Estimates for the potential accuracy required in realistic protein folding simulations and structure recognition experiments

Learning To Fold Proteins Using Energy Landscape Theory

This review is a tutorial for scientists interested in the problem of protein structure prediction, particularly those interested in using coarse-grained molecular dynamics models that are optimized using lessons learned from the energy landscape theory of protein folding. We also present a review of the results of the AMH/AMC/AMW/AWSEM family of coarse-grained molecular dynamics protein folding models to illustrate the points covered in the first part of the article. Accurate coarse-grained structure prediction models can be used to investigate a wide range of conceptual and mechanistic issues outside of protein structure prediction; specifically, the paper concludes by reviewing how AWSEM has in recent years been able to elucidate questions related to the unusual kinetic behavior of artificially designed proteins, multidomain protein misfolding, and the initial stages of protein aggregation.

Native atomic burials, supplemented by physically motivated hydrogen bond constraints, contain sufficient information to determine the tertiary structure of small globular proteins

We investigate the possibility that atomic burials, as measured by their distances from the structural geometrical center, contain sufficient information to determine the tertiary structure of globular proteins. We report Monte Carlo simulated annealing results of all-atom hard-sphere models in continuous space for four small proteins: the all-beta WW-domain 1E0L, the alpha/beta protein-G 1IGD, the all-alpha engrailed homeo-domain 1ENH, and the alpha + beta engineered monomeric form of the Cro protein 1ORC. We used as energy function the sum over all atoms, labeled by i, of |R(i) - R(i) (*)|, where R(i) is the atomic distance from the center of coordinates, or central distance, and R(i) (*) is the "ideal" central distance obtained from the native structure. Hydrogen bonds were taken into consideration by the assignment of two ideal distances for backbone atoms forming hydrogen bonds in the native structure depending on the formation of a geometrically defined bond, independently of bond partner. Lowest energy final conformations turned out to be very similar to the native structure for the four proteins under investigation and a strong correlation was observed between energy and distance root mean square deviation (DRMS) from the native in the case of all-beta 1E0L and alpha/beta 1IGD. For all alpha 1ENH and alpha + beta 1ORC the overall correlation between energy and DRMS among final conformations was not as high because some trajectories resulted in high DRMS but low energy final conformations in which alpha-helices adopted a non-native mutual orientation. Comparison between central distances and actual accessible surface areas corroborated the implicit assumption of correlation between these two quantities. The Z-score obtained with this native-centric potential in the discrimination of native 1ORC from a set of random compact structures confirmed that it contains a much smaller amount of native information when compared to a traditional contact Go potential but indicated that simple sequence-dependent burial potentials still need some improvement in order to attain a similar discriminability. Taken together, our results suggest that central distances, in conjunction to physically motivated hydrogen bond constraints, contain sufficient information to determine the native conformation of these small proteins and that a solution to the folding problem for globular proteins could arise from sufficiently accurate burial predictions from sequence followed by minimization of a burial-dependent energy function.

A physically meaningful method for the comparison of potential energy functions

In the study of the conformational behavior of complex systems, such as proteins, several related statistical measures are commonly used to compare two different potential energy functions. Among them, the Pearson's correlation coefficient r has no units and allows only semiquantitative statements to be made. Those that do have units of energy and whose value may be compared to a physically relevant scale, such as the root-mean-square deviation (RMSD), the mean error of the energies (ER), the standard deviation of the error (SDER) or the mean absolute error (AER), overestimate the distance between potentials. Moreover, their precise statistical meaning is far from clear. In this article, a new measure of the distance between potential energy functions is defined that overcomes the aforementioned difficulties. In addition, its precise physical meaning is discussed, the important issue of its additivity is investigated, and some possible applications are proposed. Finally, two of these applications are illustrated with practical examples: the study of the van der Waals energy, as implemented in CHARMM, in the Trp-Cage protein (PDB code 1L2Y) and the comparison of different levels of the theory in the ab initio study of the Ramachandran map of the model peptide HCO-L-Ala-NH2.

Relevant distance between two different instances of the same potential energy in protein folding

In the context of complex systems and, particularly, of protein folding, a physically meaningful distance is defined which allows to make useful statistical statements about the way in which energy differences are modified when two different instances of the same potential-energy function are used. When the two instances arise from the fact that different algorithms or different approximations are used, the distance herein defined may be used to evaluate the relative accuracy of the two methods. When the difference is due to a change in the free parameters of which the potential depends on, the distance can be used to quantify, in each region of parameter space, the robustness of the modeling to such a change and this, in turn, may be used to assess the significance of a parameters' fit. Both cases are illustrated with a practical example: the study of the Poisson-based solvation energy in the Trp-Cage protein (PDB code 1L2Y).

Thermodynamics of interactions between amino acid side chains: experimental differentiation of aromatic-aromatic, aromatic-aliphatic, and aliphatic-aliphatic side-chain interactions in water

A stationary phase for high-pressure liquid chromatography has been prepared by derivatizing microparticulate silica gel with functionality mimicking the side chain of isoleucine. The chromatographic retentions of a series of hydrophobic and amphiphilic amino acid analytes on this stationary phase (Ile MSP) using an aqueous mobile phase were measured as a function of temperature from 273 K to 323 K. Observed temperature dependencies are consistent with a constant change in heat capacity, DeltaC degrees P, upon binding of the analyte to the stationary phase. The curvatures of plots of retention data versus temperature (related to the magnitude of DeltaC degrees P) are distinctly different for retention of aromatic and aliphatic analytes, with retention of aliphatic analytes Val, Ile, and Leu exhibiting the characteristic signature of the hydrophobic effect, i.e., a large negative DeltaC degrees P upon desolvation from water and a maximum of retention around room temperature. Retention of aromatic analytes (Trp, Phe, and Tyr) involves smaller heat capacity changes and pronounced negative enthalpies of interaction with the stationary phase. Estimates of DeltaC degrees P for the interactions of analyte side chains with the Ile side chain were obtained by fitting the temperature dependence of retention to an expression derived from thermodynamic considerations and chromatographic theory. Similar estimates were made for interactions with the Phe side chain, using previously published data for a phenylalanine mimic stationary phase (Phe MSP) (. Protein Sci. 1:786-795). As with the Ile MSP, the retentions of aliphatic analytes show temperature dependencies markedly different from those of aromatic analytes. Data from both phases indicate that a realistic differentiation can be made between the interactions of various types of amino acid side chains tested (i.e., aliphatic/aliphatic, aliphatic/aromatic, and aromatic/aromatic) by comparison of the corresponding thermodynamic functions for pairwise interactions. The retention of leucine on the Phe MSP and that of phenylalanine on the Ile MSP showed similar DeltaC degrees P values, suggesting that the aromatic-aliphatic interaction is reasonably independent of the residue attached to the stationary phase. This result is consistent with a one-to-one interaction and suggests a simple way to estimate the column-dependent phase factor, making it possible to compare entropies and free energies of interaction obtained using different MSPs. The possibilities for using MSP-derived interaction potentials in folding simulations are discussed.