Powerful simulated-annealing algorithm locates global minimum of protein-folding potentials from multiple starting conformations

Protein-folding potentials, designed with the explicit goal that the global energy minimum correspond to crystallographically observed conformations of protein molecules, may offer great promise toward calculating native protein structures. Achieving this promise, however, depends on finding an effective means of dealing with the multiple-minimum problem inherent in such potentials. In this study, a protein-folding-potential test system has been developed that exhibits the properties of general protein-folding potentials yet has a unique well-defined global energy minimum corresponding to the crystallographically determined conformation of the test molecule. A simulated-annealing algorithm is developed that locates the global minimum of this potential in four of eight test runs from random starting conformations. Exploration of the energy-conformation surface of the potential indicates that it contains the numerous local minima typical of protein-folding potentials and that the global minimum is not easily located by conventional minimization procedures. When the annealing algorithm is applied to a previously developed actual folding potential to analyze the conformation of avian pancreatic polypeptide, a new conformer is located that is lower in energy than any conformer located in previous studies using a variety of minimization techniques.     

Molecular simulation of surfactant-assisted protein refolding

Protein refolding to its native state in vitro is a challenging problem in biotechnology, i.e., in the biomedical, pharmaceutical, and food industry. Protein aggregation and misfolding usually inhibit the recovery of proteins with their native states. These problems can be partially solved by adding a surfactant into a suitable solution environment. However, the process of this surfactant-assisted protein refolding is not well understood. In this paper, we wish to report on the first-ever simulations of surfactant-assisted protein refolding. For these studies, we defined a simple model for the protein and the surfactant and investigated how a surfactant affected the folding behavior of a two-dimensional lattice protein molecule. The model protein and model surfactant were chosen such that we could capture the important features of the folding process and the interaction between the protein and the surfactant, namely, the hydrophobic interaction. It was shown that, in the absence of surfactants, a protein in an "energy trap" conformation, i.e., a local energy minima, could not fold into the native form, which was characterized by a global energy minimum. The addition of surfactants created folding pathways via the formation of protein-surfactant complexes and thus enabled the conformations that fell into energy trap states to escape from these traps and to form the native proteins. The simulation results also showed that it was necessary to match the hydrophobicity of surfactant to the concentration of denaturant, which was added to control the folding or unfolding of a protein. The surfactants with different hydrophobicity had their own concentration range on assisting protein refolding. All of these simulations agreed well with experimental results reported elsewhere, indicating both the validity of the simulations presented here and the potential application of the simulations for the design of a surfactant on assisting protein refolding.     

Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition

Quantifying the density of conformations over phase space (the conformational distribution) is needed to model important macromolecular processes such as protein folding. In this work, we quantify the conformational distribution for a simple polypeptide (N-mer polyalanine) using the cumulative distribution function (CDF), which gives the probability that two randomly selected conformations are separated by less than a "conformational" distance and whose inverse gives conformation counts as a function of conformational radius. An important finding is that the conformation counts obtained by the CDF inverse depend critically on the assignment of a conformation's distance span and the ensemble (e.g., unfolded state model): varying ensemble and conformation definition (1 --> 2 A) varies the CDF-based conformation counts for Ala(50) from 10(11) to 10(69). In particular, relatively short molecular dynamics (MD) relaxation of Ala(50)'s random-walk ensemble reduces the number of conformers from 10(55) to 10(14) (using a 1 A root-mean-square-deviation radius conformation definition) pointing to potential disconnections in comparing the results from simplified models of unfolded proteins with those from all-atom MD simulations. Explicit waters are found to roughen the landscape considerably. Under some common conformation definitions, the results herein provide (i) an upper limit to the number of accessible conformations that compose unfolded states of proteins, (ii) the optimal clustering radius/conformation radius for counting conformations for a given energy and solvent model, (iii) a means of comparing various studies, and (iv) an assessment of the applicability of random search in protein folding.     

A robust force field based method for calculating conformational energies of charged drug-like molecules

The binding affinity of a drug-like molecule depends among other things on the availability of the bioactive conformation. If the bioactive conformation has a significantly higher energy than the global minimum energy conformation, then the molecule is unlikely to bind to its target. Determination of the global minimum energy conformation and calculation of conformational penalties of binding is a prerequisite for prediction of reliable binding affinities. Here, we present a simple and computationally efficient procedure to estimate the global energy minimum for a wide variety of structurally diverse molecules, including polar and charged compounds. Identifying global energy minimum conformations of such compounds with force field methods is problematic due to the exaggeration of intramolecular electrostatic interactions. We demonstrate that the global energy minimum conformations of zwitterionic compounds generated by conformational analysis with modified electrostatics are good approximations of the conformational distributions predicted by experimental data and with molecular dynamics performed in explicit solvent. Finally the method is used to calculate conformational penalties for zwitterionic GluA2 agonists and to filter false positives from a docking study.     

The protein folding transition state: insights from kinetics and thermodynamics

We perform extensive lattice Monte Carlo simulations of protein folding to construct and compare the equilibrium and the kinetic transition state ensembles of a model protein that folds to the native state with two-state kinetics. The kinetic definition of the transition state is based on the folding probability analysis method, and therefore on the selection of conformations with 0.4相似文献   

Computer simulations of the refolding of sperm whale apomyoglobin from high-temperature denaturated state

The refolding mechanism of apomyoglobin (apoMb) subsequent to high-temperature unfolding has been examined using computer simulations with atomic level detail. The folding of this protein has been extensively studied experimentally, providing a large database of folding parameters which can be probed using simulations. In the present study, 4-folding trajectories of apoMb were computed starting from coiled structures. A crystal structure of sperm whale myoglobin taken from the Protein Data Bank was used to construct the final native conformation by removal of the heme group followed by energy optimization. The initial unfolded conformations were obtained from high-temperature molecular dynamics simulations. Room-temperature refolding trajectories at neutral pH were obtained using the stochastic difference equation in length algorithm. The folding trajectories were compared with experimental results and two previous molecular dynamics studies at low pH. In contrast to the previous simulations, an extended intermediate with large helical content was not observed. In the present study, a structural collapse occurs without formation of helices or native contacts. Once the protein structure is more compact (radius of gyration<18 A) secondary and tertiary structures appear. These results suggest that apoMb follows a different folding pathway after high-temperature denaturation.     

Constrained proper sampling of conformations of transition state ensemble of protein folding

Characterizing the conformations of protein in the transition state ensemble (TSE) is important for studying protein folding. A promising approach pioneered by Vendruscolo et al. [Nature (London) 409, 641 (2001)] to study TSE is to generate conformations that satisfy all constraints imposed by the experimentally measured φ values that provide information about the native likeness of the transition states. Fai?sca et al. [J. Chem. Phys. 129, 095108 (2008)] generated conformations of TSE based on the criterion that, starting from a TS conformation, the probabilities of folding and unfolding are about equal through Markov Chain Monte Carlo (MCMC) simulations. In this study, we use the technique of constrained sequential Monte Carlo method [Lin et al., J. Chem. Phys. 129, 094101 (2008); Zhang et al. Proteins 66, 61 (2007)] to generate TSE conformations of acylphosphatase of 98 residues that satisfy the φ-value constraints, as well as the criterion that each conformation has a folding probability of 0.5 by Monte Carlo simulations. We adopt a two stage process and first generate 5000 contact maps satisfying the φ-value constraints. Each contact map is then used to generate 1000 properly weighted conformations. After clustering similar conformations, we obtain a set of properly weighted samples of 4185 candidate clusters. Representative conformation of each of these cluster is then selected and 50 runs of Markov chain Monte Carlo (MCMC) simulation are carried using a regrowth move set. We then select a subset of 1501 conformations that have equal probabilities to fold and to unfold as the set of TSE. These 1501 samples characterize well the distribution of transition state ensemble conformations of acylphosphatase. Compared with previous studies, our approach can access much wider conformational space and can objectively generate conformations that satisfy the φ-value constraints and the criterion of 0.5 folding probability without bias. In contrast to previous studies, our results show that transition state conformations are very diverse and are far from nativelike when measured in cartesian root-mean-square deviation (cRMSD): the average cRMSD between TSE conformations and the native structure is 9.4 A? for this short protein, instead of 6 A? reported in previous studies. In addition, we found that the average fraction of native contacts in the TSE is 0.37, with enrichment in native-like β-sheets and a shortage of long range contacts, suggesting such contacts form at a later stage of folding. We further calculate the first passage time of folding of TSE conformations through calculation of physical time associated with the regrowth moves in MCMC simulation through mapping such moves to a Markovian state model, whose transition time was obtained by Langevin dynamics simulations. Our results indicate that despite the large structural diversity of the TSE, they are characterized by similar folding time. Our approach is general and can be used to study TSE in other macromolecules.     

Combined vibrational,conformational energy and electron diffraction studies of trans-2-decalone

The structure of trans-2-decalone was investigated by combined gas phase electron diffraction, conformational energy and vibrational analyses. In this study first the minimum energy conformations for trans-2-decalone were calculated by molecular mechanics techniques using a force field described in the literature; the same field and the minimum energy conformations were then used in subsequent vibrational analyses to calculate the mean amplitudes of vibration for each minimum energy conformation of trans-2-decalone; these mean amplitudes and the corresponding internuclear distances were then used to calculate theoretical electron diffraction radial distribution curves which were compared to the experimental curves. Four conformational energy minima were investigated with one or both rings in a chair or non-chair form. The results of the combined investigations indicate that the molecule exists in the conformation which has both rings in a distorted chair form.     

Toward absolute density of states calculations for proteins

The density of states (DOS), which gives the number of conformations with a particular energy E, is a prerequisite in computing most thermodynamic quantities and in elucidating important biological processes such as the mechanism of protein folding. However, current methods for computing DOS of large systems such as proteins generally yield only the ratios of microstate counts for different energies, which could yield absolute conformation counts if the total number of conformations in phase space is known, thus motivating this work. Here, the total number of energy minima of 50-mer polyalanine, whose size corresponds to naturally occurring small proteins, was estimated under an all-atom potential energy function based on the cumulative distribution function (CDF) of conformational differences to be approximately 10(38). This estimate can place any DOS function, such as the Gaussian DOS distribution in the random energy model, on an absolute scale. Comparing the absolute conformational counts from a Gaussian DOS function with those from the CDF derived from quenched molecular dynamics ensembles shows that the former are far greater than the latter, indicating far fewer low-energy minima actually exist. In addition to showing how CDF and relative DOS calculations can yield absolute DOS for a discrete system, we also show how they can yield absolute DOS for continuous variable systems to a specified atomic variance. In the context of protein folding, knowing this phase-space "volume" of conformations in a DOS function, as well as characteristic transition times, constrains the set of possible folding mechanisms.     

Quantum mechanical calculations of tryptophan and comparison with conformations in native proteins

We report a detailed analysis of the potential energy surface of N-acetyl-l-tryptophan-N-methylamide, (NATMA) both in the gas phase and in solution. The minima are identified using the density-functional-theory (DFT) with the 6-31g(d) basis set. The full potential energy surface in terms of torsional angles is spanned starting from various initial configurations. We were able to locate 77 distinct L-minima. The calculated energy maps correspond to the intrinsic conformational propensities of the individual NATMA molecule. We show that these conformations are essentially similar to the conformations of tryptophan in native proteins. For this reason, we compare the results of DFT calculations in the gas and solution phases with native state conformations of tryptophan obtained from a protein library. In native proteins, tryptophan conformations have strong preferences for the beta sheet, right-handed helix, tight turn, and bridge structures. The conformations calculated by DFT, the solution-phase results in particular, for the single tryptophan residue are in agreement with native state values obtained from the Protein Data Bank.     

Predictive in silico all-atom folding of a four-helix protein with a free-energy model

We report the predictive all-atom folding of the 60 amino acid four-helix bacterial ribosomal protein (BRP) L20 with a stochastic evolutionary optimization method in a free-energy force field. The energetically best, as well as six of the 10 lowest conformations, converge to a near-native structure. All of the 10 best energy conformations share the secondary structure elements of the native conformation, but differ in their tertiary alignment. The best conformation has a backbone root-mean-square deviation of 4.6 A to the native conformation and reproduces most distance constraints of the NMR experiment to 1.5 A resolution. Starting from random initial conditions, the native content of the simulated population increases more than 60-fold in the course of the simulation. These data demonstrate the feasibility of predictive unbiased all-atom protein folding with present day computational resources for the BRP L20.     

Mesoscopic dynamic Monte Carlo simulations of the adsorption of proteinlike HP chains within laterally constricted spaces

Two-dimensional dynamic Monte Carlo simulations are applied to the protein-like HP chain model to investigate the influence of lateral confinement of the adsorbed chain on adsorption thermodynamics and the ensemble of accessible chain conformations. The structure of the model makes it possible to enumerate all possible chain conformations and thereby define with precision the relation between adsorption thermodynamics and changes in accessible chain conformations resulting from the adsorption process. Lateral confinement of the adsorbed chain is shown to dramatically reduce the number of accessible energy states and unique chain conformations such that, under certain conditions, adsorption is predicted to actually stabilize the chain against denaturation. Lateral confinement preferentially eliminates expanded conformations of the adsorbed chain, shifting the equilibrium from the unfolded state toward the native state. As a result, the conformational entropy of the adsorbed chain is predicted to be lower than that of the chain free in solution. The protein-like HP chain responds to an increase in the hydrophobicity of the sorbent surface by strongly favoring those conformations that minimize the overall internal energy of the system. As a result, adsorption severely destabilizes the native-state conformation. The ability of our simulation results to provide insights into underlying mechanisms for nonspecific protein adsorption is illustrated through qualitative comparison with activity data for hen egg-white lysozyme adsorbed on silica at different surface concentrations.     

Conformational elasticity theory of chain molecules

This paper develops a conformational elasticity theory of chain molecules, which is based on three key points: (i) the molecular model is the rotational isomeric state (RIS) model; (ii) the conformational distribution function of a chain molecule is described by a function of two variables, the end-to-end distance of a chain conformation and the energy of the conformation; (iii) the rule of changes in the chain conformational states during deformation is that a number of chain conformations would vanish. The ideal deformation behavior calculated by the theory shows that the change in chain conformations is physically able to make the upward curvature of the stress-strain curve at the large-scale deformation of natural rubber. With the theory, different deformation behaviors between polymers with different chemical structures can be described, the energy term of the stress in the deformations can be predicted, and for natural rubber the fraction of the energy term is around 13%, coinciding with the experi     

A minimal proteinlike lattice model: an alpha-helix motif

A simple protein model of a four-helix bundle motif on a face-centered cubic lattice has been studied. Total energy of a conformation includes attractive interactions between hydrophobic residues, repulsive interactions between hydrophobic and polar residues, and a potential that favors helical turns. Using replica exchange Monte Carlo simulations we have estimated a set of parameters for which the native structure is a global minimum of conformational energy. Then we have shown that all the above types of interactions are necessary to guarantee the cooperativity of folding transition and to satisfy the thermodynamic hypothesis.     

Selective stabilization of natively folded RNA structure by DNA constraints

Learning how native RNA conformations can be stabilized relative to unfolded states is an important objective, for both understanding natural RNAs and improving the design of artificial functional RNAs. Here we show that covalently attached double-stranded DNA constraints (ca. 14 base pairs in length) can significantly stabilize the native conformation of an RNA molecule. Using the P4-P6 domain of the Tetrahymena group I intron as the test system, we identified pairs of RNA sites where attaching a DNA duplex is predicted to be structurally compatible with only the folded state of the RNA. The DNA-constrained RNAs were synthesized and shown by nondenaturing polyacrylamide gel electrophoresis (native PAGE) to have substantial decreases in their Mg2+ midpoints ([Mg2+]1/2 values). These changes are equivalent to free energy stabilizations as large as DeltaDeltaGdegrees = -2.5 kcal/mol, which is approximately 14% of the total tertiary folding energy. For comparison, the sole modification of P4-P6 previously reported to stabilize this RNA is a single-nucleotide deletion (DeltaC209) that provides only 1.1 kcal/mol of stabilization. Our findings indicate that nature has not completely optimized P4-P6 RNA folding. Furthermore, the DNA constraints are designed not to interact directly and extensively with the RNA, but rather more indirectly to modulate the relative stabilities of folded and unfolded RNA states. The successful implementation of this strategy to further stabilize a natively folded RNA conformation suggests an important element of modularity in stabilization of RNA structure, with implications for how nature might use other molecules such as proteins to stabilize specific RNA conformations.     

Independence of photoproduct formation on DNA conformation.

Abstract— In an ethanolic solution native T7 DNA can undergo conformational transitions from the B conformation (0% ethanol) to the C-like (60% w/w ethanol) and the A (80% w/w ethanol) conformations. We have investigated the formation of three classes of thymine-derived photoproducts in T7 DNA irradiated (280 nm) in the B, C-like, and A conformations, which were monitored by circular dichroism measurements. We find that the predominant class of thymine-derived photoproducts in any conformational state is cyclobutyl dipyrimidines. While the ‘spore product,’ 5-thyminyl-5,6-dihydrothymine, which belongs to another class of photoproductsf does form in native DNA in the A conformation, its yield in denatured DNA at 80% ethanol is the same as that in native DNA. The yield of pyrimidine adduct, a third photoproduct class, is a maximum at 50–60% ethanol. This effect of ethanol is probably not due to the ethanol-induced C-like conformation, however, since pyrimidine adduct formation is not enhanced when T7 DNA is irradiated in the C conformation in 6 M CsCl or in intact phage. We conclude from these and other data in the literature that the degree of hydration rather than the conformational state is the critical factor in determining which of the photoproducts will form in native DNA.     

Can a physics‐based,all‐atom potential find a protein's native structure among misfolded structures? I. Large scale AMBER benchmarking

Recent work has shown that physics-based, all-atom energy functions (AMBER, CHARMM, OPLS-AA) and local minimization, when used in scoring, are able to discriminate among native and decoy structures. Yet, there have been only few instances reported of the successful use of physics based potentials in the actual refinement of protein models from a starting conformation to one that ends in structures, which are closer to the native state. An energy function that has a global minimum energy in the protein's native state and a good correlation between energy and native-likeness should be able to drive model structures closer to their native structure during a conformational search. Here, the possible reasons for the discrepancy between the scoring and refinement results for the case of AMBER potential are examined. When the conformational search via molecular dynamics is driven by the AMBER potential for a large set of 150 nonhomologous proteins and their associated decoys, often the native minimum does not appear to be the lowest free energy state. Ways of correcting the potential function in order to make it more suitable for protein model refinement are proposed.     

Estimation of protein folding rate from Monte Carlo simulations and entropy capacity

The problem of protein self-organization is one of the most important problems of molecular biology nowadays. Despite the recent success in the understanding of general principles of protein folding, details of this process are yet to be elucidated. Moreover, the prediction of protein folding rates has its own practical value due to the fact that aggregation directly depends on the rate of protein folding. The time of folding has been calculated for 67 proteins with known experimental data at the point of thermodynamic equilibrium between unfolded and native states using a Monte Carlo model where each residue is considered to be either folded as in the native state or completely disordered. The times of folding for 67 proteins which reach the native state within the limit of 10(8) Monte Carlo steps are in a good correlation with the experimentally measured folding rate at the mid-transition point (the correlation coefficient is -0.82). Theoretical consideration of a capillarity model for the process of protein folding demonstrates that the difference in the folding rate for proteins sharing more spherical and less spherical folds is the result of differences in the conformational entropy due to a larger surface of the boundary between folded and unfolded phases in the transition state for proteins with more spherical fold. The capillarity model allows us to predict the folding rate at the same level of correlation as by Monte Carlo simulations. The calculated model entropy capacity (conformational entropy per residue divided by the average contact energy per residue) for 67 proteins correlates by about 78% with the experimentally measured folding rate at the mid-transition point.     

Computation of 3D queries for ROCS based virtual screens

Rapid overlay of chemical structures (ROCS) is a method that aligns molecules based on shape and/or chemical similarity. It is often used in 3D ligand-based virtual screening. Given a query consisting of a single conformation of an active molecule ROCS can generate highly enriched hit lists. Typically the chosen query conformation is a minimum energy structure. Can better enrichment be obtained using conformations other than the minimum energy structure? To answer this question a methodology has been developed called CORAL (COnformational analysis, Rocs ALignment). For a given set of molecule conformations it computes optimized conformations for ROCS screening. It does so by clustering all conformations of a chosen molecule set using pairwise ROCS combo scores. The best representative conformation is that which has the highest average overlap with the rest of the conformations in the cluster. It is these best representative conformations that are then used for virtual screening. CORAL was tested by performing virtual screening experiments with the 40 DUD (Directory of Useful Decoys) data sets. Both CORAL and minimum energy queries were used. The recognition capability of each query was quantified as the area under the ROC curve (AUC). Results show that the CORAL AUC values are on average larger than the minimum energy AUC values. This demonstrates that one can indeed obtain better ROCS enrichments with conformations other than the minimum energy structure. As a result, CORAL analysis can be a valuable first step in virtual screening workflows using ROCS.