Extracting information on folding from the amino acid sequence: consensus regions with preferred conformation in homologous proteins.

It is investigated whether protein segments predicted to have a well-defined conformational preference in the absence of tertiary interactions are conserved in families of homologous proteins. The prediction method follows the procedures of Rooman, M., Kocher, J.-P., and Wodak, S. (preceding paper in this issue). It uses a knowledge-based force field that incorporates only local interactions along the sequence and identifies segments whose lowest energy structure displays a sizable energy gap relative to other computed conformations. In 13 of the protein families and subfamilies considered that are sufficiently homologous to have similar 3D structures, at least one region is consistently predicted as having the same preferred conformation in virtually all family members. These regions are between 4 and 26 residues long. They are often located at chain ends and correspond primarily to segments of secondary structure heavily involved in interactions with the rest of the protein, suggesting that they could act as nuclei around which other parts of the structure would assemble. Experimental data on early folding intermediates or on protein fragments with appreciable structure in aqueous solution are available for more than half of the protein families. Comparison of our results with these data is quite favorable. They reveal that each of the experimentally identified early formed, or independently stable, substructures harbors at least one of the segments consistently predicted as having a preferred conformation by our procedure. The implications of our findings for the conservation of folding pathways in homologous proteins are discussed.     

Prediction of protein folding from amino acid sequence over discrete conformation spaces

Predicting the three-dimensional structure of a protein given only its amino acid sequence is a long-standing goal in computational chemistry. In the thermodynamic approach, one needs a potential function of conformation that resembles the free energy of the real protein to the extent that the global minimum of the potential is attained by the native conformation and no other. In practice, this has never been achieved with certainty because even with greatly simplified representations of the polypeptide chain, there are an astronomical number of local minima to examine. If one chooses instead a protein representation with only a large but manageable number of discrete conformations, then the global preference of the potential for the native can be directly verified. Representing a protein as a walk on a two-dimensional square lattice makes it easy to see that simple functions of the interresidue contacts are sufficient to globally favor a given "native" conformation, as long as it is a compact, globular structure. Explicit representation of the solvent is not required. Another more realistic way to confine the conformational search to a finite set is to draw alternative conformations from fragments of larger proteins having known crystal structure. Then it is possible to construct a simple function of interresidue contacts in three dimensions such that only 8 proteins are required to determine the adjustable parameters, and the native conformations of 37 other proteins are correctly preferred over all alternative conformations. The deduced function favors short-range backbone-backbone contacts regardless of residue type and long-range hydrophobic associations. Interactions over long distances, such as electrostatics, are not required.     

Structure-templated predictions of novel protein interactions from sequence information

The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.     

Swfoldrate: Predicting protein folding rates from amino acid sequence with sliding window method

Protein folding is the process by which a protein processes from its denatured state to its specific biologically active conformation. Understanding the relationship between sequences and the folding rates of proteins remains an important challenge. Most previous methods of predicting protein folding rate require the tertiary structure of a protein as an input. In this study, the long‐range and short‐range contact in protein were used to derive extended version of the pseudo amino acid composition based on sliding window method. This method is capable of predicting the protein folding rates just from the amino acid sequence without the aid of any structural class information. We systematically studied the contributions of individual features to folding rate prediction. The optimal feature selection procedures are adopted by means of combining the forward feature selection and sequential backward selection method. Using the jackknife cross validation test, the method was demonstrated on the large dataset. The predictor was achieved on the basis of multitudinous physicochemical features and statistical features from protein using nonlinear support vector machine (SVM) regression model, the method obtained an excellent agreement between predicted and experimentally observed folding rates of proteins. The correlation coefficient is 0.9313 and the standard error is 2.2692. The prediction server is freely available at http://www.jci‐bioinfo.cn/swfrate/input.jsp . Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Combining the GOR V algorithm with evolutionary information for protein secondary structure prediction from amino acid sequence

We have modified and improved the GOR algorithm for the protein secondary structure prediction by using the evolutionary information provided by multiple sequence alignments, adding triplet statistics, and optimizing various parameters. We have expanded the database used to include the 513 non-redundant domains collected recently by Cuff and Barton (Proteins 1999;34:508-519; Proteins 2000;40:502-511). We have introduced a variable size window that allowed us to include sequences as short as 20-30 residues. A significant improvement over the previous versions of GOR algorithm was obtained by combining the PSI-BLAST multiple sequence alignments with the GOR method. The new algorithm will form the basis for the future GOR V release on an online prediction server. The average accuracy of the prediction of secondary structure with multiple sequence alignment and full jack-knife procedure was 73.5%. The accuracy of the prediction increases to 74.2% by limiting the prediction to 375 (of 513) sequences having at least 50 PSI-BLAST alignments. The average accuracy of the prediction of the new improved program without using multiple sequence alignments was 67.5%. This is approximately a 3% improvement over the preceding GOR IV algorithm (Garnier J, Gibrat JF, Robson B. Methods Enzymol 1996;266:540-553; Kloczkowski A, Ting K-L, Jernigan RL, Garnier J. Polymer 2002;43:441-449). We have discussed alternatives to the segment overlap (Sov) coefficient proposed by Zemla et al. (Proteins 1999;34:220-223).     

Correspondence of homologies in amino acid sequence and tertiary structure of protein molecules

According to the method developed previously (Kubota, Y., Takahashi, S., Nishikawa, K. and Ooi, T. (1981) J. Theor, Biol. 91, 347-361), homology among proteins may be estimated quantitatively. We extended the method to investigate the relationship of an amino acid sequence to its teritary structure and identify homologous segments which have homologous native conformations in proteins. First, we selected proper indices for the computation of correlation coefficients from 32 properties inherent to amino acids, such as hydrophobicity. The arithmetic average of correlation coefficients using six indices gave rise to a good correlation for the CD- and EF-hand regions (Ca2+ binding sites) in carp parvalbumin, but poor ones for other segments. We then applied the method to homologous proteins, the three-dimensional structures of which are known: horse hemoglobin alpha-chain and beta-chain; cytochrome c and c2; serine proteases, chymotrypsinogen and elastase; alpha-lytic protease and protease A from prokaryotic organisms. The results show that the sequence homology estimated by the present method has a good correspondence to the homology in three-dimensional structures and therefore the method is promising for the identification of important sites in sequences which have similar native conformations. For an example of the application of the method, two sequences of human interferon, one from fibroblast and the other from leukocyte, are compared, suggesting functional sites in the molecule.     

Hierarchy of regions of amino acid sequence with respect to their role in the protein spatial structure.

The method of the representation of amino acid sequence by graph of the interactions energy between parts of spatial structure has been elaborated. Our method provides the possibility to establish the compatibility between each point of a polypeptide chain and the Van der Waals interactions energy of regions of a native globule adjacent to this amino acid residue. We have undertaken an exhaustive analysis of a set of proteins. Boundaries of domain and module structures have been found. Nonequivalence of different parts of sequences in respect to their contribution to stabilization of the spatial structure of the protein macromolecules has been revealed. On the basis of the number of energetic levels which are necessary to identify all independent parts of the globule, the contribution from each part of the sequence to stabilization of the spatial structure of the globule is defined. Thus, it has been found that the sequence of amino acid residues coincides with the sequence of the numerical values which can be used in turn in formal procedures, such as an alignment, a search of consensus, the recognition of composition peculiarities, etc. An example of the comparison of proteins with various sequence identities is considered to demonstrate the scheme of an alignment procedure.     

Specific interactions for ab initio folding of protein terminal regions with secondary structures

Proteins fold into unique three-dimensional structures by specific, orientation-dependent interactions between amino acid residues. Here, we extract orientation-dependent interactions from protein structures by treating each polar atom as a dipole with a direction. The resulting statistical energy function successfully refolds 13 out of 16 fully unfolded secondary-structure terminal regions of 10-23 amino acid residues in 15 small proteins. Dissecting the orientation-dependent energy function reveals that the orientation preference between hydrogen-bonded atoms is not enough to account for the structural specificity of proteins. The result has significant implications on the theoretical and experimental searches for specific interactions involved in protein folding and molecular recognition between proteins and other biologically active molecules.     

Monte Carlo simulation studies on the prediction of protein folding types from amino acid composition.

In the methodology development for statistical prediction of protein structures, the founders of different methods usually selected different sets of proteins to test their predicted results. Therefore, it is hard to make a fair comparison according to the results they reported. Even if the predictions by different methods are performed for the same set of proteins, there is still such a problem: a method better that the other for one set of proteins would not necessarily remain so when applied to another set of proteins. To tackle this problem, a Monte Carlo simulation method is proposed to establish an objective criterion to measure the accuracy of prediction for the protein folding type. Such an objective accuracy is actually corresponding to the asymptotical limit genereated during the Monte Carlo simulation process. Based on that, it has been found that the average objective accuracy for predicting the all-alpha, all-beta, alpha + beta, and alpha/beta proteins by the least Euclid's distance method (Nakashima, H., K. Nishikawa, and T. Ooi. 1986. J. Biochem. 99:152-162) is 73.0% and that by the least Minkowski's distance method (Chou, P.Y. 1989. Prediction in Protein Structure and the Principles of Protein Conformation. Plenum Press. New York. 549-586) is 70.9%, indicating that the former is better than the latter. However, according to the original reports, the latter claimed a rate of correct prediction with 79.7% but the former with only 70.2%, leading to a completely opposite conclusion. This indicates the necessity of establishing an objective criterion, and a comparison is meaningful only when it is based on the objective criterion. The simulation method and the idea developed here also can be applied to examine any other statistical prediction methods.     

Studies on protein folding, unfolding and fluctuations by computer simulation. I. The effect of specific amino acid sequence represented by specific inter-unit interactions.

A lattice model of proteins is introduced. "A protein molecule" is a chain of nown-intersecting units of a given length on the two-dimensional square lattice. The copolymeric character of protein molecules is incorporated into the model in the form of specificities of inter-unit interactions. This model proved most effective for studying the statistical mechanical characteristics of protein folding, unfolding and fluctuations. The specificities of inter-unit interactions are shown to be the primary factors responsible for the all-or-none type transition from native to denatured states of globular proteins. The model has been studied by the Monte Carlo method of Metropolis et al., which is now shown applied to approximately simulating a kinetic process. In the strong limit of the specificity of the inter-unit interaction the native conformation was reached in this method by starting from an extended conformation. The possible generalization and application of this method for finding the native conformation of proteins form their amino sequence are discussed.     

The preferred conformation of the tripeptide Ala-Phe-Ala in water is an inverse gamma-turn: implications for protein folding and drug design

Recent studies have provided evidence that peptides as short as tripeptides do adopt preferred conformations. Here we report that the tripeptide Ala-Phe-Ala (AFA) in aqueous solution preferentially forms an inverse gamma-turn. Circular dichroism (CD) indicated the presence of a predominant turn structure, and Fourier transform infrared (FTIR) bands suggested the presence of a gamma-turn forming a bifurcated H-bond with the solvent molecules. The high-resolution structure was obtained by a combined use of NMR spectroscopy and calculations. On the basis of 30 unambiguous ROESY-derived distance restraints (including the Halpha-NH NOE between Ala(1) and Ala(3) and a hydrogen bond between the CO group of Ala(1) and the NH group of Ala(3)), calculations clearly demonstrated the presence of an inverse gamma-turn centered on Phe(2). From NOE data, we estimated a mole fraction for the gamma-turn of 0.65. Since for AFA an extended beta-strand was also reported [Eker, F., Griebenow, K., Cao, X., Nafie, L. A., and Schweitzer-Stenner, R. (2004) Proc. Natl. Acad. Sci. U.S.A. 101, 10054-10059], we investigated the possibility that gamma-turn and beta-strand may represent two major conformations. By using a best-fit procedure that calculated experimental NOEs as weighted averages of the effects originating from both structures, we were able to calculate with good accuracy the backbone NOEs at 280 K in terms of the two limiting conformers, yielding a mole fraction for the gamma-turn and beta-strand conformations of 0.60 and 0.40, respectively, in good agreement with those found by NOE data. The implication of the existence of a preferred conformation by a small structural element is discussed in the context of the nucleation of protein folding events and the design of small peptide and peptidomimetic drugs.     

Prediction of protein structural class from the amino acid sequence

The multidimensional statistical technique of discriminant analysis is used to allocate amino acid sequences to one of four secondary structural classes: high α content, high β content, mixed α and β, low content of ordered structure. Discrimination is based on four attributes: estimates of percentages of α and β structures, and regular variations in the hydrophobic values of residues along the sequence, occurring with periods of 2 and 3.6 residues. The reliability of the method, estimated by classifying 138 sequences from the Brookhaven Protein Data Bank, is 80%, with no misallocations between α-rich and β-rich classes. The reliability can be increased to 84% by making no allocation for proteins classified with odds close to 1. Classification using previously developed secondary structural prediction methods is considerably less reliable, the best result being 64% obtained using predictions based on the Delphi method.     

Modelling charge interactions in the prion protein: predictions for pathogenesis.

Calculations are presented for the pH-dependence of stability and membrane charge complementarity of prion protein fragments. The theoretical results are compared with reported characterisations of prion protein folding in vitro. Discussion of models for conformational change and pathogenesis in vivo leads to the prediction of amino acids that could mediate sensitivity to the endosomal pH and to a design strategy for recombinant prion proteins with an increased susceptibility to prion proteinSc-like properties in vitro. In this model, the protective effect of certain basic polymorphisms can be interpreted in terms of oligomerisation on a negatively-charged surface.     

Putative amino acid sequence of chick calcium-binding protein deduced from a complementary DNA sequence.

Two DNA fragments coding for chick CaBP have been isolated and sequenced. cDNA was prepared from enriched intestinal mRNA and cloned in pUC12. The recombinant clones were screened by differential hybridisation with 32P-cDNA probes synthesized from vitamin D replete and deficient chick intestinal mRNA. Two clones had outstanding affinity with the +D probe. Hybrid-arrested and hybrid-selected translation systems showed that both clones hybridised to mRNA coding for immunoprecipitable CaBP. The mRNA for CaBP has a 100 bp G,C rich sequence before a 786 bp coding region followed by 1250 nucleotides 3' untranslated region. Nucleotides coding for the Ca-binding sites show a high degree of homology for Ca-binding sites in chick calmodulin and rat intestinal CaBP. The amino acid sequence specified by the longest open reading frame contains five Ca-binding sites but is too large for the native CaBP; post-translational modification must therefore occur.     

Monte Carlo simulation studies on the prediction of protein folding types from amino acid composition

A number of methods to predicting the folding type of a protein based on its amino acid composition have been developed during the past few years. In order to perform an objective and fair comparison of different prediction methods, a Monte Carlo simulation method was proposed to calculate the asymptotic limit of the prediction accuracy [Zhang and Chou (1992),Biophys. J. 63, 1523–1529, referred to as simulation method I]. However, simulation method I was based on an oversimplified assumption, i.e., there are no correlations between the compositions of different amino acids. By taking into account such correlations, a new method, referred to as simulation method II, has been proposed to recalculate the objective accuracy of prediction for the least Euclidean distance method [Nakashimaet al. (1986),J. Biochem. 99, 152–162] and the least Minkowski distance method [Chou (1989),Prediction in Protein Structure and the Principles of Protein Conformation, Plenum Press, New York, pp. 549–586], respectively. The results show that the prediction accuracy of the former is still better than that of the latter, as found by simulation method I; however, after incorporating the correlative effect, the objective prediction accuracies become lower for both methods. The reason for this phenomenon is discussed in detail. The simulation method and the idea developed in this paper can be applied to examine any other statistical prediction method, including the computersimulated neural network method.     

The complete amino acid sequence of the human erythrocyte membrane anion-transport protein deduced from the cDNA sequence.

1. We have isolated cDNA clones corresponding to the red cell membrane anion-transport protein (Band 3). 2. The cDNA clones cover 3475 bases of the mRNA and contain the entire protein-coding region, 150 bases of the 5' untranslated region and part of the 3' non-coding region, but do not extend to the 3' end of the mRNA. 3. The translated protein sequence predicts that the human red cell anion transporter contains 911 amino acids. 4. The availability of the amino acid sequence allows the interpretation of some of the many studies on the chemical and proteolytic modification of the human protein aimed at examining the structure and mechanism of this membrane transport protein.