Antonio Rey

A method for predicting protein structure from sequence

BACKGROUND The ability to predict the native conformation of a globular protein from its amino-acid sequence is an important unsolved problem of molecular biology. We have previously reported a method in which reduced representations of proteins are folded on a lattice by Monte Carlo simulation, using statistically-derived potentials. When applied to sequences designed to fold into four-helix bundles, this method generated predicted conformations closely resembling the real ones. RESULTS We now report a hierarchical approach to protein-structure prediction, in which two cycles of the above-mentioned lattice method (the second on a finer lattice) are followed by a full-atom molecular dynamics simulation. The end product of the simulations is thus a full-atom representation of the predicted structure. The application of this procedure to the 60 residue, B domain of staphylococcal protein A predicts a three-helix bundle with a backbone root mean square (rms) deviation of 2.25-3 A from the experimentally determined structure. Further application to a designed, 120 residue monomeric protein, mROP, based on the dimeric ROP protein of Escherichia coli, predicts a left turning, four-helix bundle native state. Although the ultimate assessment of the quality of this prediction awaits the experimental determination of the mROP structure, a comparison of this structure with the set of equivalent residues in the ROP dime- crystal structure indicates that they have a rms deviation of approximately 3.6-4.2 A. CONCLUSION Thus, for a set of helical proteins that have simple native topologies, the native folds of the proteins can be predicted with reasonable accuracy from their sequences alone. Our approach suggest a direction for future work addressing the protein-folding problem.

Thermodynamics of Gō-type models for protein folding

Go-type potentials, based on the inter-residue contacts present in the native structure of a protein, are frequently used to predict dynamic and structural features of the folding pathways through computer simulations. However, the mathematical form used to define the model interactions includes several arbitrary choices, whose consequences are not usually analyzed. In this work, we use a simple off-lattice protein model and a parallel tempering Monte Carlo simulation technique to carry out such analysis, centered in the thermodynamic characteristics of the folding transition. We show how the definition of a native contact has a deep impact on the presence of simple or complex transitions, with or without thermodynamic intermediates. In addition, we have checked that the width of the attractive wells has a profound effect on the free-energy barrier between the folded and unfolded states, mainly through its influence on the entropy of the denatured state.

Influence of the native topology on the folding barrier for small proteins

The possibility of downhill instead of two-state folding for proteins has been a very controversial topic which arose from recent experimental studies. From the theoretical side, this question has also been accomplished in different ways. Given the experimental observation that a relationship exists between the native structure topology of a protein and the kinetic and thermodynamic properties of its folding process, Gō-type potentials are an appropriate way to approach this problem. In this work, we employ an interaction potential from this family to get a better insight on the topological characteristics of the native state that may somehow determine the presence of a thermodynamic barrier in the folding pathway. The results presented here show that, indeed, the native topology of a small protein has a great influence on its folding behavior, mostly depending on the proportion of local and long range contacts the protein has in its native structure. Furthermore, when all the interactions present contribute in a balanced way, the transition results to be cooperative. Otherwise, the tendency to a downhill folding behavior increases.

The shape of linear and star polymers with and without excluded volume

The shape of isolated linear and star polymers, with and without excluded volume, has been determined by Monte Carlo simulations using a pivot algorithm. Stars with 3, 4, 5, and 6 arms are studied. The high efficiency of the pivot algorithm has allowed us to obtain accurate data for long chains. Good agreement is found with existing analytical expressions for nonexcluded volume chains and with other computer simulations for excluded volume chains.

Investigation of the end-to-end vector distribution function for linear polymers in different regimes

Monte Carlo simulations employing the pivot algorithm are used to generate off‐lattice three‐dimensional linear polymers in three regimes: nonexcluded volume, theta, and excluded volume. The end‐to‐end vector distribution function is calculated from the resulting configurations. It is found that the shape of the distribution function is Gaussian for nonexcluded volume chains, nearly Gaussian for theta chains, and that the scaling form derived by des Cloizeaux fits the data for excluded volume chains well.

Effect of double bonds on the dynamics of hydrocarbon chains

Brownian dynamics simulations of isolated 18‐carbon chains have been performed, both for saturated and unsaturated hydrocarbons. The effect of one or several (nonconjugated) double bonds on the properties of the chains is discussed in terms of both equilibrium and dynamic properties. The introduction of a cis double bond increases the relaxation rates of the unsaturated chain with respect to the saturated alkane. On the other hand, coupling effects in the torsional transitions around a trans double bond make the dynamics of this unsaturated chain very similar to the saturated one. Based on these results, the parameters and moves of a dynamic Monte Carlo algorithm are tuned to reproduce the observed behavior, providing an efficient method for the study of more complicated systems.

Brownian dynamics simulation of flexible polymer chains with excluded volume and hydrodynamic interactions. A comparison with Monte Carlo and theoretical results

Abstract The generation of Brownian dynamics trajectories for a flexible polymer constituted of statistical Gaussian units with intramolecular long-range (excluded volume) interactions is accomplished. The intramolecular interactions are described by relatively soft repulsive forces derived from an exponentially decaying potential with a cut-off distance. The validity of this method is satisfactorily tested through the comparison of a wide set of numerical results for equilibrium properties (different averaged dimensions and internal distances, and the end-to-end distance distribution factor) with Monte Carlo results from a model that includes the customary hard-spheres representation of excluded volume forces. Furthermore, the numerical values obtained in this study for the different properties are shown to agree with the scaling theories or Renormalization Group predictions. A transport property, the translational diffusion coefficient, is also obtained and included in the numerical analysis.

Brownian dynamics of a flexible polymer. Internal modes and quaiselastic scattering function

Brownian Dynamics trajectories have been simulated by means of the Ermak and McCammon algorithm for Gaussian polymer chains of different lengths with hydrodynamic interactions. The results for relaxation times and dynamic scattering functions of chains with 2–20 statistical units are close to those calculated from the preaveraged Rouse–Zimm theory. The differences between both sets of results are slightly higher than the range of uncertainties of the simulation values (about 5% in most typical cases). Moreover, the simulated scattering functions have been fitted to sums of exponentials in order to extract translational diffusion coefficients and first relaxation times, following the Pecora procedure. The values obtained this way are in satisfactory agreement with the results directly calculated from the trajectories.

A refined hydrogen bond potential for flexible protein models

One of the major disadvantages of coarse-grained hydrogen bond potentials, for their use in protein folding simulations, is the appearance of abnormal structures when these potentials are used in flexible chain models, and no other geometrical restrictions or energetic contributions are defined into the system. We have efficiently overcome this problem, for chains of adequate size in a relevant temperature range, with a refined coarse-grained hydrogen bond potential. With it, we have been able to obtain nativelike alpha-helices and beta-sheets in peptidic systems, and successfully reproduced the competition between the populations of these secondary structure elements by the effect of temperature and concentration changes. In this manuscript we detail the design of the interaction potential and thoroughly examine its applicability in energetic and structural terms, considering factors such as chain length, concentration, and temperature.

Simple model for the simulation of peptide folding and aggregation with different sequences

We present a coarse-grained interaction potential that, using just one single interaction bead per amino acid and only realistic interactions, can reproduce the most representative features of peptide folding. We combine a simple hydrogen bond potential, recently developed in our group, with a reduced alphabet for the amino acid sequence, which takes into account hydrophobic interactions. The sequence does not pose any additional influence in the torsional properties of the chain, as it often appears in previously published work. Our model is studied in equilibrium simulations at different temperatures and concentrations. At low concentrations the effect of hydrophobic interactions is determinant, as α-helices (isolated or in bundles) or β-sheets are the most populated conformations, depending on the simulated sequence. On the other hand, an increase in concentration translates into a higher influence of the hydrogen bond interactions, which mostly favor the formation of β-type aggregates, in agreement with experimental observations. These aggregates, however, still keep some distinct characteristics for different sequences.