Building proteins from C alpha coordinates using the dihedral probability grid Monte Carlo method.

Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better.     

Prediction of polyelectrolyte polypeptide structures using Monte Carlo conformational search methods with implicit solvation modeling.

Many interesting proteins possess defined sequence stretches containing negatively charged amino acids. At present, experimental methods (X-ray crystallography, NMR) have failed to provide structural data for many of these sequence domains. We have applied the dihedral probability grid-Monte Carlo (DPG-MC) conformational search algorithm to a series of N- and C-capped polyelectrolyte peptides, (Glu)20, (Asp)20, (PSer)20, and (PSer-Asp)10, that represent polyanionic regions in a number of important proteins, such as parathymosin, calsequestrin, the sodium channel protein, and the acidic biomineralization proteins. The atomic charges were estimated from charge equilibration and the valence and van der Waals parameters are from DREIDING. Solvation of the carboxylate and phosphate groups was treated using sodium counterions for each charged side chain (one Na+ for COO-; two Na for CO(PO3)-2) plus a distance-dependent (shielded) dielectric constant, epsilon = epsilon 0 R, to simulate solvent water. The structures of these polyelectrolyte polypeptides were obtained by the DPG-MC conformational search with epsilon 0 = 10, followed by calculation of solvation energies for the lowest energy conformers using the protein dipole-Langevin dipole method of Warshel. These calculations predict a correlation between amino acid sequence and global folded conformational minima: 1. Poly-L-Glu20, our structural benchmark, exhibited a preference for right-handed alpha-helix (47% helicity), which approximates experimental observations of 55-60% helicity in solution. 2. For Asp- and PSer-containing sequences, all conformers exhibited a low preference for right-handed alpha-helix formation (< or = 10%), but a significant percentage (approximately 20% or greater) of beta-strand and beta-turn dihedrals were found in all three sequence cases: (1) Aspn forms supercoil conformers, with a 2:1:1 ratio of beta-turn:beta-strand:alpha-helix dihedral angles; (2) PSer20 features a nearly 1:1 ratio of beta-turn:beta-sheet dihedral preferences, with very little preference for alpha-helical structure, and possesses short regions of strand and turn combinations that give rise to a collapsed bend or hairpin structure; (3) (PSer-Asp)10 features a 3:2:1 ratio of beta-sheet:beta-turn:alpha-helix and gives rise to a superturn or C-shaped structure.     

CRANKITE: A fast polypeptide backbone conformation sampler

Background

CRANKITE is a suite of programs for simulating backbone conformations of polypeptides and proteins. The core of the suite is an efficient Metropolis Monte Carlo sampler of backbone conformations in continuous three-dimensional space in atomic details.

Methods

In contrast to other programs relying on local Metropolis moves in the space of dihedral angles, our sampler utilizes local crankshaft rotations of rigid peptide bonds in Cartesian space.

Results

The sampler allows fast simulation and analysis of secondary structure formation and conformational changes for proteins of average length.     

The influence of helix morphology on co-operative polyamide backbone conformational flexibility in peptide nucleic acid complexes.

A systematic analysis of peptide nucleic acid (PNA) complexes deposited in the Protein Data Bank has been carried out using a set of contiguous atom torsion angle definitions. The analysis is complemented by molecular mechanics adiabatic potential energy calculations on hybrid PNA-nucleic acid model systems. Hitherto unobserved correlations in the values of the (alpha and epsilon) dihedral angles flanking the backbone secondary amide bond are found. This dihedral coupling forms the basis of a PNA backbone conformation classification scheme. Six conformations are thus characterised in experimental structures. Helix morphology is found to exert a significant influence on backbone conformation and flexibility: Watson-Crick PNA strands in complexes with DNA and RNA, that possess A-like base-pair stacking, adopt backbone conformations distinct from those in PNA.DNA-PNA triplex and PNA-PNA duplex P-helix forms. Solvation effects on Watson-Crick PNA backbone conformation in heterotriplexes are discussed and the possible involvement of inter-conformational transitions and dihedral angle uncoupling in asymmetric heteroduplex base-pair breathing is suggested.     

Efficient search on energy minima for structure prediction of nucleic acid motifs

Structure prediction of non-canonical motifs such as mismatches, extra unmatched nucleotides or internal and hairpin loop structures in nucleic acids is of great importance for understanding the function and design of nucleic acid structures. Systematic conformational analysis of such motifs typically involves the generation of many possible combinations of backbone dihedral torsion angles for a given motif and subsequent energy minimization (EM) and evaluation. Such approach is limited due to the number of dihedral angle combinations that grows very rapidly with the size of the motif. Two conformational search approaches have been developed that allow both an effective crossing of barriers during conformational searches and the computational demand grows much less with system size then search methods that explore all combinations of backbone dihedral torsion angles. In the first search protocol single torsion angles are flipped into favorable states using constraint EM and subsequent relaxation without constraints. The approach is repeated in an iterative manner along the backbone of the structural motif until no further energy improvement is obtained. In case of two test systems, a DNA-trinucleotide loop (sequence: GCA) and a RNA tetraloop (sequence: UUCG), the approach successfully identified low energy states close to experiment for two out of five start structures. In the second method randomly selected combinations of up to six backbone torsion angles are simultaneously flipped into preset ranges by a short constraint EM followed by unconstraint EM and acceptance according to a Metropolis acceptance criterion. This combined stochastic/EM search was even more effective than the single torsion flip approach and selected low energy states for the two test cases in between two and four cases out of five start structures.     

Strategy for supplementing structure calculations using limited data with hydrophobic distance restraints

Introductory biochemistry texts often note that the fold of a protein is completely defined when the dihedral angles phi and psi are known for each amino acid. This assertion was examined with torsion angle dynamics and simulated annealing (TAD/SA) calculations of protein G using only dihedral angle restraints. When all dihedral angles were restrained to within 1 degrees of the values of the X-ray structure, the TAD/SA structures gave a backbone root mean square deviation to the target of 4 A. Factors that contributed to divergence from the correct solution include deviations of peptide bonds from planarity, internal conflicts resulting from the nonuniform energies of different phi, psi combinations, and relaxation to extended conformations in the absence of long-range constraints. Simulations including hydrogen-bond restraints showed that even a few long-range contacts constrain the fold better than a complete set of accurate dihedral restraints. A procedure is described for TAD/SA calculations using hydrogen-bond restraints, idealized dihedral restraints for residues in regular secondary structures, and "hydrophobic distance restraints" derived from the positions of hydrophobic residues in the amino acid sequence. The hydrogen-bond restraints are treated as inviolable, whereas violated hydrophobic restraints are removed following reduction of restraint upper bounds from 2 to 1 times the predicted radius of gyration. The strategy was tested with simulated restraints from X-ray structures of proteins from different fold classes and NMR data for cold shock protein A that included only backbone chemical shifts and hydrogen bonds obtained from a long-range HNCO experiment.     

Free energy landscapes of peptides by enhanced conformational sampling

The free energy landscapes of peptide conformations in water have been observed by the enhanced conformational sampling method, applying the selectively enhanced multicanonical molecular dynamics simulations. The conformations of the peptide dimers, -Gly-Gly-, -Gly-Ala-, -Gly-Ser-, -Ala-Gly-, -Asn-Gly-, -Pro-Gly-, -Pro-Ala-, and -Ala-Ala-, which were all blocked with N-terminal acetyl and C-terminal N-methyl groups, were individually sampled with the explicit TIP3P water molecules. From each simulation trajectory, we obtained the canonical ensemble at 300 K, from which the individual three-dimensional landscape was drawn by the potential of mean force using the three reaction coordinates: the backbone dihedral angle, psi, of the first amino acid, the backbone dihedral angle, phi, of the second amino acid, and the distance between the carbonyl oxygen of the N-terminal acetyl group and the C-terminal amide proton. The most stable state and several meta-stable states correspond to extended conformations and typical beta-turn conformations, and their free energy values were accounted for from the potentials of mean force at the states. In addition, the contributions from the intra-molecular energies of peptides and those from the hydration effects were analyzed. Consequently, the stable beta-turn conformations in the free energy landscape were consistent with the empirically preferred beta-turn types for each amino acid sequence. The thermodynamic values for the hydration effect were decomposed and they correlated well with the empirical values estimated from the solvent accessible surface area of each molecular conformation during the trajectories. The origin of the architecture of protein local fragments was analyzed from the viewpoint of the free energy and its decomposed factors.     

Local propensities and statistical potentials of backbone dihedral angles in proteins

The following three issues concerning the backbone dihedral angles of protein structures are presented. (1) How do the dihedral angles of the 20 amino acids depend on the identity and conformation of their nearest residues? (2) To what extent are the native dihedral angles determined by local (dihedral) potentials? (3) How to build a knowledge-based potential for a residue's dihedral angles, considering the identity and conformation of its nearest residues? We find that the dihedral angle distribution for a residue can significantly depend on the identity and conformation of its adjacent residues. These correlations are in sharp contrast to the Flory isolated-pair hypothesis. Statistical potentials are built for all combinations of residue triplets and depend on the dihedral angles between consecutive residues. First, a low-resolution potential is obtained, which only differentiates between the main populated basins in the dihedral angle density plots. Minimization of the dihedral potential for 125 test proteins reveals that most native alpha-helical residues (89%) and a large fraction of native beta-sheet residues (47%) adopt conformations close to their native one. For native loop residues, the percentage is 48%. It is also found that this fraction is higher for residues away from the ends of alpha or beta secondary structure elements. In addition, a higher resolution potential is built as a function of dihedral angles by a smoothing procedure and continuous functions interpolations. Monte Carlo energy minimization with this potential results in a lower fraction for native beta-sheet residues. Nevertheless, because of the higher flexibility and entropy of beta structures, they could be preferred under the influence of non-local interactions. In general, most alpha-helices and many beta-sheets are strongly determined by the local potential, while the conformations in loops and near the end of beta-sheets are more influenced by non-local interactions.     

Efficient Search on Energy Minima for Structure Prediction of Nucleic Acid Motifs

Abstract

Structure prediction of non-canonical motifs such as mismatches, extra unmatched nucleotides or internal and hairpin loop structures in nucleic acids is of great importance for understanding the function and design of nucleic acid structures. Systematic conformational analysis of such motifs typically involves the generation of many possible combinations of backbone dihedral torsion angles for a given motif and subsequent energy minimization (EM) and evaluation. Such approach is limited due to the number of dihedral angle combinations that grows very rapidly with the size of the motif. Two conformational search approaches have been developed that allow both an effective crossing of barriers during con-formational searches and the computational demand grows much less with system size then search methods that explore all combinations of backbone dihedral torsion angles. In the first search protocol single torsion angles are flipped into favorable states using constraint EM and subsequent relaxation without constraints. The approach is repeated in an iterative manner along the backbone of the structural motif until no further energy improvement is obtained. In case of two test systems, a DNA-trinucleotide loop (sequence: GCA) and a RNA tetraloop (sequence: UUCG), the approach successfully identified low energy states close to experiment for two out of five start structures. In the second method randomly selected combinations of up to six backbone torsion angles are simultaneously flipped into preset ranges by a short constraint EM followed by unconstraint EM and acceptance according to a Metropolis acceptance criterion. This combined stochastic/EM search was even more effective than the single torsion flip approach and selected low energy states for the two test cases in between two and four cases out of five start structures.     

Monte Carlo calculations on the conformations of models for the glycopeptide linkage of glycoproteins

In order to search for probable conformations of the peptide, the amino acid side chain, and the carbohydrate linkage in glycoproteins, conformational energy surfaces of glycopeptide model compounds were studied by Monte Carlo methods using the Metropolis algorithm. The potential energies were composed of empirical energy functions which include nonbonded interactions, electrostatics, hydrogen bonding, and torsional energies specified by parameters which have been used for peptides. Calculations were performed on 1-N-acetyl-2-acetamido-beta-D-glucopyranosyl amine and the glycosylated dipeptide N-acetyl-delta-N-(2-acetamido-beta-D-glucopyranosyl)-L-asparaginyl-N'-methyl amide as models for N-glycosylated peptides and on methyl-2-acetamido-alpha-D-galactopyranoside as well as the glycosylated dipeptides N-acetyl-gamma-O-(2-acetamido-alpha-D-galactopyranosyl)-L-threonyl-N'-methyl amide and its seryl analog as models for O-glycosylated glycoproteins. The probable conformations of these compounds were analyzed by single-angle probability tables and by two-dimensional conformation density maps projected from the Markov chains which contained up to six independently varied conformational dihedral angles. The presence of high barriers to rotation required the use of search strategies which resulted in a rather low acceptance rate for new conformations in the Metropolis algorithm in order to avoid trapping of the Markov chain in local energy minima. This problem contributed to the failure of these calculations to attain complete convergence to the thermodynamic limit for the glycosylated dipeptide models in which six dihedral angles were independently varied. Analysis of the results shows that the conformational space available to the highly crowded axial glycosides of the alpha-O-GalNAc type is much more restricted than that for the N-asparaginyl glycopeptides. The most probable conformation for the O-glycosylated peptides is is a beta-turn while N-glycosylated peptides may be either in a beta-turn or an extended conformation.     

A flexible docking scheme to explore the binding selectivity of PDZ domains

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTA LIGAND , we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density‐95/Dlg/ZO‐1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.     

Monte Carlo loop refinement and virtual screening of the thyroid-stimulating hormone receptor transmembrane domain

Metropolis Monte Carlo (MMC) loop refinement has been performed on the three extracellular loops (ECLs) of rhodopsin and opsin-based homology models of the thyroid-stimulating hormone receptor transmembrane domain, a class A type G protein-coupled receptor. The Monte Carlo sampling technique, employing torsion angles of amino acid side chains and local moves for the six consecutive backbone torsion angles, has previously reproduced the conformation of several loops with known crystal structures with accuracy consistently less than 2?Å. A grid-based potential map, which includes van der Waals, electrostatics, hydrophobic as well as hydrogen-bond potentials for bulk protein environment and the solvation effect, has been used to significantly reduce the computational cost of energy evaluation. A modified sigmoidal distance-dependent dielectric function has been implemented in conjunction with the desolvation and hydrogen-bonding terms. A long high-temperature simulation with 2?kcal/mol repulsion potential resulted in extensive sampling of the conformational space. The slow annealing leading to the low-energy structures predicted secondary structure by the MMC technique. Molecular docking with the reported agonist reproduced the binding site within 1.5?Å. Virtual screening performed on the three lowest structures showed that the ligand-binding mode in the inter-helical region is dependent on the ECL conformations.     

Investigating energy‐based pool structure selection in the structure ensemble modeling with experimental distance constraints: The example from a multidomain protein Pub1

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure‐based and physics‐based atomistic force field with an efficient sampling strategy is adopted to simulate a model di‐domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low‐energy structures and the minimum‐size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small‐angle X‐ray scattering data. It is illustrated that the regularizations of energy and ensemble‐size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high‐energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure‐ensemble optimizations with a topology‐based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates.     

The beta-turn scaffold of tripeptide containing an azaphenylalanine residue

The conformational preferences of azaphenylalanine-containing peptide were investigated using a model compound, Ac-azaPhe-NHMe with ab initio method at the HF/3-21G and HF/6-31G(*) levels, and the seven minimum energy conformations with trans orientation of acetyl group and the 4 minimum energy conformations with cis orientation of acetyl group were found at the HF/6-31G(*) level if their mirror images were not considered. An average backbone dihedral angle of the 11 minimum energy conformations is phi=+/-91 degrees +/-24 degrees , psi =+/-18 degrees +/-10 degrees (or +/-169 degrees +/-8 degrees ), corresponding to the i+2 position of beta-turn (delta(R)) or polyproline II (beta(P)) structure, respectively. The chi(1) angle in the aromatic side chain of azaPhe residue adopts preferentially between +/-60 degrees and +/-130 degrees, which reflect a steric hindrance between the N-terminal carbonyl group or the C-terminal amide group and the aromatic side chain with respect to the configuration of the acetyl group. These conformational preferences of Ac-azaPhe-NHMe predicted theoretically were compared with those of For-Phe-NHMe to characterize the structural role of azaPhe residue. Four tripeptides containing azaPhe residue, Boc-Xaa-azaPhe-Ala-OMe [Xaa=Gly(1), Ala(2), Phe(3), Asn(4)] were designed and synthesized to verify whether the backbone torsion angles of azaPhe reside are still the same as compared with theoretical conformations and how the preceding amino acids of azaPhe residue perturb the beta-turn skeleton in solution. The solution conformations of these tripeptide models containing azaPhe residue were determined in CDCl(3) and DMSO solvents using NMR and molecular modeling techniques. The characteristic NOE patterns, the temperature coefficients of amide protons and small solvent accessibility for the azapeptides 1-4 reveal to adopt the beta-turn structure. The structures of azapeptides containing azaPhe residue from a restrained molecular dynamics simulation indicated that average dihedral angles [(phi(1), psi(1)), (phi(2), psi(2))] of Xaa-azaPhe fragment in azapeptide, Boc-Xaa-azaPhe-Ala-OMe were [(-68 degrees, 135 degrees ), (116 degrees, -1 degrees )], and this implies that the intercalation of an azaPhe residue in tripeptide induces the betaII-turn conformation, and the volume change of a preceding amino acid of azaPhe residue in tripeptides would not perturb seriously the backbone dihedral angle of beta-turn conformation. We believe such information could be critical in designing useful molecules containing azaPhe residue for drug discovery and peptide engineering.     

Modeling mutations in protein structures

We describe an automated method for the modeling of point mutations in protein structures. The protein is represented by all non-hydrogen atoms. The scoring function consists of several types of physical potential energy terms and homology-derived restraints. The optimization method implements a combination of conjugate gradient minimization and molecular dynamics with simulated annealing. The testing set consists of 717 pairs of known protein structures differing by a single mutation. Twelve variations of the scoring function were tested in three different environments of the mutated residue. The best-performing protocol optimizes all the atoms of the mutated residue, with respect to a scoring function that includes molecular mechanics energy terms for bond distances, angles, dihedral angles, peptide bond planarity, and non-bonded atomic contacts represented by Lennard-Jones potential, dihedral angle restraints derived from the aligned homologous structure, and a statistical potential for non-bonded atomic interactions extracted from a large set of known protein structures. The current method compares favorably with other tested approaches, especially when predicting long and flexible side-chains. In addition to the thoroughness of the conformational search, sampled degrees of freedom, and the scoring function type, the accuracy of the method was also evaluated as a function of the flexibility of the mutated side-chain, the relative volume change of the mutated residue, and its residue type. The results suggest that further improvement is likely to be achieved by concentrating on the improvement of the scoring function, in addition to or instead of increasing the variety of sampled conformations.     

Conformational analysis of protein and nucleic acid fragments with the new grid search algorithm FOUND

The new computer algorithm FOUND, which is implemented as an integrated module of the DYANA structure calculation program, is capable of performing systematic local conformation analyses by exhaustive grid searches for arbitrary contiguous fragments of proteins and nucleic acids. It uses torsion angles as the only degrees of freedom to identify all conformations that fulfill the steric and NMR-derived conformational restraints within a contiguous molecular fragment, as defined either by limits on the maximal restraint violations or by the fragment-based DYANA target function value. Sets of mutually dependent torsion angles, for example in ribose rings, are treated as a single degree of freedom. The results of the local conformation analysis include allowed torsion angle ranges and stereospecific assignments for diastereotopic substituents, which are then included in the input of a subsequent structure calculation. FOUND can be used for grid searches comprising up to 13 torsion angles, such as the backbone of a complete -helical turn or dinucleotide fragments in nucleic acids, and yields a significantly higher number of stereospecific assignments than the precursor grid search algorithm HABAS.     

Systematic conformational investigations of peptoids and peptoid-peptide chimeras

Peptoids are originally defined as N-substituted oligoglycine derivatives, and in a broader definition as N-substituted peptides (peptoid-peptide chimeras). Both types were systematically investigated by force field calculations. The Merck MMFF and YASARA2 force fields were shown to be, among others, the most suitable ones for conformational investigations of peptoids with no missing parameterizations, in contrast to AMBER or CHARMM. Ramachandran-like plots were calculated for dipeptoids and chimeras using energy calculations and grid searches by varying the dihedral angels PHI and PSI in steps of 10 degrees for s-cis- and s-trans amide bonds. Barriers as well as low energy conformations are compared to peptide Ramachandran plots, showing that peptoids have both, more barriers due to additional steric interactions as well as access to minimum conformations not accessible by peptides. Low energy conformations of dimers were used as starting conformations of higher oligomers of the peptoids for extensive molecular dynamics simulations over 10 or 20 ns with the YASARA2 force field and an explicit water solvent box to evaluate their potential to form secondary structural elements. Especially peptoids with aminoisobutyric acid-like monomer units were found to form left-handed or polyproline-like helices also known from less common natural peptides. Furthermore, new secondary structures appear feasible based on stable conformations outside the allowed areas of the Ramachandran plot for peptides, but allowed for peptoids.     

Reconstruction of the src-SH3 protein domain transition state ensemble using multiscale molecular dynamics simulations

We use an integrated computational approach to reconstruct accurately the transition state ensemble (TSE) for folding of the src-SH3 protein domain. We first identify putative TSE conformations from free energy surfaces generated by importance sampling molecular dynamics for a fully atomic, solvated model of the src-SH3 protein domain. These putative TSE conformations are then subjected to a folding analysis using a coarse-grained representation of the protein and rapid discrete molecular dynamics simulations. Those conformations that fold to the native conformation with a probability (P(fold)) of approximately 0.5, constitute the true transition state. Approximately 20% of the putative TSE structures were found to have a P(fold) near 0.5, indicating that, although correct TSE conformations are populated at the free energy barrier, there is a critical need to refine this ensemble. Our simulations indicate that the true TSE conformations are compact, with a well-defined central beta sheet, in good agreement with previous experimental and theoretical studies. A structured central beta sheet was found to be present in a number of pre-TSE conformations, however, indicating that this element, although required in the transition state, does not define it uniquely. An additional tight cluster of contacts between highly conserved residues belonging to the diverging turn and second beta-sheet of the protein emerged as being critical elements of the folding nucleus. A number of commonly used order parameters to identify the transition state for folding were investigated, with the number of native Cbeta contacts displaying the most satisfactory correlation with P(fold) values.