Comparison of the structures of globins and phycocyanins: evidence for evolutionary relationship

Globins and phycocyanins are two classes of proteins with different function, different ligands, and no substantial sequence similarity, yet the conformations of their polypeptide chains show very similar folding patterns. Does this arise from a genuine, albeit very distant, evolutionary relationship, or does it represent a common solution of a structural problem? We address this question by a very detailed comparison of the structures of the two protein families. An analysis of the helices and their interactions shows many features common to globins and phycocyanins, including some exceptional features of the globins such as a 3–10 C helix and the unusual “crossed-ridge” packing pattern at the B/E helix interfaces. We conclude that the evidence supports the hypothesis of distant evolutionary relationship between globins and phycocyanins.     

Families and the structural relatedness among globular proteins.

Protein structures come in families. Are families “closely knit” or “loosely knit” entities? We describe a measure of relatedness among polymer conformations. Based on weighted distance maps, this measure differs from existing measures mainly in two respects: (1) it is computationally fast, and (2) it can compare any two proteins, regardless of their relative chain lengths or degree of similarity. It does not require finding relative alignments. The measure is used here to determine the dissimilarities between all 12, 403 possible pairs of 158 diverse protein structures from the Brookhaven Protein Data Bank (PDB). Combined with minimal spanning trees and hierarchical clustering methods, this measure is used to define structural families. It is also useful for rapidly searching a dataset of protein structures for specific substructural motifs. By using an analogy to distributions of Euclidean distances, we find that protein families are not tightly knit entities.     

Conformational analysis of endothelin-1: Effects of solvation free energy

In order to investigate conformational preferences of the 21-residue peptide hormone endothelin-1 (ET-1), an extensive conformational search was carried out in vacuo using a combination of high temperature molecular dynamics / annealing and a Monte Carlo / minimization search in torsion angle space. Fully minimized conformations from the search were grouped into families using a clustering technique based on rms fitting over the Cartesian coordinates of the atoms of the peptide backbone of the ring region. A wide range of local energy minima were identified even though two disulfide bridges (Cys¹-Cys¹⁵ and Cys³-Cys¹¹) constrain the structure of the peptide. Low energy conformers of ET-1 as a nonionized species in vacuo arestabilized by intramolecular interaction of the ring region (residues 1-15) with the tail (residues 16–21). Strained conformations for individual residues are observed. Conformational similarity to protein loops is established by matching to protein crystal structures In order to assess the influence of aqueous environment on conformational preference, the electrostatic contribution to the solvation energy was calculated for ET-1 as a fully ionized species (Asp⁸, Lys⁹, Glu¹⁰, Asp¹⁸, N- and C-terminus) using a continuum electrostatics model (DelPhi) for each of the conformed generated in vacuo, and the total solvation free energy was estimated by adding a hydrophobic contribution proportional to solvent accessible surface area. Solvation dramatically alters the relative energetics of ET-1 conformers from that calculated in vacuo. Conformers of ET-1 favored by the electrostatic salvation energy in water include conformers with helical secondary structure in the region of residues 9–15. Perhaps of most importance, it was demonstrated that the contribution tosolvation by an individual charge depends not only on its solvent accessibility but on the proximity of other charges, i.e., it is a cooperative effect. This was shown by the calculation of electrostatic solvation energy as afunction of conformation with individual charges systematically turned “on” and “off”. The cooperative effect of multiple charges on solvation demonstrated in this manner calls into question models that relate solvation energysimply to solvent accessibility by atom or residue alone. © 1995 John Wiley & Sons, Inc.     

Monte Carlo minimization with thermalization for global optimization of polypeptide conformations in cartesian coordinate space.

A new minimization procedure for the global optimization in cartesian coordinate space of the conformational energy of a polypeptide chain is presented. The Metropolis Monte Carlo minimization is thereby supplemented by a thermalization process, which is initiated whenever a structure becomes trapped in an area containing closely located local minima in the conformational space. The method has been applied to the endogenous opioid pentapeptide methionine enkephalin. Five among 13 different starting conformations led to the same apparent global minimum of an in-house developed energy function, a type II' reverse turn, the central residues of which are Gly-3-Phe-4. A comparison between the ECEPP/2 global minimum conformation of methionine enkephalin and the apparent one achieved by the present method shows that minimum-energy conformations having a certain similarity can be generated by relatively different force fields.     

Protein loops on structurally similar scaffolds: database and conformational analysis

A general problem in comparative modeling and protein design is the conformational evaluation of loops with a certain sequence in specific environmental protein frameworks. Loops of different sequences and structures on similar scaffolds are common in the Protein Data Bank (PDB). In order to explore both structural and sequential diversity of them, a data base of loops connecting similar secondary structure fragments is constructed by searching the data base of families of structurally similar proteins and PDB. A total of 84 loop families having 2-13 residues are found among the well-determined structures of resolution better than 2.5 A. Eight alpha-alpha, 20 alpha-beta, 19 beta-alpha, and 37 beta-beta families are identified. Every family contains more than 5 loop motifs. In each family, no loops share same sequence and all the frameworks are well superimposed. Forty-three new loop classes are distinguished in the data base. The structural variability of loops in homologous proteins are examined and shown in 44 families. Motif families are characterized with geometric parameters and sequence patterns. The conformations of loops in each family are clustered into subfamilies using average linkage cluster analysis method. Information such as geometric properties, sequence profile, sequential and structural variability in loop, structural alignment parameters, sequence similarities, and clustering results are provided. Correlations between the conformation of loops and loop sequence, motif sequence, and global sequence of PDB chain are examined in order to find how loop structures depend on their sequences and how they are affected by the local and global environment. Strong correlations (R > 0.75) are only found in 24 families. The best R value is 0.98. The data base is available through the Internet.     

Hierarchical sampling for metastable conformers determines biomolecular recognition: the case of malectin and diglucosylated N-glycan interactions

Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin’s exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate–aromatic interactions including CH–π and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to β-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.     

Understanding the structural characteristics of compstatin by conformational space annealing

The structural characteristics of the 13-residue compstatin molecule are investigated using the conformational space annealing (CSA) method with CHARMM force field and the GBSA continuum solvent model. In order to sample conformations in the energy range of the minimized NMR structures, we have used the stopping criterion to the CSA search when a conformation whose energy is less than -490 kcal/mol is found. With this stopping criterion, a great variety of conformations are generated around experimentally known structures. Twenty independent CSA runs starting from random states find 1000 representative conformations in the energy landscape of the compstatin, which are classified into thirty-one structural families. The majority of the conformations (94.4%) are in the coil state. Other conformers containing a 3(10)-helix, a pi-helix, a beta-hairpin, and an alpha-helix are also found.     

Navigating within thiamine diphosphate-dependent decarboxylases: Sequences,structures, functional positions,and binding sites

Thiamine diphosphate-dependent decarboxylases catalyze both cleavage and formation of C C bonds in various reactions, which have been assigned to different homologous sequence families. This work compares 53 ThDP-dependent decarboxylases with known crystal structures. Both sequence and structural information were analyzed synergistically and data were analyzed for global and local properties by means of statistical approaches (principle component analysis and principal coordinate analysis) enabling complexity reduction. The different results obtained both locally and globally, that is, individual positions compared with the overall protein sequence or structure, revealed challenges in the assignment of separated homologous families. The methods applied herein support the comparison of enzyme families and the identification of functionally relevant positions. The findings for the family of ThDP-dependent decarboxylases underline that global sequence identity alone is not sufficient to distinguish enzyme function. Instead, local sequence similarity, defined by comparisons of structurally equivalent positions, allows for a better navigation within several groups of homologous enzymes. The differentiation between homologous sequences is further enhanced by taking structural information into account, such as BioGPS analysis of the active site properties or pairwise structural superimpositions. The methods applied herein are expected to be transferrable to other enzyme families, to facilitate family assignments for homologous protein sequences.     

Conformational analysis of a novel cyclic enkephalin analogue using NMR and EDMC calculations

Conformational space of a novel cyclic enkephalin analogue, cyclo(N(epsilon),N(epsilon')-carbonyl-D-Lys2,Lys5)enkephalin amide, was exhaustively examined. A large number of conformations was selected and clustered into families on the basis of their structure and energy. For representative conformations ROESY spectra were generated and their linear combination was fitted to the spectra measured in water and Me2SO-d6. This procedure yielded an ensemble of most populated conformations of the peptide in the two solvents.     

The Urfold: Structural similarity just above the superfold level?

We suspect that there is a level of granularity of protein structure intermediate between the classical levels of “architecture” and “topology,” as reflected in such phenomena as extensive three‐dimensional structural similarity above the level of (super)folds. Here, we examine this notion of architectural identity despite topological variability, starting with a concept that we call the “Urfold.” We believe that this model could offer a new conceptual approach for protein structural analysis and classification: indeed, the Urfold concept may help reconcile various phenomena that have been frequently recognized or debated for years, such as the precise meaning of “significant” structural overlap and the degree of continuity of fold space. More broadly, the role of structural similarity in sequence?structure?function evolution has been studied via many models over the years; by addressing a conceptual gap that we believe exists between the architecture and topology levels of structural classification schemes, the Urfold eventually may help synthesize these models into a generalized, consistent framework. Here, we begin by qualitatively introducing the concept.     

Improving conformational searches by geometric screening

MOTIVATION: Conformational searches in molecular docking are a time-consuming process with wide range of applications. Favorable conformations of the ligands that successfully bind with receptors are sought to form stable ligand-receptor complexes. Usually a large number of conformations are generated and their binding energies are examined. We propose adding a geometric screening phase before an energy minimization procedure so that only conformations that geometrically fit in the binding site will be prompted for energy calculation. RESULTS: Geometric screening can drastically reduce the number of conformations to be examined from millions (or higher) to thousands (or lower). The method can also handle cases when there are more variables than geometric constraints. An early-stage implementation is able to finish the geometric filtering of conformations for molecules with up to nine variables in 1 min. To the best of our knowledge, this is the first time such results are reported deterministically. CONTACT: mzhang@mdanderson.org.     

A method of factor analysis for shape coordinates

Currently the most common reporting style for a geometric morphometric (GMM) analysis of anthropological data begins with the principal components of the shape coordinates to which the original landmark data have been converted. But this focus often frustrates the organismal biologist, mainly because principal component analysis (PCA) is not aimed at scientific interpretability of the loading patterns actually uncovered. The difficulty of making biological sense of a PCA is heightened by aspects of the shape coordinate setting that further diverge from our intuitive expectations of how morphometric measurements ought to combine. More than 50 years ago one of our sister disciplines, psychometrics, managed to build an algorithmic route from principal component analysis to scientific understanding via the toolkit generally known as factor analysis. This article introduces a modification of one standard factor‐analysis approach, Henry Kaiser's varimax rotation of 1958, that accommodates two of the major differences between the GMM context and the psychometric context for these approaches: the coexistence of “general” and “special” factors of form as adumbrated by Sewall Wright, and the typical loglinearity of partial warp variance as a function of bending energy. I briefly explain the history of principal components in biometrics and the contrast with factor analysis, introduce the modified varimax algorithm I am recommending, and work three examples that are reanalyses of previously published cranial data sets. A closing discussion emphasizes the desirability of superseding PCA by algorithms aimed at anthropological understanding rather than classification or ordination.     

Local sequence‐structure relationships in proteins

We seek to understand the interplay between amino acid sequence and local structure in proteins. Are some amino acids unique in their ability to fit harmoniously into certain local structures? What is the role of sequence in sculpting the putative native state folds from myriad possible conformations? In order to address these questions, we represent the local structure of each C_α atom of a protein by just two angles, θ and μ, and we analyze a set of more than 4,000 protein structures from the PDB. We use a hierarchical clustering scheme to divide the 20 amino acids into six distinct groups based on their similarity to each other in fitting local structural space. We present the results of a detailed analysis of patterns of amino acid specificity in adopting local structural conformations and show that the sequence‐structure correlation is not very strong compared with a random assignment of sequence to structure. Yet, our analysis may be useful to determine an effective scoring rubric for quantifying the match of an amino acid to its putative local structure.     

Classification of the family Plectonemertidae (Nemertea): a phenetic comparison

A phenetic classification based on overall morphological similarity between the species in the family Plectonemertidae (genera Plectonemertes, Campbellonemertes, Potamonemertes, Leptonemertes, Katechonemertes, Argonemertes, Anliponemertes, and Acteonemertes ) was undertaken and the result compared with a cladistic and an evolutionary classification. Similarity between species was computed by Gower's general coefficient of similarity and various techniques were used to find patterns in the similarity matrix: single-linkage, average-linkage, and complete-linkage clustering, together with principal coordinate analysis. Although the explicit aim of phenetics is not to estimate the phylogeny, the classification based on overall similarity still portrays phylogeny better than an intuitive assessment of morphological similarity, as judged by the cladistic analysis. The classification does not support the previously proposed hypothesis that the two freshwater genera Campbellonemertes and Potamonemertes have descended from a terrestrial ancestor.     

Conformational landscapes for KMSKS loop in tyrosyl-tRNA synthetases

Protein synthesis requires accurate charging of tRNA with cognate amino acid as catalyzed by aminoacyl-tRNA synthetases. Crystal structures of tyrosyl-tRNA synthetase (YRSs) show remarkably diverse conformations for the KMSKS loop, hitherto classified as “open” and “closed”. This traditional classification implied that the KMSKS loop adopts different conformations depending on occupancy of active site pocket. Our structural analyses of evolutionarily derived ensemble of differentially ligated YRSs using quantitative structural criterion demonstrate intrinsic conformational heterogeneity in KMSKS loop that is independent of occupancy of active site. Differential centroid distance analyses between KMSKS motif and Rossmann fold domain reveal an intriguing bimodal distribution. These insights have been used for a more consistent re-classification of YRS conformations as either compact or extended. Our data not only reflect inherent dynamics within the conformational landscape of KMSKS loops, but also have implications for structure-based drug design efforts.     

A new method for modeling large-scale rearrangements of protein domains

A method for modeling large-scale rearrangements of protein domains connected by a single- or a double-stranded linker is proposed. Multidomain proteins may undergo substantial domain displacements, while their intradomain structure remains essentially unchanged. The method allows automatic identification of an interdomain linker and builds an all-atom model of a protein structure in internal coordinates. Torsion angles belonging to the interdomain linkers and side chains potentially able to form domain interfaces are set free while all remaining torsions, bond lengths, and bond angles are fixed. Large-scale sampling of the reduced torsion conformational subspace is effected with the “biased probability Monte Carlo-minimization” method [Abagyan, R.A., Totrov, M.M. (1994): J. Mol. Biol. 235, 983–1002]. Solvation and side-chain entropic contributions are added to the energy function. A special procedure has been developed to generate concerted deformations of a double-stranded interdomain linker in such a way that the polypeptide chain continuity is preserved. The method was tested on Bence-Jones protein with a single-stranded linker and lysine/arginine/ornithine-binding (LAO) protein with a double-stranded linker. For each protein, structurally diverse low-energy conformations with ideal covalent geometry were generated, and an overlap between two sets of conformations generated starting from the crystallographically determined “closed” and “open” forms was found. One of the low-energy conformations generated in a run starting from the LAO “closed” form was only 2.2 Å away from the structure of the “open” form. The method can be useful in predicting the scope of possible domain rearrangements of a multidomain protein. Proteins 27:410–424, 1997. © 1997 Wiley-Liss, Inc.     

New developments of the electrostatically driven monte carlo method: Test on the membrane-bound portion of melittin

The electrostatically driven Monte Carlo (EDMC) method has been greatly improved by adding a series of new features, including a procedure for cluster analysis of the accepted conformations. This information is used to guide the search for the global energy minimum. Alternative procedures for generating perturbed conformations to sample the conformational space were also included. These procedures enhance the efficiency of the method by generating a larger number of low-energy conformations. The improved EDMC method has been used to explore the conformational space of a 20-residue polypeptide chain whose sequence corresponds to the membrane-bound portion of melittin. The ECEPP/3 (Empirical Conformational Energy Program for Peptides) algorithm was used to describe the conformational energy of the chain. After an exhaustive search involving 14 independent runs, the lowest energy conformation (LEC) (−91.0 kcal/mol) of the entire study was encountered in four of the runs, while conformations higher in energy by no more than 1.8 kcal/mol were found in the remaining runs with the exception of one of them (run 8). The LEC is identical to the conformation found recently by J. Lee, H.A. Scheraga, and S. Rackovsky [(1998) “Conformational Analysis of the 20-Residue Membrane-Bound Portion of Melittin by Conformational Space Annealing,” Biopolymers, Vol. 46, pp. 103–115] as the lowest energy conformation obtained in their study using the conformational space annealing method. These results suggest that this conformation corresponds to the global energy minimum of the ECEPP/3 potential function for this specific sequence; it also appears to be the conformation of lowest free energy. © 1998 John Wiley & Sons, Inc. Biopoly 46: 117–126, 1998     

Genetic variation among Saudi tomato (Solanum lycopersicum L.) landraces studied using SDS-PAGE and SRAP markers

Genetic diversity among seven Saudi tomato landraces collected from different regions of the country was assessed using SDS-PAGE and molecular (sequence-related amplified polymorphism- SRAP) markers. A total of 19 alternative protein bands with different mobility rates were identified within a molecular weight range of 9.584–225?KDa, with 53% polymorphism. Specific protein bands were observed in the “Hail 548” and “Qatif 565” landraces. Genetic similarity based on Jaccard’s coefficient ranged from 0.53 to 1.00, with an average of 0.72. For molecular evaluation, 143 amplicons (fragments) were generated using 27 SRAP primer pair combinations, of which 88 were polymorphic across all the landraces. The PIC values ranged from 0.46 to 0.90, with an average of 0.76. All landraces showed an average of 0.66 similarity coefficient value. The UPGMA dendrogram supported by principal coordinate analysis (PCoA) revealed clusters of the landraces that almost corresponded to their geographical origin. Thus, seed storage protein profiling based on SDS-PAGE and SRAP markers can efficiently be used to assess genetic variability among tomato germplasms. The information obtained in the analysis will be of great interest in the management of ex situ collections for utilization in breeding programs or for direct use in quality markets.     

An efficient algorithm for large-scale detection of protein families

Detection of protein families in large databases is one of the principal research objectives in structural and functional genomics. Protein family classification can significantly contribute to the delineation of functional diversity of homologous proteins, the prediction of function based on domain architecture or the presence of sequence motifs as well as comparative genomics, providing valuable evolutionary insights. We present a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families. The method relies on the Markov cluster (MCL) algorithm for the assignment of proteins into families based on precomputed sequence similarity information. This novel approach does not suffer from the problems that normally hinder other protein sequence clustering algorithms, such as the presence of multi-domain proteins, promiscuous domains and fragmented proteins. The method has been rigorously tested and validated on a number of very large databases, including SwissProt, InterPro, SCOP and the draft human genome. Our results indicate that the method is ideally suited to the rapid and accurate detection of protein families on a large scale. The method has been used to detect and categorise protein families within the draft human genome and the resulting families have been used to annotate a large proportion of human proteins.