER alpha genes. Comparison with the highly conserved DNA binding domain suggests that ER alpha 2 may be undergoing neofunctionalization possibly by binding to another ligand. By contrast, both ER beta 1 and ER beta 2 bind similarly to E2 and the best fitting model of selection indicates that the ligand binding domain of all ER beta genes are evolving under the same level of purifying selection, comparable to ER alpha 1.

physics.bio-ph↗

arXiv2010

Accurate Estimation of Solvation Free Energy Using Polynomial Fitting Techniques

This report details an approach to improve the accuracy and precision of free energy difference estimates using thermodynamic integration data (slope of the free energy with respect to the switching variable lambda) and its application to calculating solvation free energy. The central idea is to utilize polynomial fitting schemes to approximate the thermodynamic integration data to improve the accuracy and precision of the free energy difference estimates. In this report we introduce polynomial and spline interpolation techniques. Two systems with analytically solvable relative free energies are used to test the accuracy and precision of the interpolation approach (Shyu and Ytreberg, J Comput Chem 30: 2297-2304, 2009). We also use both interpolation and extrapolation methods to determine a small molecule salvation free energy. Our simulations show that, using such polynomial techniques and non-equidistant lambda values, the solvation free energy can be estimated with high accuracy without using soft-core scaling and separate simulations for Lennard-Jones and partial charges. The results from our study suggest these polynomial techniques, especially with use of non-equidistant lambda values, improve the accuracy and precision for dF estimates without demanding additional simulations. To allow researchers to immediately utilize these methods, free software and documentation is provided via http://www.phys.uidaho.edu/ytreberg/software

physics.comp-ph↗

arXiv2009

Computational study of small molecule binding for both tethered and free conditions

Using a calix[4]arene-benzene complex as a test system we compare the potential of mean force for when the calix[4]arene is tethered versus free. When the complex is in vacuum our results show that the difference between tethered and free is primarily due to the entropic contribution to the potential of mean force resulting in a binding free energy difference of 6.5 kJ/mol. By contrast, when the complex is in water our results suggest that the difference between tethered and free is due to the enthalpic contribution resulting in a binding free energy difference of 1.6 kJ/mol. This study elucidates the roles of entropy and enthalpy for this small molecule system and emphasizes the point that tethering the receptor has the potential to dramatically impact the binding properties. These findings should be taken into consideration when using calixarene molecules in nanosensor design.

physics.bio-ph↗

arXiv2008

Absolute FKBP binding affinities obtained via non-equilibrium unbinding simulations

We compute absolute binding affinities for two ligands bound to the FKBP protein using non-equilibrium unbinding simulations. The methodology is straight-forward, requiring little or no modification to many modern molecular simulation packages. The approach makes use of a physical pathway, eliminating the need for complicated alchemical decoupling schemes. Results of this study are promising. For the ligands studied here the binding affinities are typically estimated within less than 4.0 kJ/mol of the target values; and the target values are within less than 1.0 kJ/mol of experiment. These results suggest that non-equilibrium simulation could provide a simple and robust means to estimate protein-ligand binding affinities.

physics.bio-ph↗

arXiv2008

Reducing the Bias and Uncertainty of Free Energy Estimates by Using Regression to Fit Thermodynamic Integration Data

This report presents the application of polynomial regression for estimating free energy differences using thermodynamic integration. We employ linear regression to construct a polynomial that optimally fits the thermodynamic integration data, and thus reduces the bias and uncertainty of the resulting free energy estimate. Two test systems with analytical solutions were used to verify the accuracy and precision of the approach. Our results suggest that regression with a high degree of polynomials give the most accurate free energy difference estimates, but often with a slightly larger variance, compared to commonly used quadrature techniques. High degrees of polynomials possess the flexibility to closely fit the thermodynamic integration data but are often sensitive to small changes in data points. To further improve overall accuracy and reduce uncertainty, we also examine the use of Chebyshev nodes to guide the selection of non-equidistant lambda values for the thermodynamic integration scheme. We conclude that polynomial regression with non-equidistant lambda values delivers the most accurate and precise free energy estimates for thermodynamic integration data. Software and documentation is available at http://www.phys.uidaho.edu/ytreberg/software

physics.comp-ph↗

arXiv2007

A "black-box" re-weighting analysis can correct flawed simulation data, after the fact

There is a great need for improved statistical sampling in a range of physical, chemical and biological systems. Even simulations based on correct algorithms suffer from statistical error, which can be substantial or even dominant when slow processes are involved. Further, in key biomolecular applications, such as the determination of protein structures from NMR data, non-Boltzmann-distributed ensembles are generated. We therefore have developed the "black-box" strategy for re-weighting a set of configurations generated by arbitrary means to produce an ensemble distributed according to any target distribution. In contrast to previous algorithmic efforts, the black-box approach exploits the configuration-space density observed in a simulation, rather than assuming a desired distribution has been generated. Successful implementations of the strategy, which reduce both statistical error and bias, are developed for a one-dimensional system, and a 50-atom peptide, for which the correct 250-to-1 population ratio is recovered from a heavily biased ensemble.

physics.comp-ph↗

arXiv2007

Demonstrated convergence of the equilibrium ensemble for a fast united-residue protein model

Due to the time-scale limitations of all-atom simulation of proteins, there has been substantial interest in coarse-grained approaches. Some methods, like "Resolution Exchange," [E. Lyman et al., Phys. Rev. Lett. 96, 028105 (2006)] can accelerate canonical all-atom sampling, but require properly distributed coarse ensembles. We therefore demonstrate that full sampling can indeed be achieved in a sufficiently simplified protein model, as verified by a recently developed convergence analysis. The model accounts for protein backbone geometry in that rigid peptide planes rotate according to atomistically defined dihedral angles, but there are only two degrees of freedom (phi and psi dihedrals) per residue. Our convergence analysis indicates that small proteins (up to 89 residues in our tests) can be simulated for more than 50 "structural decorrelation times" in less than a week on a single processor. We show that the fluctuation behavior is reasonable, as well as discussing applications, limitations, and extensions of the model.

physics.bio-ph↗

arXiv2006

Comparison of free energy methods for molecular systems

We present a detailed comparison of computational efficiency and precision for several free energy difference ($ΔF$) methods. The analysis includes both equilibrium and non-equilibrium approaches, and distinguishes between uni-directional and bi-directional methodologies. We are primarily interested in comparing two recently proposed approaches, adaptive integration and single-ensemble path sampling, to more established methodologies. As test cases, we study relative solvation free energies, of large changes to the size or charge of a Lennard-Jones particle in explicit water. The results show that, for the systems used in this study, both adaptive integration and path sampling offer unique advantages over the more traditional approaches. Specifically, adaptive integration is found to provide very precise long-simulation $ΔF$ estimates as compared to other methods used in this report, while also offering rapid estimation of $ΔF$. The results demonstrate that the adaptive integration approach is the best overall method for the systems studied here. The single-ensemble path sampling approach is found to be superior to ordinary Jarzynski averaging for the uni-directional, ``fast-growth'' non-equilibrium case. Closer examination of the path sampling approach on a two-dimensional system suggests it may be the overall method of choice when conformational sampling barriers are high. However, it appears that the free energy landscapes for the systems used in this study have rather modest configurational sampling barriers.

physics.bio-ph↗

arXiv2006

Simple estimation of absolute free energies for biomolecules

One reason that free energy difference calculations are notoriously difficult in molecular systems is due to insufficient conformational overlap, or similarity, between the two states or systems of interest. The degree of overlap is irrelevant, however, if the absolute free energy of each state can be computed. We present a method for calculating the absolute free energy that employs a simple construction of an exactly computable reference system which possesses high overlap with the state of interest. The approach requires only a physical ensemble of conformations generated via simulation, and an auxiliary calculation of approximately equal central-processing-unit (CPU) cost. Moreover, the calculations can converge to the correct free energy value even when the physical ensemble is incomplete or improperly distributed. As a "proof of principle," we use the approach to correctly predict free energies for test systems where the absolute values can be calculated exactly, and also to predict the conformational equilibrium for leucine dipeptide in implicit solvent.

physics.bio-ph↗

arXiv2005

Resolution exchange simulation

We extend replica exchange simulation in two ways, and apply our approaches to biomolecules. The first generalization permits exchange simulation between models of differing resolution -- i.e., between detailed and coarse-grained models. Such ``resolution exchange'' can be applied to molecular systems or spin systems. The second extension is to ``pseudo-exchange'' simulations, which require little CPU usage for most levels of the exchange ladder and also substantially reduces the need for overlap between levels. Pseudo exchanges can be used in either replica or resolution exchange simulations. We perform efficient, converged simulations of a 50-atom peptide to illustrate the new approaches.

q-bio.BM↗

arXiv2004

Peptide Conformational Equilibria Computed via a Single-Stage Shifting Protocol

We study the conformational equilibria of two peptides using a novel statistical mechanics approach designed for calculating free energy differences between highly dis-similar conformational states. Our results elucidate the contrasting roles of entropy in implicitly solvated leucine dipeptide and decaglycine. The method extends earlier work by Voter, and overcomes the notorious "overlap" problem in free energy computations by constructing a mathematically equivalent calculation with high conformational similarity. The approach requires only equilibrium simulations of the two states of interest, without the need for sampling transition states. We discuss extensions of the approach to binding affinity estimation and explicitly solvated systems, as well as possible optimizations.

physics.bio-ph↗

arXiv2004

Single-ensemble nonequilibrium path-sampling estimates of free energy differences

We introduce a straightforward, single-ensemble, path sampling approach to calculate free energy differences based on Jarzynski's relation. For a two-dimensional ``toy'' test system, the new (minimally optimized) method performs roughly one hundred times faster than either optimized ``traditional'' Jarzynski calculations or conventional thermodynamic integration. The simplicity of the underlying formalism suggests the approach will find broad applicability in molecular systems.

physics.comp-ph↗

arXiv2004

Efficient use of non-equilibrium measurement to estimate free energy differences for molecular systems

A promising method for calculating free energy differences Delta F is to generate non-equilibrium data via ``fast-growth'' simulations or experiments -- and then use Jarzynski's equality. However, a difficulty with using Jarzynski's equality is that Delta F estimates converge very slowly and unreliably due to the nonlinear nature of the calculation -- thus requiring large, costly data sets. Here, we present new analyses of non-equilibrium data from various simulated molecular systems exploiting statistical properties of Jarzynski's equality. Using a fully automated procedure, with no user-input parameters, our results suggest that good estimates of Delta F can be obtained using 6-15 fold less data than was previously possible. Systematizing and extending previous work [1], the new results exploit the systematic behavior of bias due to finite sample size. A key innovation is better use of the more statistically reliable information available from the raw data.

physics.comp-ph↗

arXiv2003

Scaling Behavior of Field-Induced Aggregates in Ferrofluids

An ordered hexagonal array of aggregates can form in thin ferrofluid layers when an external magnetic field is applied. Using the Helmholtz free energy for this system, we calculate the optimum spacing for these aggregates. Results show excellent agreement with experimental findings as a function of field strength and layer thickness. Our analysis yields a crossover in the exponent for the scaling behavior of the aggregate spacing as a function of plate separation, in agreement with experiment. For the first time, we report a similar crossover in the scaling behavior of the aggregate spacing as a function of the magnetic field. The mechanisms responsible for both crossovers are introduced and discussed.

cond-mat.soft↗