Prediction of protein secondary structures from their hydrophobic characteristics

Evolutionary Pattern of Interferon Alpha Genes in Bovidae and Genetic Diversity of IFNAA in the Bovine Genome

Interferons are secretory proteins induced in response to specific extracellular stimuli which stimulate intra- and intercellular networks for regulating innate and acquired immunity, resistance to viral infections, and normal and tumor cell survival and death. Type 1 interferons plays a major role in the CD8 T-cell response to viral infection. The genomic analysis carried out here for type I interferons within Bovidae family shows that cattle, bison, water buffalo, goat, and sheep (all Bovidae), have different number of genes of the different subtypes, with a large increase in the numbers, compared to human and mouse genomes. A phylogenetic analysis of the interferon alpha (IFNA) proteins in this group shows that the genes do not follow the evolutionary pattern of the species, but rather a cycle of duplications and deletions in the different species. In this study we also studied the genetic diversity of the bovine interferon alpha A (IFNAA), as an example of the IFNA genes in cattle, sequencing a fragment of the coding sequence in 18 breeds of cattle from Pakistan, Nigeria and USA. Similarity analysis allowed the allocation of sequences into 22 haplotypes. Bhagnari, Brangus, Sokoto Gudali, and White Fulani, had the highest number of haplotypes, while Angus, Hereford and Nari Master had the least. However, when analyzed by the average haplotype count, Angus, Bhagnari, Hereford, Holstein, Muturu showed the highest values, while Cholistani, Lohani, and Nari Master showed the lowest values. Haplotype 4 was found in the highest number of individuals (74), and in 15 breeds. Sequences for yak, bison, and water buffalo, were included within the bovine haplotypes. Medium Joining network showed that the sequences could be divided into 4 groups: one with highly similar haplotypes containing mostly Asian and African breeds, one with almost all of the Bos taurus American breeds, one mid-diverse group with mostly Asian and African sequences, and one group with highly divergent haplotypes with five N'Dama sequences and one from each of White Fulani, Dhanni, Tharparkar, and Bhagnari. The large genetic diversity found in IFNAA could be a very good indication of the genetic variation among the different genes of IFNA and could be an adaptation for these species in response to viral challenges they face.

IMPContact: An Interhelical Residue Contact Prediction Method

As an important category of proteins, alpha-helix transmembrane proteins (αTMPs) play an important role in various biological activities. Because the solved αTMP structures are inadequate, predicting the residue contacts among the transmembrane segments of an αTMP exhibits the basis of protein fold, which can be used to further discover more protein functions. A few efforts have been devoted to predict the interhelical residue contact using machine learning methods based on the prior knowledge of transmembrane protein structure. However, it is still a challenge to improve the prediction accuracy, while the deep learning method provides an opportunity to utilize the structural knowledge in a different insight. For this purpose, we proposed a novel αTMP residue-residue contact prediction method IMPContact, in which a convolutional neural network (CNN) was applied to recognize those interhelical contacts in a TMP using its specific structural features. There were four sequence-based TMP-specific features selected to descript a pair of residues, namely, evolutionary covariation, predicted topology structure, residue relative position, and evolutionary conservation. An up-to-date dataset was used to train and test the IMPContact; our method achieved better performance compared to peer methods. In the case studies, IHRCs in the regular transmembrane helixes were better predicted than in the irregular ones.

Structural prediction, whole exome sequencing and molecular dynamics simulation confirms p.G118D somatic mutation of PIK3CA as functionally important in breast cancer patients

To understand the structural and functional importance of PIK3CA somatic mutations, whole exome sequencing, molecular dynamics simulation techniques in combination with in silico prediction algorithms such as SIFT, PolyPhen, Provean and CADD were employed. Twenty out of eighty missense somatic mutations in PIK3CA gene were found to be pathogenic by all the four algorithms. Most recurrent mutations found were known hotspot PIK3CA mutations with known clinical significance like p.E545 K, p.E545A, p.E545 G and p.C420R. A missense mutation p.G118D was found to be recurrently mutated in 5 cases. Interestingly, this mutation was observed in one of the patients who underwent whole exome sequencing and was completely absent from the controls. To see the effect of this mutation on the structure of PIK3CA protein, molecular dynamics simulation was performed. By molecular dynamics approach, we have shown that p.G118D mutation deviated from the native structure which was supported by the decrease in the number of hydrogen bonds, difference in hydrogen bond distance and angle, difference in root mean square deviation between the native and the mutant structures.

50 years of amino acid hydrophobicity scales: revisiting the capacity for peptide classification

BACKGROUND

Physicochemical properties are frequently analyzed to characterize protein-sequences of known and unknown function. Especially the hydrophobicity of amino acids is often used for structural prediction or for the detection of membrane associated or embedded β-sheets and α-helices. For this purpose many scales classifying amino acids according to their physicochemical properties have been defined over the past decades. In parallel, several hydrophobicity parameters have been defined for calculation of peptide properties. We analyzed the performance of separating sequence pools using 98 hydrophobicity scales and five different hydrophobicity parameters, namely the overall hydrophobicity, the hydrophobic moment for detection of the α-helical and β-sheet membrane segments, the alternating hydrophobicity and the exact ß-strand score.

RESULTS

Most of the scales are capable of discriminating between transmembrane α-helices and transmembrane β-sheets, but assignment of peptides to pools of soluble peptides of different secondary structures is not achieved at the same quality. The separation capacity as measure of the discrimination between different structural elements is best by using the five different hydrophobicity parameters, but addition of the alternating hydrophobicity does not provide a large benefit. An in silico evolutionary approach shows that scales have limitation in separation capacity with a maximal threshold of 0.6 in general. We observed that scales derived from the evolutionary approach performed best in separating the different peptide pools when values for arginine and tyrosine were largely distinct from the value of glutamate. Finally, the separation of secondary structure pools via hydrophobicity can be supported by specific detectable patterns of four amino acids.

CONCLUSION

It could be assumed that the quality of separation capacity of a certain scale depends on the spacing of the hydrophobicity value of certain amino acids. Irrespective of the wealth of hydrophobicity scales a scale separating all different kinds of secondary structures or between soluble and transmembrane peptides does not exist reflecting that properties other than hydrophobicity affect secondary structure formation as well. Nevertheless, application of hydrophobicity scales allows distinguishing between peptides with transmembrane α-helices and β-sheets. Furthermore, the overall separation capacity score of 0.6 using different hydrophobicity parameters could be assisted by pattern search on the protein sequence level for specific peptides with a length of four amino acids.

Investigating the structural impacts of I64T and P311S mutations in APE1-DNA complex: a molecular dynamics approach

Background

Elucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA.

Principal Findings

In this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T) and rs1803120 (P311S) were taken further for structural analysis.

Significance

Different parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis.

RECOGNITION OF TRANSMEMBRANE SEGMENTS IN PROTEINS: REVIEW AND CONSISTENCY-BASED BENCHMARKING OF INTERNET SERVERS

Membrane proteins perform a number of crucial functions as transporters, receptors, and components of enzyme complexes. Identification of membrane proteins and prediction of their topology is thus an important part of genome annotation. We present here an overview of transmembrane segments in protein sequences, summarize data from large-scale genome studies, and report results of benchmarking of several popular internet servers.

ENSEMBLE VOTING SYSTEM FOR MULTICLASS PROTEIN FOLD RECOGNITION

Protein structure classification is an important issue in understanding the associations between sequence and structure as well as possible functional and evolutionary relationships. Recently structural genomes initiatives and other high-throughput experiments have populated the biological databases at a rapid pace. In this paper, three types of classifiers, k nearest neighbors, class center and nearest neighbor and probabilistic neural networks and their homogenous ensemble for multiclass protein fold recognition problem are evaluated firstly, and then a heterogenous ensemble Voting System is designed for the same problem. The different features and/or their combinations extracted from the protein fold dataset are used in these classification models. The heterogenous classification results are then put into a voting system to get the final result. The experimental results show that the proposed method can improve prediction accuracy by 4%–10% on a benchmark dataset containing 27 SCOP folds.

Bacterial protein structures reveal phylum dependent divergence

Protein sequence space is vast compared to protein fold space. This raises important questions about how structures adapt to evolutionary changes in protein sequences. A growing trend is to regard protein fold space as a continuum rather than a series of discrete structures. From this perspective, homologous protein structures within the same functional classification should reveal a constant rate of structural drift relative to sequence changes. The clusters of orthologous groups (COG) classification system was used to annotate homologous bacterial protein structures in the Protein Data Bank (PDB). The structures and sequences of proteins within each COG were compared against each other to establish their relatedness. As expected, the analysis demonstrates a sharp structural divergence between the bacterial phyla Firmicutes and Proteobacteria. Additionally, each COG had a distinct sequence/structure relationship, indicating that different evolutionary pressures affect the degree of structural divergence. However, our analysis also shows the relative drift rate between sequence identity and structure divergence remains constant.

Eukaryote-wide sequence analysis of mitochondrial β-barrel outer membrane proteins

BACKGROUND

The outer membranes of mitochondria are thought to be homologous to the outer membranes of Gram negative bacteria, which contain 100's of distinct families of β-barrel membrane proteins (BOMPs) often forming channels for transport of nutrients or drugs. However, only four families of mitochondrial BOMPs (MBOMPs) have been confirmed to date. Although estimates as high as 100 have been made in the past, the number of yet undiscovered MBOMPs is an open question. Fortunately, the recent discovery of a membrane integration signal (the β-signal) for MBOMPs gave us an opportunity to look for undiscovered MBOMPs.

RESULTS

We present the results of a comprehensive survey of eukaryotic protein sequences intended to identify new MBOMPs. Our search employs recent results on β-signals as well as structural information and a novel BOMP predictor trained on both bacterial and mitochondrial BOMPs. Our principal finding is circumstantial evidence suggesting that few MBOMPs remain to be discovered, if one assumes that, like known MBOMPs, novel MBOMPs will be monomeric and β-signal dependent. In addition to this, our analysis of MBOMP homologs reveals some exceptions to the current model of the β-signal, but confirms its consistent presence in the C-terminal region of MBOMP proteins. We also report a β-signal independent search for MBOMPs against the yeast and Arabidopsis proteomes. We find no good candidates MBOMPs in yeast but the Arabidopsis results are less conclusive.

CONCLUSIONS

Our results suggest there are no remaining MBOMPs left to discover in yeast; and if one assumes all MBOMPs are β-signal dependent, few MBOMP families remain undiscovered in any sequenced organism.

Application of amino acid occurrence for discriminating different folding types of globular proteins

Background

Predicting the three-dimensional structure of a protein from its amino acid sequence is a long-standing goal in computational/molecular biology. The discrimination of different structural classes and folding types are intermediate steps in protein structure prediction.

Results

In this work, we have proposed a method based on linear discriminant analysis (LDA) for discriminating 30 different folding types of globular proteins using amino acid occurrence. Our method was tested with a non-redundant set of 1612 proteins and it discriminated them with the accuracy of 38%, which is comparable to or better than other methods in the literature. A web server has been developed for discriminating the folding type of a query protein from its amino acid sequence and it is available at http://granular.com/PROLDA/.

Conclusion

Amino acid occurrence has been successfully used to discriminate different folding types of globular proteins. The discrimination accuracy obtained with amino acid occurrence is better than that obtained with amino acid composition and/or amino acid properties. In addition, the method is very fast to obtain the results.

Conformational study of palindromic tripeptides (GPG, IPI and KPK) in HIV-1 protease--a density functional theory study

A comparative study has been carried out on three palindromic tripeptides Gly-Pro-Gly, Ile-Pro-Ile and Lys-Pro-Lys which were present in HIV protein along with their analogues applying density functional computation at B3LYP/6-31G* level of theory. Discrepancy from the structural analysis has been noted for all the systems and it was found to be more for amide capped structure at the C terminal of proline. The puckering amplitude A and Phase angle P of the pyrrolidine ring of proline in the chosen palindromic tripeptides and their analogues were calculated from the endocyclic torsion angles. The minimum energy conformers lying well within the prescribed region of proline were obtained for the derived compounds from potential energy surface scan mentioning that no role has been played by its terminal residues. This is further supported by the simulated amide bands identifying the helical structure for all three palindromic tripeptides signifying the importance of proline. The molecular properties such as stabilization energy, chemical hardness along with dipole moment were calculated and interpreted. The values of Calpha-H(s) and the peptide backbone N-Calpha-CO for all the selected conformers specify the three palindromic tripeptides to have a symmetrical achiral structure.

A generalized analysis of hydrophobic and loop clusters within globular protein sequences

Background

Hydrophobic Cluster Analysis (HCA) is an efficient way to compare highly divergent sequences through the implicit secondary structure information directly derived from hydrophobic clusters. However, its efficiency and application are currently limited by the need of user expertise. In order to help the analysis of HCA plots, we report here the structural preferences of hydrophobic cluster species, which are frequently encountered in globular domains of proteins. These species are characterized only by their hydrophobic/non-hydrophobic dichotomy. This analysis has been extended to loop-forming clusters, using an appropriate loop alphabet.

Results

The structural behavior of hydrophobic cluster species, which are typical of protein globular domains, was investigated within banks of experimental structures, considered at different levels of sequence redundancy. The 294 more frequent hydrophobic cluster species were analyzed with regard to their association with the different secondary structures (frequencies of association with secondary structures and secondary structure propensities). Hydrophobic cluster species are predominantly associated with regular secondary structures, and a large part (60 %) reveals preferences for α-helices or β-strands. Moreover, the analysis of the hydrophobic cluster amino acid composition generally allows for finer prediction of the regular secondary structure associated with the considered cluster within a cluster species. We also investigated the behavior of loop forming clusters, using a "PGDNS" alphabet. These loop clusters do not overlap with hydrophobic clusters and are highly associated with coils. Finally, the structural information contained in the hydrophobic structural words, as deduced from experimental structures, was compared to the PSI-PRED predictions, revealing that β-strands and especially α-helices are generally over-predicted within the limits of typical β and α hydrophobic clusters.

Conclusion

The dictionary of hydrophobic clusters described here can help the HCA user to interpret and compare the HCA plots of globular protein sequences, as well as provides an original fundamental insight into the structural bricks of protein folds. Moreover, the novel loop cluster analysis brings additional information for secondary structure prediction on the whole sequence through a generalized cluster analysis (GCA), and not only on regular secondary structures. Such information lays the foundations for developing a new and original tool for secondary structure prediction.

Amino acid propensities for secondary structures are influenced by the protein structural class

Amino acid propensities for secondary structures were used since the 1970s, when Chou and Fasman evaluated them within datasets of few tens of proteins and developed a method to predict secondary structure of proteins, still in use despite prediction methods having evolved to very different approaches and higher reliability. Propensity for secondary structures represents an intrinsic property of amino acid, and it is used for generating new algorithms and prediction methods, therefore our work has been aimed to investigate what is the best protein dataset to evaluate the amino acid propensities, either larger but not homogeneous or smaller but homogeneous sets, i.e., all-alpha, all-beta, alpha-beta proteins. As a first analysis, we evaluated amino acid propensities for helix, beta-strand, and coil in more than 2000 proteins from the PDBselect dataset. With these propensities, secondary structure predictions performed with a method very similar to that of Chou and Fasman gave us results better than the original one, based on propensities derived from the few tens of X-ray protein structures available in the 1970s. In a refined analysis, we subdivided the PDBselect dataset of proteins in three secondary structural classes, i.e., all-alpha, all-beta, and alpha-beta proteins. For each class, the amino acid propensities for helix, beta-strand, and coil have been calculated and used to predict secondary structure elements for proteins belonging to the same class by using resubstitution and jackknife tests. This second round of predictions further improved the results of the first round. Therefore, amino acid propensities for secondary structures became more reliable depending on the degree of homogeneity of the protein dataset used to evaluate them. Indeed, our results indicate also that all algorithms using propensities for secondary structure can be still improved to obtain better predictive results.

Motifs in outer membrane protein sequences: Applications for discrimination

Discriminating outer membrane proteins (OMPs) from other folding types of globular and membrane proteins is an important problem for predicting their secondary and tertiary structures and detecting outer membrane proteins from genomic sequences as well. In this work, we have systematically analyzed the distribution of amino acid residues in the sequences of globular and outer membrane proteins with several motifs, such as A*B, A**B, etc. We observed that the motifs E*L, A*K and L*E occur frequently in globular proteins while S*S, N*S and R*D predominantly occur in OMPs. We have devised a statistical method based on frequently occurring motifs in globular and OMPs and obtained an accuracy of 96% and 82% for correctly identifying OMPs and excluding globular proteins, respectively. Further, we noticed that the motifs of transmembrane helical (TMH) proteins are different from that of OMPs. While I*A, I*L and L*I prefer in TMH proteins S*S, N*S and N*N predominantly occur in OMPs. The information about the occurrence of A*B motifs in TMH and OMPs could discriminate them with an accuracy of 80% for excluding OMPs and 100% for identifying OMPs. The influence of protein size and structural class for discrimination is discussed.

Application of residue distribution along the sequence for discriminating outer membrane proteins

Discriminating outer membrane proteins from other folding types of globular and membrane proteins is an important problem both for detecting outer membrane proteins from genomic sequences and for the successful prediction of their secondary and tertiary structures. In this work, we have systematically analyzed the distribution of amino acid residues in the sequences of globular and outer membrane proteins. We observed that the occurrence of two neighboring aliphatic and polar residues is significantly higher in outer membrane proteins than in globular proteins. From the information about the dipeptide composition we have devised a statistical method for discriminating outer membrane proteins from other globular and membrane proteins. Our approach correctly picked up the outer membrane proteins with an accuracy of 95% for the training set of 337 proteins. On the other hand, our method has correctly excluded the globular proteins at an accuracy of 79% in a non-redundant dataset of 674 proteins. Furthermore, the present method is able to correctly exclude alpha-helical membrane proteins up to an accuracy of 87%. These accuracy levels are comparable to other methods in the literature. The influence of protein size and structural class for discrimination is discussed.

Relative importance of secondary structure and solvent accessibility to the stability of protein mutants

Understanding the factors influencing the stability of protein mutants is an important task in molecular and computational biology. In this work, we have approached this problem by examining the relative importance of secondary structure and solvent accessibility of the mutant residue for understanding/predicting the stability of protein mutants. We have used hydrophobic, electrostatic and hydrogen bond free energy terms and nine unique physicochemical, energetic and conformational properties of amino acids in the present study and these parameters have been related with changes in thermal stability (DeltaTm) of all the single mutants of lysozymes based on single and multiple correlation coefficients. As expected the properties reflecting hydrophobicity and hydrophobic free energy play a major role to distinguish stabilizing and destabilizing mutants. The hydrophobic free energy due to carbon and nitrogen atoms distinguish the stability of coil and strand mutations to the accuracy of 100 and 90%, respectively. In agreement with previous results, the subgroup classification based on secondary structure and the information about its location in the structure yielded good relationship with the experimental DeltaTm. We revealed that the secondary structure information is equally or more important than solvent accessibility for understanding the stability of protein mutants. The comparison of amino acid properties with free-energy terms indicate that the energetic contribution explains the mutant stability better in coil region whereas the amino acid properties do better in strand region. Further, the combination of free energies with amino acid properties increased the correlation significantly. The present study demonstrates the importance of classifying the mutants based on secondary structure to the stability of proteins upon mutations.

Inter-residue interactions in protein folding and stability

During the process of protein folding, the amino acid residues along the polypeptide chain interact with each other in a cooperative manner to form the stable native structure. The knowledge about inter-residue interactions in protein structures is very helpful to understand the mechanism of protein folding and stability. In this review, we introduce the classification of inter-residue interactions into short, medium and long range based on a simple geometric approach. The features of these interactions in different structural classes of globular and membrane proteins, and in various folds have been delineated. The development of contact potentials and the application of inter-residue contacts for predicting the structural class and secondary structures of globular proteins, solvent accessibility, fold recognition and ab initio tertiary structure prediction have been evaluated. Further, the relationship between inter-residue contacts and protein-folding rates has been highlighted. Moreover, the importance of inter-residue interactions in protein-folding kinetics and for understanding the stability of proteins has been discussed. In essence, the information gained from the studies on inter-residue interactions provides valuable insights for understanding protein folding and de novo protein design.

A simple statistical method for discriminating outer membrane proteins with better accuracy

MOTIVATION

Discriminating outer membrane proteins from other folding types of globular and membrane proteins is an important task both for identifying outer membrane proteins from genomic sequences and for the successful prediction of their secondary and tertiary structures.

RESULTS

We have systematically analyzed the amino acid composition of globular proteins from different structural classes and outer membrane proteins. We found that the residues, Glu, His, Ile, Cys, Gln, Asn and Ser, show a significant difference between globular and outer membrane proteins. Based on this information, we have devised a statistical method for discriminating outer membrane proteins from other globular and membrane proteins. Our approach correctly picked up the outer membrane proteins with an accuracy of 89% for the training set of 337 proteins. On the other hand, our method has correctly excluded the globular proteins at an accuracy of 79% in a non-redundant dataset of 674 proteins. Furthermore, the present method is able to correctly exclude alpha-helical membrane proteins up to an accuracy of 80%. These accuracy levels are comparable to other methods in the literature, and this is a simple method, which could be used for dissecting outer membrane proteins from genomic sequences. The influence of protein size, structural class and specific residues for discrimination is discussed.

Characteristic features of amino acid residues in coiled-coil protein structures

Detailed analyses of protein structures provide an opportunity to understand conformation and function in terms of amino acid sequence and composition. In this work, we have systematically analyzed the characteristic features of the amino acid residues found in alpha-helical coiled-coils and, in so doing, have developed indices for their properties, conformational parameters, surrounding hydrophobicity and flexibility. As expected, there is preference for hydrophobic (Ala, Leu), positive (Lys, Arg) and negatively (Glu) charged residues in coiled-coil domains. However, the surrounding hydrophobicity of residues in coiled-coil domains is significantly less than that for residues in other regions of coiled-coil proteins. The analysis of temperature factors in coiled-coil proteins shows that the residues in these domains are more stable than those in other regions. Further, we have delineated the medium- and long-range contacts in coiled-coil domains and compared the results with those obtained for other (non-coiled-coil) parts of the same proteins and non-coiled-coil helical segments of globular proteins. The residues in coiled-coil domains are largely influenced by medium-range contacts, whereas long-range interactions play a dominant role in other regions of these same proteins as well as in non-coiled-coil helices. We have also revealed the preference of amino acid residues to form cation-pi interactions and we found that Arg is more likely to form such interactions than Lys. The parameters developed in this work can be used to understand the folding and stability of coiled-coil proteins in general.

Predicting protein conformation by statistical methods

The unique folded structure makes a polypeptide a functional protein. The number of known sequences is about a hundred times larger than the number of known structures and the gap is increasing rapidly. The primary goal of all structure prediction methods is to obtain structure-related information on proteins, whose structures have not been determined experimentally. Besides this goal, the development of accurate prediction methods helps to reveal principles of protein folding. Here we present a brief survey of protein structure predictions based on statistical analyses of known sequence and structure data. We discuss the background of these methods and attempt to elucidate principles, which govern structure formation of soluble and membrane proteins.

Factors influencing the stability of alpha-helices and beta-strands in thermophilic ribonuclease H

Understanding the influence of structural parameters is crucial to enhance the thermal stability of proteins. In this work, the stability (deltaG) of residues in different secondary structures of Ribonuclease H (RNase H) has been analyzed with 48 amino acid properties. The properties reflecting hydrophobicity show a good correlation with stability. Further, the linear distribution of surrounding hydrophobicity in alpha-helices, obtained from the three dimensional structure of thermophilic RNase H, agrees well with experimental deltaG values. Moreover, the stability parameters correlate better in alpha-helices than those did in beta-strand segments. Multiple regression analysis, incorporating combinations of three properties from among all possible combinations of the 48 properties, increased the correlation coefficient to 0.77.

Quantitative comparison of the ability of hydropathy scales to recognize surface beta-strands in proteins

Methods based on the use of hydropathy scales have been used widely to ascertain the secondary structures of proteins. However, over 100 such scales have been reported in the literature, and which of these is the most successful in terms of the prediction rate of the correct structure is not clear. This article, therefore, reports a comprehensive analysis of the relative success of hydropathy scales to locate beta-strands on the surfaces of proteins. The technique we used is based on the technique proposed by Fraser and Parry, but it includes a modification that allows a higher rate of successful prediction and a lower rate of overprediction. We used as a basis for assessing the predictions a database of sequence-unique structures that we previously established. Proteins 2001;42:243-255.

Structural class prediction: an application of residue distribution along the sequence

Deciphering the native conformation of proteins from their amino acid sequences is one of the most challenging problems in molecular biology. Information on the secondary structure of a protein can be helpful in understanding its native folded state. In our earlier work on molecular chaperones, we have analyzed the hydrophobic and charged patches, short-, medium- and long-range contacts and residue distributions along the sequence. In this article, we have made an attempt to predict the structural class of globular and chaperone proteins based on the information obtained from residue distributions. This method predicts the structural class with an accuracy of 93 and 96%, respectively, for the four- and three-state models in a training set of 120 globular proteins, and 90 and 96%, respectively, for a test set of 80 proteins. We have used this information and methodology to predict the structural classes of chaperones. Interestingly most of the chaperone proteins are predicted under alpha/beta or mixed folding type.

A graphic approach to evaluate algorithms of secondary structure prediction

Algorithms of secondary structure prediction have undergone the developments of nearly 30 years. However, the problem of how to appropriately evaluate and compare algorithms has not yet completely solved. A graphic method to evaluate algorithms of secondary structure prediction has been proposed here. Traditionally, the performance of an algorithm is evaluated by a number, i.e., accuracy of various definitions. Instead of a number, we use a graph to completely evaluate an algorithm, in which the mapping points are distributed in a three-dimensional space. Each point represents the predictive result of the secondary structure of a protein. Because the distribution of mapping points in the 3D space generally contains more information than a number or a set of numbers, it is expected that algorithms may be evaluated and compared by the proposed graphic method more objectively. Based on the point distribution, six evaluation parameters are proposed, which describe the overall performance of the algorithm evaluated. Furthermore, the graphic method is simple and intuitive. As an example of application, two advanced algorithms, i.e., the PHD and NNpredict methods, are evaluated and compared. It is shown that there is still much room for further improvement for both algorithms. It is pointed out that the accuracy for predicting either the alpha-helix or beta-strand in proteins with higher alpha-helix or beta-strand content, respectively, should be greatly improved for both algorithms.

Influence of medium and long range interactions in protein folding

Protein structures are stabilized by both local and long range interactions. In this work, we analyze the residue-residue contacts and the role of medium- and long-range interactions in globular proteins belonging to different structural classes. The results show that while medium range interactions predominate in all-alpha class proteins, long-range interactions predominate in all-beta class. Based on this, we analyze the performance of several structure prediction methods in different structural classes of globular proteins and found that all the methods predict the secondary structures of all-alpha proteins more accurately than other classes. Also, we observed that the residues occurring in the range of 21-30 residues apart contributes more towards long-range contacts and about 85% of residues are involved in long-range contacts. Further, the preference of residue pairs to the folding and stability of globular proteins is discussed.

Role of structural and sequence information in the prediction of protein stability changes: comparison between buried and partially buried mutations

Predicting mutation-induced changes in protein stability is one of the greatest challenges in molecular biology. In this work, we analyzed the correlation between stability changes caused by buried and partially buried mutations and changes in 48 physicochemical, energetic and conformational properties. We found that properties reflecting hydrophobicity strongly correlated with stability of buried mutations, and there was a direct relation between the property values and the number of carbon atoms. Classification of mutations based on their location within helix, strand, turn or coil segments improved the correlation of mutations with stability. Buried mutations within beta-strand segments correlated better than did those in alpha-helical segments, suggesting stronger hydrophobicity of the beta-strands. The stability changes caused by partially buried mutations in ordered structures (helix, strand and turn) correlated most strongly and were mainly governed by hydrophobicity. Due to the disordered nature of coils, the mechanism underlying their stability differed from that of the other secondary structures: the stability changes due to mutations within the coil were mainly influenced by the effects of entropy. Further classification of mutations within coils, based on their hydrogen-bond forming capability, led to much stronger correlations. Hydrophobicity was the major factor in determining the stability of buried mutations, whereas hydrogen bonds, other polar interactions and hydrophobic interactions were all important determinants of the stability of partially buried mutations. Information about local sequence and structural effects were more important for the prediction of stability changes caused by partially buried mutations than for buried mutations; they strengthened correlations by an average of 27% among all data sets.

Relationship between amino acid properties and protein stability: buried mutations

In order to understand the mechanism of protein stability and to develop a simple method for predicting mutation-induced stability changes, we analyzed the relationship between stability changes caused by buried mutations and changes in 48 amino acid properties. As expected from the importance of hydrophobicity, properties reflecting hydrophobicity are strongly correlated with the stability of proteins. We found that subgroup classification based on secondary structure increased correlations significantly, and mutations within beta-strand segments correlated better than did those in alpha-helical segments, which may result from stronger hydrophobicity of the beta-strands. Multiple regression analyses incorporating combinations of three properties from among all possible combinations of the 48 properties increased the correlation coefficient to 0.88 and by an average of 13% for all data sets. Analyzing the stability of tryptophan synthase mutants with Glu49 replaced by all other residues except Arg revealed that combining buriedness, solvent-accessible surface area for denatured protein, and unfolding Gibbs free energy change increased the correlation to 0.95. Consideration of sequence and structural information (neighboring residues in sequence and in space) did not significantly strengthen the correlations in buried mutations, suggesting that nonspecific interactions dominate in the interior of proteins.

A simple method for predicting transmembrane alpha helices with better accuracy

The prediction of a protein's structure from its amino acid sequence has been a long-standing goal of molecular biology. In this work, a new set of conformational parameters for membrane spanning alpha helices was developed using the information from the topology of 70 membrane proteins. Based on these conformational parameters, a simple algorithm has been formulated to predict the transmembrane alpha helices in membrane proteins. A FORTRAN program has been developed which takes the amino acid sequence as input and gives the predicted transmembrane alpha-helices as output. The present method correctly identifies 295 transmembrane helical segments in 70 membrane proteins with only two overpredictions. Furthermore, this method predicts all 45 transmembrane helices in the photosynthetic reaction center, bacteriorhodopsin and cytochrome c oxidase to an 86% level of accuracy and so is better than all other methods published to date.

Importance of long-range interactions in protein folding

Long-range interactions play an active role in the stability of protein molecules. In this work, we have analyzed the importance of long-range interactions in different structural classes of globular proteins in terms of residue distances. We found that 85% of residues are involved in long-range contacts. The residues occurring in the range of 4-10 residues apart contribute more towards long-range contacts in all-alpha proteins while the range is 11-20 in all-beta proteins. The hydrophobic residues Cys, Ile and Val prefer the 11-20 range and all other residues prefer the 4-10 range. The residues in all-beta proteins have an average of 3-8 long-range contacts whereas the residues in other classes have 1-4 long-range contracts. Furthermore, the preference of residue pairs to the folding and stability will be discussed.

Analysis of hydrophobic and charged patches and influence of medium- and long-range interactions in molecular chaperones

The amino acid composition of the aromatic residues Phe, Tyr and Trp are much less significant in chaperones and the residues Cys, Glu, His, Met and Pro vary significantly in chaperones compared to normal globular proteins. In the present work, we have analysed the hydrophobic and charged patches in molecular chaperones which provide more insight for a better understanding of chaperone folding. Also, we have investigated the role of medium- and long-range contacts in chaperones and the preference of amino acid residues influenced by these interactions. Furthermore, the role of hydrophobic and helix-forming residues and disulfide bonding in these interactions have been discussed.

Principles governing amino acid composition of integral membrane proteins: application to topology prediction

A new method is suggested here for topology prediction of helical transmembrane proteins. The method is based on the hypothesis that the localizations of the transmembrane segments and the topology are determined by the difference in the amino acid distributions in various structural parts of these proteins rather than by specific amino acid compositions of these parts. A hidden Markov model with special architecture was developed to search transmembrane topology corresponding to the maximum likelihood among all the possible topologies of a given protein. The prediction accuracy was tested on 158 proteins and was found to be higher than that found using prediction methods already available. The method successfully predicted all the transmembrane segments in 143 proteins out of the 158, and for 135 of these proteins both the membrane spanning regions and the topologies were predicted correctly. The observed level of accuracy is a strong argument in favor of our hypothesis.

Importance of long-range interactions in (alpha/beta)8 barrel fold

Protein structures are stabilized by both local and long-range interactions. In this work, we analyzed the importance of long-range interactions in (alpha/beta)8 barrel proteins in terms of residue distances. We found that the residues occurring in the range of 21-30 residues apart contribute more toward long-range contacts. Indeed, about 50% of successive strands in these proteins are found to occur at a sequential distance of 21-30 residues. The aromatic amino acid residues Phe, Trp, and Tyr prefer the 4-10 range and all other residues prefer the 21-30 range. Hydrophobic-hydrophobic residue pairs are the most preferred ones for long-range interactions and they may play a key role in the folding and stabilization of (alpha/beta)8 barrel proteins.

Solvent accessibility studies on glycosaminoglycans

Theoretical calculations on the solvent accessible surface area of the commonly occurring glycosaminoglycans (GAGs) have been carried out by employing the solvent accessibility technique of Lee and Richards. The results indicate that the average variation of solvent accessible surface area (ASA) for the different atoms is in the range of 2-28 A2. The average ASA for carbon (9.02 A2) and oxygen (19.3 A2) are relatively very high compared to that for nitrogen and sulfur. The total contribution of ASA by the buried atoms in all the molecules has been found to be small. Heparin complexed with the protein is less accessible to the solvent than the uncomplexed. The iduronic acid is also found to have a varied ASA due to its conformational flexibility. The sulfate groups in heparin have 50% of the total ASA of the molecule. Residue analysis indicates that in general D-configuration residues have higher ASA than L-configuration residues.

Solvent accessibility analysis on the mutants of Hsc70 ATPase fragment

Molecular chaperones are the cellular proteins which mediate the correct folding of other polypeptides. The concept of 'solvent accessibility' is one of the most powerful tools to understand the structure and stability of protein molecules. The hydrophobic variation of amino acid residues due to point mutations at many active sites of chaperone protein Hsc70 using solvent accessibility analysis is carried out. The numerical indices for several properties of amino acid residues, such as, reduction in accessibility, preference of amino acid residues in interior and surface parts, transfer free energy and the preference of amino acid residues to change their positions (buried/exposed) due to amino acid substitutions for Hsc70 and its mutants were set up. The accessibility of amino acid residues varies much between native and mutant proteins whereas there is no major changes on their conformations. The conformational stability for Hsc70 and its mutants were established and the computed hydrophobic free energy change is around 10 kcal/mol due to single amino acid substitution.

Influence of Medium and Long Range Interactions in (α/β)(8) Barrel Proteins

The residue-residue contacts and the role of medium and long rangeinteractions in 36 (α/β)(8) barrel proteins have beenanalysed. The influence of long range contacts in the formation ofphysico-chemically similar clusters, and the preference of amino acidresidues towards long range contacts have also been studied. Theresults reveal a nearly uniform level of medium and long rangecontacts in most of the proteins. The residues Gln and Ala havehighest medium range contacts and the residue Pro has the lowestmedium range contacts. The residue Cys has the highest long rangecontact followed by other hydrophobic residues namely Val, Ile andLeu. In the physico-chemically similar clusters identified in theseproteins, 25-40 percent residues are influenced by long rangecontacts, and the residues Cys, Ile, Val and Met are the mostpreferred ones.

Influence of medium and long range interactions in different structural classes of globular proteins

An analysis of the dependence known three dimensional structure ofglobular proteins on their residue contacts and their interactions providesmuch information about their folding and stability. In this work, we analysethe residue-residue contacts and the role of medium and long rangeinteractions in globular proteins belonging to different structural classes.The results show that while medium range interactions predominate in allalpha class proteins, long range interactions predominate in all beta class.The residues Pro and Gly are found to have lowest medium range contacts,probably due to their helix breaking tendency. The hydrophobic residues Ile,Val and Tyr have higher long range contacts, and hence may serve as goodnucleation centres. Further, the role of charged residues and disulfidebridges in these interactions are also discussed.

Prediction of conformational states of amino acids using a Ramachandran plot

(phi, psi) data from crystal structures of 221 proteins having high resolution and sequence similarity cut-off at the 25% level were analysed by dividing the Ramachandran plot in three regions representing three conformational states: (i) conformational state 1: conformations in the (phi, psi) range from (-140 degrees, -100 degrees) to (0 degrees, 0 degrees); (ii) conformational state 2: conformations with (phi, psi) from (-180 degrees, 80 degrees) to (0 degrees, 180 degrees); and (iii) conformational state 3: all the remaining conformations in the (phi, psi) plane which are not included in the above two conformational states. Normalized probability values of the occurrence of single amino acid residues in conformational regions 1-3 and similar values for dipeptides were calculated. Comparisons of single residue and dipeptide normalized probability values have shown that short-range interactions, although strong, destabilize conformational states of only 44 dipeptides out of the 400 x 9 possible states. However, dipeptide frequency values provide better resolving power than single-residue potentials when used to predict conformational states of residues in a protein from its primary structure. The simple approach used in the present study to predict conformational states yields an accuracy of > 70% for 14 proteins and an accuracy in the range of 50-70% for 247 proteins. Thus these studies point out yet another use of the Ramachandran plot and the role of tertiary interactions in protein folding.