Samuel Selvaraj

FOLD-RATE: prediction of protein folding rates from amino acid sequence

We have developed a web server, FOLD-RATE, for predicting the folding rates of proteins from their amino acid sequences. The relationship between amino acid properties and protein folding rates has been systematically analyzed and a statistical method based on linear regression technique has been proposed for predicting the folding rate of proteins. We found that the classification of proteins into different structural classes shows an excellent correlation between amino acid properties and folding rates of two and three-state proteins. Consequently, different regression equations have been developed for proteins belonging to all-α, all-β and mixed class. We observed an excellent agreement between predicted and experimentally observed folding rates of proteins; the correlation coefficients are, 0.99, 0.97 and 0.90, respectively, for all-α, all-β and mixed class proteins. The prediction server is freely available at .

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.

Locating the stabilizing residues in (α/β)8 barrel proteins based on hydrophobicity, long‐range interactions, and sequence conservation

In nature, 1 out of every 10 proteins has an (α/β)8 (TIM)‐barrel fold, and in most cases, pairwise comparisons show no sequence similarity between them. Hence, delineating the key residues that induce very different sequences to share a common fold is important for understanding the folding and stability of TIM‐barrel domains. In this work, we propose a new consensus approach for locating these stabilizing residues based on long‐range interactions, hydrophobicity, and conservation of amino acid residues. We have identified 957 stabilizing residues in 63 proteins from a nonredundant set of 71 TIM‐barrel domains. Most of these residues are located in the 8‐stranded β‐sheet, with nearly one half of them oriented toward the interior of the barrel and the other half oriented toward the surrounding α‐helices. Several stabilizing residues are found in the N‐ and C‐terminal loops, whereas very few appear in the α‐helices that surround the internal β‐sheet. Further, these 957 residues are placed in 434 stabilizing segments of various sizes, and each domain contains 1–10 of these segments. We found that 8 segments per domain is the most abundant one, and two thirds of the proteins have 7–9 stabilizing segments. Finally, we verified the identified residues with experimental temperature factors and found that these residues are among the ones with less mobility in the considered proteins. We suggest that our new protocol serves as a powerful tool to identify the stabilizing residues in TIM‐barrel domains, which can be used as potential candidates for studying protein folding and stability by means of protein engineering experiments. Proteins 2004;55:000–000.

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.

Specificity of Protein–DNA Recognition Revealed by Structure-based Potentials: Symmetric/Asymmetric and Cognate/Non-cognate Binding

Asymmetric binding of protein homodimers to DNA, which has been observed in a number of protein-DNA complexes, leads to subtle structural differences between the two subunits. Such structural differences are frequently observed when the subunits form cognate and non-cognate protein-DNA complexes, respectively. Analysis of these structural effects on binding specificity should provide insight into the mechanism of protein-DNA recognition. We previously derived empirical potential functions for specific nucleotide base-amino acid interactions from statistical analyses of the structures of many protein-DNA complexes and used a combinatorial threading procedure to evaluate the fitness of the DNA sequences involved. We then introduced Z-scores to measure the specificity with which proteins bind to DNA within complexes, as compared to random DNA sequences. Here, we examined in detail the structural effects of asymmetric and cognate/non-cognate binding on specificity. Marked differences in the specificity of DNA binding were observed for the two subunits of lambda repressor, the glucocorticoid receptor, and for transcription factors containing a Zn(2)Cys(6) binuclear cluster domain, which are known to bind asymmetrically to DNA. Moreover, the differences in the specificity with which BamH1 and EcoRV endonucleases bind to their cognate and non-cognate DNA sequences were clearly detected using this approach; indeed, analysis of EcoRV binding enabled us to show the cooperative effect of sequence and structure on binding specificity. The present results demonstrate the utility of this approach when examining the structure-specificity relationship in protein-DNA recognition, as subtle structural differences in symmetric/asymmetric and cognate/non-cognate binding were clearly shown to cause marked differences in specificity. This method can also be used as a tool for checking new structures of protein-DNA complexes for their specificity.

Role of Hydrophobic Clusters and Long-Range Contact Networks in the Folding of (α/β)8 Barrel Proteins

Analysis on the three dimensional structures of (α/β)8 barrel proteins provides ample light to understand the factors that are responsible for directing and maintaining their common fold. In this work, the hydrophobically enriched clusters are identified in 92% of the considered (α/β)8 barrel proteins. The residue segments with hydrophobic clusters have high thermal stability. Further, these clusters are formed and stabilized through long-range interactions. Specifically, a network of long-range contacts connects adjacent β-strands of the (α/β)8 barrel domain and the hydrophobic clusters. The implications of hydrophobic clusters and long-range networks in providing a feasible common mechanism for the folding of (α/β)8 barrel proteins are proposed.

ProTherm, Thermodynamic Database for Proteins and Mutants: developments in version 3.0

The current release of ProTherm, Thermodynamic Database for Proteins and Mutants, contains more than 10 000 numerical data (300% of the first version) of several thermodynamic parameters, experimental methods and conditions, reversibility of folding, details about the surrounding residues in space for all mutants, structural, functional and literature information. In the current version, we have added information about the source of each protein, identification codes for SWISS-PROT and Protein Information Resource and unique Protein Data Bank (PDB) code for proteins with relevant source. We have also provided additional options to search for data based on PDB code, number of states and reversibility. ProTherm is cross-linked with other sequence, structural, functional and literature databases, and the mutant sites and surrounding residues are automatically mapped on the structure. The ProTherm database is freely available at http://www.rtc.riken.go.jp/jouhou/protherm/protherm.html.

Thermodynamic database for protein-nucleic acid interactions (ProNIT)

MOTIVATION Protein-nucleic acid interactions are fundamental to the regulation of gene expression. In order to elucidate the molecular mechanism of protein-nucleic acid recognition and analyze the gene regulation network, not only structural data but also quantitative binding data are necessary. Although there are structural databases for proteins and nucleic acids, there exists no database for their experimental binding data. Thus, we have developed a Thermodynamic Database for Protein-Nucleic Acid Interactions (ProNIT). RESULTS We have collected experimentally observed binding data from the literature. ProNIT contains several important thermodynamic data for protein-nucleic acid binding, such as dissociation constant (K(d)), association constant (K(a)), Gibbs free energy change (DeltaG), enthalpy change (DeltaH), heat capacity change (DeltaC(p)), experimental conditions, structural information of proteins, nucleic acids and the complex, and literature information. These data are integrated into a relational database system together with structural and functional information to provide flexible searching facilities by using combinations of various terms and parameters. A www interface allows users to search for data based on various conditions, with different display and sorting options, and to visualize molecular structures and their interactions. AVAILABILITY ProNIT is freely accessible at the URL http://www.rtc.riken.go.jp/jouhou/pronit/pronit.html.

Important amino acid properties for determining the transition state structures of two-state protein mutants.

Understanding the mechanism in the folding pathways of proteins is an important problem in molecular biology. The Φ‐value analysis provides insight into the transition state structures during protein folding. In this work, we have analyzed the relationship between the observed Φ values upon mutations in two‐state proteins (FK506 binding protein, chymotrypsin inhibitor and src SH3 domain) and the changes in 48 various physico‐chemical, energetic and conformational properties. We found that the classification of mutations based on solvent accessibility improved the correlation significantly. The relationship between conformational properties and Φ values determines the presence/absence of secondary structures in the transition state. In buried mutations, the physical properties volume, shape and flexibility, and the thermodynamic properties enthalpy, entropy and free‐energy change have significant correlation with Φ. The short and medium‐range non‐bonded energy in partially buried mutations and average long‐range contacts in exposed mutations showed a strong correlation with Φ values. Multiple regression analysis incorporating combinations of three properties from among all possible combinations of the 48 properties increased the correlation coefficient up to 0.99, by an average rise of 20% for all the data sets. Information about local sequence and structure is more important in surface mutations than those in buried mutations for explaining the transition state structures of two‐state proteins. Further, the implications of our results for understanding the process of protein folding have been discussed.

Clusters in \alpha / \beta Barrel Proteins: Implications for Protein Structure, Function, and Folding: A Graph Theoretical Approach

The α/β barrel fold is adopted by most enzymes performing a variety of catalytic reactions, but with very low sequence similarity. In order to understand the stabilizing interactions important in maintaining the α/β barrel fold, we have identified residue clusters in a dataset of 36 α/β barrel proteins that have less than 10% sequence identity within themselves. A graph theoretical algorithm is used to identify backbone clusters. This approach uses the global information of the nonbonded interaction in the α/β barrel fold for the clustering procedure. The nonbonded interactions are represented mathematically in the form of an adjacency matrix. On diagonalizing the adjacency matrix, clusters and cluster centers are obtained from the highest eigenvalue and its corresponding vector components. Residue clusters are identified in the strand regions forming the β barrel and are topologically conserved in all 36 proteins studied. The residues forming the cluster in each of the α/β protein are also conserved among the sequences belonging to the same family. The cluster centers are found to occur in the middle of the strands or in the C‐terminal of the strands. In most cases, the residues forming the clusters are part of the active site or are located close to the active site. The folding nucleus of the α/β fold is predicted based on hydrophobicity index evaluation of residues and identification of cluster centers. The predicted nucleation sites are found to occur mostly in the middle of the strands. Proteins 2001;43:103–112.