Extracting information on folding from the amino acid sequence: accurate predictions for protein regions with preferred conformation in the absence of tertiary interactions.

A recently developed procedure to predict backbone structure from the amino acid sequence [Rooman, M., Kocher, J. P., & Wodak, S. (1991) J. Mol. Biol, 221, 961-979] is fine tuned to identify protein segments, of length 5-15 residues, that adopt well-defined conformations in the absence of tertiary interactions. These segments are obtained by requiring that their predicted lowest energy structures have a sizable energy gap relative to other computed conformations. Applying this procedure to 69 proteins of known structure, we find that regions with largest energy gaps--those having highly preferred conformations--are also the most accurately predicted ones. On the basis of previous findings that such regions correlate well with sites that become structured early during folding, our approach provides the means of identifying such sites in proteins without prior knowledge of the tertiary structure. Furthermore, when predictions are performed so as to ignore the influence of residues flanking each segment along the sequence, a situation akin to excising the considered peptide from the rest of the chain, they offer the possibility of identifying protein segments liable to adopt well-defined conformations on their own. The described approach should have useful applications in experimental and theoretical investigations of protein folding and stability, and aid in designing peptide drugs and vaccines.     

Protein structure prediction

Current methods developed for predicting protein structure are reviewed. The most widely used algorithms of Chou and Fasman and Garnier et al for predicting secondary structure are compared to the most recent ones including sequence similarity methods, neural network, pattern recognition or joint prediction methods. The best of these methods correctly predict 63-65% of the residues in the database with cross-validation for 3 conformations, helix, beta strand and coli with a standard deviation of 6-8% per protein. However, when a homologous protein is already in the database, the accuracy of prediction by the similarity peptide method of Levin and Garnier reaches about 90%. Some conclusions can be drawn on the mechanism of protein folding. As all the prediction methods only use the local sequence for prediction (+/- 8 residues maximum) one can infer that 65% of the conformation of a residue is dictated on average by the local sequence, the rest is brought by the folding. The best predicted proteins or peptide segments are those for which the folding has less effect on the conformation. Presently, prediction of tertiary structure is only of practical use when the structure of a homologous protein is already known. Amino acid alignment to define residues of equivalent spatial position is critical for modelling of the protein. We showed for serine proteases that secondary structure prediction can help to define a better alignment. Non-homologous segments of the polypeptide chain, such as loops, libraries of known loops and/or energy minimization with various force fields, are used without yet giving satisfactory solutions. An example of modelling by homology, aided by secondary structure prediction on 2 regulatory proteins, Fnr and FixK is presented.     

Prelude and Fugue, predicting local protein structure, early folding regions and structural weaknesses

Prelude&Fugue are bioinformatics tools aiming at predicting the local 3D structure of a protein from its amino acid sequence in terms of seven backbone torsion angle domains, using database-derived potentials. Prelude(&Fugue) computes all lowest free energy conformations of a protein or protein region, ranked by increasing energy, and possibly satisfying some interresidue distance constraints specified by the user. (Prelude&)Fugue detects sequence regions whose predicted structure is significantly preferred relative to other conformations in the absence of tertiary interactions. These programs can be used for predicting secondary structure, tertiary structure of short peptides, flickering early folding sequences and peptides that adopt a preferred conformation in solution. They can also be used for detecting structural weaknesses, i.e. sequence regions that are not optimal with respect to the tertiary fold. AVAILABILITY: http://babylone.ulb.ac.be/Prelude_and_Fugue.     

Logical analysis of the mechanism of protein folding II. The nucleation process

Regions of secondary structure are predicted, without using information about the conformation of the protein itself, and compared with crystallographic assignments for seven proteins of recently published sequence and conformation (Table 1). It is observed in Table 3 that the prediction of helices is good (78.7% for %cor.ass.3), except for proteins having large antiparallel pleated sheets, and the prediction of β-structure is quite good (51.2% for %cor.ass.3) except for helix-rich proteins.The prediction of secondary structure from sequence, and a survey of all protein structures analysed so far by X-ray crystallography, suggest that nuceleation starts in almost all cases from interactions in the medium range between the regions having helical potential (α-candidate) and β-structural potential (β-candidate), which are very close to each other but separated by at least three hydrophilic or neutral residues in four consecutive residues on the polypeptide chain. Predictability of loops or turns is enhanced to 71.3% (%cor.ass.2) from 64.4% by taking into account the contiguous α-β interactions. Such a medium-range interaction is called here a probable nucleus. There are a lot of nuclei in large proteins such as carboxypeptidase Aα, while there exists at least one in small proteins like the trypsin inhibitor, Moreover, such an interaction could be a transitionary state towards a helix-rich protein, and towards a helix-deficient protein having a large antiparallel pleated sheet β-structure as well.The analysis of the relation between probable nuclei with regard to their mutual spatial proximity strongly suggests that the topological pathway of the polypeptide chain in three-dimensional space might be decided by the long-range interactions between an α-candidate and a β-candidate. An empirical rule is observed that almost all parallel pleated sheets are accompanied by helices in their neighbourhood. An accumulation of chemical facts, such as complementation experiments, combinations of disulphide bonds, etc., seems also to be elucidated by the proposed mechanism of protein folding.     

Amino acid sequence homology applied to the prediction of protein secondary structures, and joint prediction with existing methods

The assumption that homologous segments in different proteins may share a similar conformation is applied to the prediction of secondary structures in proteins. Sequences homologous to a target protein are searched, without allowing any gap, and compared against a number of reference proteins of known three-dimensional structure, and then a conformational state (alpha, beta or coil) for each residue of the protein is predicted by looking at the secondary structure of corresponding homologous segments. This prediction is done in a statistical rather than 'deterministic' way, by assigning the most probable conformation state among homologous data to each residue site of a target protein. A test application for 22 sample proteins yields 60% correctness on the average, a better value in comparison with two other existing methods. Joint prediction combining three methods into one is shown to increase the reliability up to 70%, when only the regions identically predicted with the three methods are taken into account. Application of the present method to 10 proteins of unknown structure is demonstrated.     

TOUCHSTONE II: a new approach to ab initio protein structure prediction

We have developed a new combined approach for ab initio protein structure prediction. The protein conformation is described as a lattice chain connecting C(alpha) atoms, with attached C(beta) atoms and side-chain centers of mass. The model force field includes various short-range and long-range knowledge-based potentials derived from a statistical analysis of the regularities of protein structures. The combination of these energy terms is optimized through the maximization of correlation for 30 x 60,000 decoys between the root mean square deviation (RMSD) to native and energies, as well as the energy gap between native and the decoy ensemble. To accelerate the conformational search, a newly developed parallel hyperbolic sampling algorithm with a composite movement set is used in the Monte Carlo simulation processes. We exploit this strategy to successfully fold 41/100 small proteins (36 approximately 120 residues) with predicted structures having a RMSD from native below 6.5 A in the top five cluster centroids. To fold larger-size proteins as well as to improve the folding yield of small proteins, we incorporate into the basic force field side-chain contact predictions from our threading program PROSPECTOR where homologous proteins were excluded from the data base. With these threading-based restraints, the program can fold 83/125 test proteins (36 approximately 174 residues) with structures having a RMSD to native below 6.5 A in the top five cluster centroids. This shows the significant improvement of folding by using predicted tertiary restraints, especially when the accuracy of side-chain contact prediction is >20%. For native fold selection, we introduce quantities dependent on the cluster density and the combination of energy and free energy, which show a higher discriminative power to select the native structure than the previously used cluster energy or cluster size, and which can be used in native structure identification in blind simulations. These procedures are readily automated and are being implemented on a genomic scale.     

Keeping it in the family: folding studies of related proteins

Investigators have recently turned to studies of protein families to shed light on the mechanism of protein folding. In small proteins for which detailed analysis has been performed, recent studies show that transition-state structure is generally conserved. The number and structures of populated folding intermediates have been found to vary in homologous families of larger (greater than 100-residue) proteins, reflecting a balance of local and global interactions.     

Exploring local and non-local interactions for protein stability by structural motif engineering

In order to probe the relative contribution of local and non-local interactions to the thermodynamic stability of proteins, we have devised an experimental approach based on a combination of motif engineering and sequence shuffling. Candidate chain segments in an immunoglobulin V(L) domain were identified whose conformation is proposed to be dominated by non-local interactions. Locally interacting structural motifs of a different conformation were then constructed as replacements, by introducing motif consensus sequences. We find that all nine replacements we constructed systematically reduce the folding cooperativity. By comparing this destabilising effect with the folding transitions of shuffled sequences for three of these motifs, we estimate the contribution of local, native interactions to the free energy of folding. Our results suggest that local and non-local interactions contribute to stability by an approximately equal amount, but that local interactions stabilise by increasing the resistance to denaturation while non-local interactions increase folding cooperativity. The systematic loss of stability by sequence shuffling in these host-guest experiments suggests that the designed interactions indeed are present in the native state, thus consensus sequence engineering may be a useful tool in structure design, but non-local interactions must be taken into account for global stability engineering. Statistical approaches are powerful tools for engineering protein structure and stability, but an analysis based on local sequence propensities alone does not adequately represent the balance of sequence and context in protein structures.     

Analycys: a database for conservation and conformation of disulphide bonds in homologous protein domains

Disulphide bonds in proteins are known to play diverse roles ranging from folding to structure to function. Thorough knowledge of the conservation status and structural state of the disulphide bonds will help in understanding of the differences in homologous proteins. Here we present a database for the analysis of conservation and conformation of disulphide bonds in SCOP structural families. This database has a wide range of applications including mapping of disulphide bond mutation patterns, identification of disulphide bonds important for folding and stabilization, modeling of protein tertiary structures and in protein engineering. The database can be accessed at: http://bioinformatics.univ-reunion.fr/analycys/.     

Stability Curve Prediction of Homologous Proteins Using Temperature-Dependent Statistical Potentials

The unraveling and control of protein stability at different temperatures is a fundamental problem in biophysics that is substantially far from being quantitatively and accurately solved, as it requires a precise knowledge of the temperature dependence of amino acid interactions. In this paper we attempt to gain insight into the thermal stability of proteins by designing a tool to predict the full stability curve as a function of the temperature for a set of 45 proteins belonging to 11 homologous families, given their sequence and structure, as well as the melting temperature () and the change in heat capacity () of proteins belonging to the same family. Stability curves constitute a fundamental instrument to analyze in detail the thermal stability and its relation to the thermodynamic stability, and to estimate the enthalpic and entropic contributions to the folding free energy. In summary, our approach for predicting the protein stability curves relies on temperature-dependent statistical potentials derived from three datasets of protein structures with targeted thermal stability properties. Using these potentials, the folding free energies () at three different temperatures were computed for each protein. The Gibbs-Helmholtz equation was then used to predict the protein''s stability curve as the curve that best fits these three points. The results are quite encouraging: the standard deviations between the experimental and predicted ''s, ''s and folding free energies at room temperature () are equal to 13 , 1.3 ) and 4.1 , respectively, in cross-validation. The main sources of error and some further improvements and perspectives are briefly discussed.     

Parallel folding pathways in the SH3 domain protein

The transition-state ensemble (TSE) is the set of protein conformations with an equal probability to fold or unfold. Its characterization is crucial for an understanding of the folding process. We determined the TSE of the src-SH3 domain protein by using extensive molecular dynamics simulations of the Go model and computing the folding probability of a generated set of TSE candidate conformations. We found that the TSE possesses a well-defined hydrophobic core with variable enveloping structures resulting from the superposition of three parallel folding pathways. The most preferred pathway agrees with the experimentally determined TSE, while the two least preferred pathways differ significantly. The knowledge of the different pathways allows us to design the interactions between amino acids that guide the protein to fold through the least preferred pathway. This particular design is akin to a circular permutation of the protein. The finding motivates the hypothesis that the different experimentally observed TSEs in homologous proteins and circular permutants may represent potentially available pathways to the wild-type protein.     

Conformational preference functions for predicting helices in membrane proteins

A suite of FORTRAN programs, PREF, is described for calculating preference functions from the data base of known protein structures and for comparing smoothed profiles of sequence-dependent preferences in proteins of unknown structure. Amino acid preferences for a secondary structure are considered as functions of a sequence environment. Sequence environment of amino acid residue in a protein is defined as an average over some physical, chemical, or statistical property of its primary structure neighbors. The frequency distribution of sequence environments in the data base of soluble protein structures is approximately normal for each amino acid type of known secondary conformation. An analytical expression for the dependence of preferences on sequence environment is obtained after each frequency distribution is replaced by corresponding Gaussian function. The preference for the α-helical conformation increases for each amino acid type with the increase of sequence environment of buried solvent-accessible surface areas. We show that a set of preference functions based on buried surface area is useful for predicting folding motifs in α-class proteins and in integral membrane proteins. The prediction accuracy for helical residues is 79% for 5 integral membrane proteins and 74% for 11 α-class soluble proteins. Most residues found in transmembrane segments of membrane proteins with known α-helical structure are predicted to be indeed in the helical conformation because of very high middle helix preferences. Both extramembrane and transmembrane helices in the photosynthetic reaction center M and L subunits are correctly predicted. We point out in the discussion that our method of conformational preference functions can identify what physical properties of the amino acids are important in the formation of particular secondary structure elements. © 1993 John Wiley & Sons, Inc.     

Folding pathway dependence on energetic frustration and interaction heterogeneity for a three-dimensional hydrophobic protein model

Monte Carlo simulations of a hydrophobic protein model of 40 monomers in the cubic lattice are used to explore the effect of energetic frustration and interaction heterogeneity on its folding pathway. The folding pathway is described by the dependence of relevant conformational averages on an appropriate reaction coordinate, pfold, defined as the probability for a given conformation to reach the native structure before unfolding. We compare the energetically frustrated and heterogeneous hydrophobic potential, according to which individual monomers have a higher or lower tendency to form contacts unspecifically depending on their hydrophobicities, to an unfrustrated homogeneous Go-type potential with uniformly attractive native interactions and neutral non-native interactions (called Go1 in this study), and to an unfrustrated heterogeneous potential with neutral non-native interactions and native interactions having the same energy as the hydrophobic potential (called Go2 in this study). Folding kinetics are slowed down dramatically when energetic frustration increases, as expected and previously observed in a two-dimensional model. Contrary to our previous results in two dimensions, however, it appears that the folding pathway and transition state ensemble can be significantly dependent on the energy function used to stabilize the native structure. The sequence of events along the reaction coordinate, or the order along this coordinate in which different regions of the native conformation become structured, turns out to be similar for the hydrophobic and Go2 potentials, but with analogous events tending to occur at lower pfold values in the first case. In particular, the transition state obtained from the ensemble around pfold = 0.5 is more structured for the hydrophobic potential. For Go1, not only the transition state ensemble but the order of events itself is modified, suggesting that interaction heterogeneity, in addition to energetic frustration, can have significant effects on the folding mechanism, most likely by modifying the probability of different contacts in the unfolded state, the starting point for the folding reaction. Although based on a simple model, these results provide interesting insight into how sequence-dependent switching between folding pathways might occur in real proteins.     

Electrostatic contributions to the stability of hyperthermophilic proteins.

Electrostatic contributions to the folding free energy of several hyperthermophilic proteins and their mesophilic homologs are calculated. In all the cases studied, electrostatic interactions are more favorable in the hyperthermophilic proteins. The electrostatic free energy is found not to be correlated with the number of ionizable amino acid residues, ion pairs or ion pair networks in a protein, but rather depends on the location of these groups within the protein structure. Moreover, due to the large free energy cost associated with burying charged groups, buried ion pairs are found to be destabilizing unless they undergo favorable interactions with additional polar groups, including other ion pairs. The latter case involves the formation of stabilizing ion pair networks as is observed in a number of proteins. Ion pairs located on the protein surface also provide stabilizing interactions in a number of cases. Taken together, our results suggest that many hyperthermophilic proteins enhance electrostatic interactions through the optimum placement of charged amino acid residues within the protein structure, although different design strategies are used in different cases. Other physical mechanisms are also likely to contribute, however optimizing electrostatic interactions offers a simple means of enhancing stability without disrupting the core residues characteristic of different protein families.     

Alpha-hairpin stability and folding of transmembrane segments

Molecular Dynamics (MD) simulations at low dielectric constant have been carried out for peptides matching the double spanning segments of transmembrane proteins. Different folding dynamics have been observed. The peptides folded into the stable helix-turn-helix conformation-alpha-hairpin-with antiparallel-oriented strands or unstable alpha-hairpin conformation that unfolded later into the straight helical structure. The peptide having flexible residues in the TM helices often misfolded into a tangled structure that can be avoided by restricting the flexibility of these residues. General conclusions can be drawn from the observed folding dynamics. The stability and folding of some double spanning transmembrane fragments are self-assembling. The following and/or neighboring peptide chains of the protein may support the stability of the hairpin structure of other fragments. The stability of the TM helices containing flexible residues could be maintained due to contacts with neighboring TM segments.     

Suggestions for "safe" residue substitutions in site-directed mutagenesis

The conserved topological structure observed in various molecular families such as globins or cytochromes c allows structural equivalencing of residues in every homologous structure and defines in a coherent way a global alignment in each sequence family. A search was performed for equivalent residue pairs in various topological families that were buried in protein cores or exposed at the protein surface and that had mutated but maintained similar unmutated environments. Amino acid residues with atoms in contact with the mutated residue pairs defined the environment. Matrices of preferred amino acid exchanges were then constructed and preferred or avoided amino acid substitutions deduced. Given the conserved atomic neighborhoods, such natural in vivo substitutions are subject to similar constrains as point mutations performed in site-directed mutagenesis experiments. The exchange matrices should provide guidelines for "safe" amino acid substitutions least likely to disturb the protein structure, either locally or in its overall folding pathway, and most likely to allow probing the structural and functional significance of the substituted site.     

A segment alignment approach to protein comparison

MOTIVATION: Local structure segments (LSSs) are small structural units shared by unrelated proteins. They are extensively used in protein structure comparison, and predicted LSSs (PLSSs) are used very successfully in ab initio folding simulations. However, predicted or real LSSs are rarely exploited by protein sequence comparison programs that are based on position-by-position alignments. RESULTS: We developed a SEgment Alignment algorithm (SEA) to compare proteins described as a collection of predicted local structure segments (PLSSs), which is equivalent to an unweighted graph (network). Any specific structure, real or predicted corresponds to a specific path in this network. SEA then uses a network matching approach to find two most similar paths in networks representing two proteins. SEA explores the uncertainty and diversity of predicted local structure information to search for a globally optimal solution. It simultaneously solves two related problems: the alignment of two proteins and the local structure prediction for each of them. On a benchmark of protein pairs with low sequence similarity, we show that application of the SEA algorithm improves alignment quality as compared to FFAS profile-profile alignment, and in some cases SEA alignments can match the structural alignments, a feat previously impossible for any sequence based alignment methods.     

Studies on protein folding, unfolding and fluctuations by computer simulation. IV. Hydrophobic interactions.

The theoretical model of proteins on the two-dimensional square lattice, introduced previously, is extended to include the hydrophobic interactions. Two proteins, whose native conformations have different folded patterns, are studied. Units in the protein chains are classified into polar units and nonpolar units. If there is a vacant lattice point next to a nonpolar unit, it is interpreted as being occupied by solvent water and the entropy of the system is assumed to decrease by a certain amount. Besides these hydrophobic free energies, the specific long-range interactions studied in previous papers are assumed to be operative in a protein chain. Equilibrium properties of the folding and unfolding transitions of the two proteins are found to be similar, even though one of them was predicted, based on the one globule model of the transitions, to unfold through a significant intermediate state (or at least to show a tendency toward such a behavior), when the hydrophobic interactions are strongly weighted. The failure of this prediction led to the development of a more refined model of transitions; a non-interacting local structure model. The hydrophobic interactions assumed here have a character of non-specific long-range interactions. Because of this character the hydrophobic interactions have the effect of decelerating the folding kinetics. The deceleration effect is less pronounced in one of the two proteins, whose native conformation is stabilized by many pairs of medium-range interactions. It is therefore inferred that the medium-range interactions have the power to cope with the decelerating effect of the non-specific hydrophobic interactions.     

Identification and ab initio simulations of early folding units in proteins

The location of protein subunits that form early during folding, constituted of consecutive secondary structure elements with some intrinsic stability and favorable tertiary interactions, is predicted using a combination of threading algorithms and local structure prediction methods. Two folding units are selected among the candidates identified in a database of known protein structures: the fragment 15-55 of 434 cro, an all-alpha protein, and the fragment 1-35 of ubiquitin, an alpha/beta protein. These units are further analyzed by means of Monte Carlo simulated annealing using several database-derived potentials describing different types of interactions. Our results suggest that the local interactions along the chain dominate in the first folding steps of both fragments, and that the formation of some of the secondary structures necessarily occurs before structure compaction. These findings led us to define a prediction protocol, which is efficient to improve the accuracy of the predicted structures. It involves a first simulation with a local interaction potential only, whose final conformation is used as a starting structure of a second simulation that uses a combination of local interaction and distance potentials. The root mean square deviations between the coordinates of predicted and native structures are as low as 2-4 A in most trials. The possibility of extending this protocol to the prediction of full proteins is discussed. Proteins 2001;42:164-176.