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PubMed2003

Structure-based functional inference in structural genomics.

The dramatically increasing number of new protein sequences arising from genomics and proteomics requires the need for methods to rapidly and reliably infer the molecular and cellular functions of these proteins. One such approach, structural genomics, aims to delineate the total repertoire of protein folds in nature, thereby providing three-dimensional folding patterns for all proteins and to infer molecular functions of the proteins based on the combined information of structures and sequences. The goal of obtaining protein structures on a genomic scale has motivated the development of high throughput technologies and protocols for macromolecular structure determination that have begun to produce structures at a greater rate than previously possible. These new structures have revealed many unexpected functional inferences and evolutionary relationships that were hidden at the sequence level. Here, we present samples of structures determined at Berkeley Structural Genomics Center and collaborators' laboratories to illustrate how structural information provides and complements sequence information to deduce the functional inferences of proteins with unknown molecular functions. Two of the major premises of structural genomics are to discover a complete repertoire of protein folds in nature and to find molecular functions of the proteins whose functions are not predicted from sequence comparison alone. To achieve these objectives on a genomic scale, new methods, protocols, and technologies need to be developed by multi-institutional collaborations worldwide. As part of this effort, the Protein Structure Initiative has been launched in the United States (PSI; www.nigms.nih.gov/funding/psi.html). Although infrastructure building and technology development are still the main focus of structural genomics programs, a considerable number of protein structures have already been produced, some of them coming directly out of semiautomated structure determination pipelines. The Berkeley Structural Genomics Center (BSGC) has focused on the proteins of Mycoplasma or their homologues from other organisms as its structural genomics targets because of the minimal genome size of the Mycoplasmas as well as their relevance to human and animal pathogenicity (http://www.strgen.org). Here we present several protein examples encompassing a spectrum of functional inferences obtainable from their three-dimensional structures in five situations, where the inferences are new and testable, and are not predictable from protein sequence information alone.

Adenosine Triphosphate↗

PubMed2005

Sequence structure of van der Waals locks in proteins.

Recent works has suggested that proteins in early evolution have gone through a stage of closed loop elements with a typical contour size of 25-35 residues. These closed loops are still the elementary protein units to these days, and can be used to spell out protein sequence/structure relationship through a relatively small number of protein prototypes. In this study we aimed to identify the sequences that are used to lock the loop ends to one another, and to show how an extensive dictionary of such locking pairs can be created using positional correlation data from a large proteome database, and structural data from PDB databases. Such a dictionary can be used in reconstructing the evolutionary pathway the modern proteins have gone through, and in identifying closed loop elements in modern proteins with yet unknown 3D structure.

Amino Acid Motifs↗

PubMed2003

Gene3D: structural assignments for the biologist and bioinformaticist alike.

The Gene3D database (http://www.biochem.ucl.ac.uk/bsm/cath_new/Gene3D/) provides structural assignments for genes within complete genomes. These are available via the internet from either the World Wide Web or FTP. Assignments are made using PSI-BLAST and subsequently processed using the DRange protocol. The DRange protocol is an empirically benchmarked method for assessing the validity of structural assignments made using sequence searching methods where appropriate assignment statistics are collected and made available. Gene3D links assignments to their appropriate entries in relevent structural and classification resources (PDBsum, CATH database and the Dictionary of Homologous Superfamilies). Release 2.0 of Gene3D includes 62 genomes, 2 eukaryotes, 10 archaea and 40 bacteria. Currently, structural assignments can be made for between 30 and 40 percent of any given genome. In any genome, around half of those genes assigned a structural domain are assigned a single domain and the other half of the genes are assigned multiple structural domains. Gene3D is linked to the CATH database and is updated with each new update of CATH.

Animals↗

PubMed2003

MMDB: Entrez's 3D-structure database.

Three-dimensional structures are now known within most protein families and it is likely, when searching a sequence database, that one will identify a homolog of known structure. The goal of Entrez's 3D-structure database is to make structure information and the functional annotation it can provide easily accessible to molecular biologists. To this end, Entrez's search engine provides several powerful features: (i) links between databases, for example between a protein's sequence and structure; (ii) pre-computed sequence and structure neighbors; and (iii) structure and sequence/structure alignment visualization. Here, we focus on a new feature of Entrez's Molecular Modeling Database (MMDB): Graphical summaries of the biological annotation available for each 3D structure, based on the results of automated comparative analysis. MMDB is available at: http://www.ncbi.nlm.nih.gov/Entrez/structure.html.

Animals↗

PubMed2003

The SBASE domain sequence library, release 10: domain architecture prediction.

SBASE (http://www.icgeb.trieste.it/sbase) is an on-line collection of protein domain sequences and related computational tools designed to facilitate detection of domain homologies based on simple database search. The 10th 'jubilee release' of the SBASE library of protein domain sequences contains 1 052 904 protein sequence segments annotated by structure, function, ligand-binding or cellular topology, clustered into over 6000 domain groups. Domain identification and functional prediction are based on a comparison of BLAST search outputs with a knowledge base of biologically significant similarities extracted from known domain groups. The knowledge base is generated automatically for each domain group from the comparison of within-group ('self') and out-of-group ('non-self') similarities. This is a memory-based approach wherein group-specific similarity functions are automatically learned from the database.

Animals↗

PubMed2006

DMAPS: a database of multiple alignments for protein structures.

The database of multiple alignments for protein structures (DMAPS) provides instant access to pre-computed multiple structure alignments for all protein structure families in the Protein Data Bank (PDB). Protein structure families have been obtained from four distinct classification methods including SCOP, CATH, ENZYME and CE, and multiple structure alignments have been built for all families containing at least three members, using CE-MC software. Currently, multiple structure alignments are available for 3050 SCOP-, 3087 CATH-, 664 ENZYME- and 1707 CE-based families. A web-based query system has been developed to retrieve multiple alignments for these families using the PDB chain ID of any member of a family. Multiple alignments can be viewed or downloaded in six different formats, including JOY/html, TEXT, FASTA, PDB (superimposed coordinates), JOY/postscript and JOY/rtf. DMAPS is accessible online at http://bioinformatics.albany.edu/~dmaps.

Databases, Protein↗

PubMed2006

Flexible Structural Neighborhood--a database of protein structural similarities and alignments.

Protein structures are flexible, changing their shapes not only upon substrate binding, but also during evolution as a collective effect of mutations, deletions and insertions. A new generation of protein structure comparison algorithms allows for such flexibility; they go beyond identifying the largest common part between two proteins and find hinge regions and patterns of flexibility in protein families. Here we present a Flexible Structural Neighborhood (FSN), a database of structural neighbors of proteins deposited in PDB as seen by a flexible protein structure alignment program FATCAT, developed previously in our group. The database, searchable by a protein PDB code, provides lists of proteins with statistically significant structural similarity and on lower menu levels provides detailed alignments, interactive superposition of structures and positions of hinges that were identified in the comparison. While superficially similar to other structural protein alignment resources, FSN provides a unique resource to study not only protein structural similarity, but also how protein structures change. FSN is available from a server http://fatcat.burnham.org/fatcat/struct_neighbor and by direct links from the PDB database.

Databases, Protein↗

PubMed2004

Evaluation of structural similarity based on reduced dimensionality representations of protein structure.

Protein similarity estimations can be achieved using reduced dimensional representations and we describe a new application for the generation of two-dimensional maps from the three-dimensional structure. The code for the dimensionality reduction is based on the concept of pseudo-random generation of two-dimensional coordinates and Monte Carlo-like acceptance criteria for the generated coordinates. A new method for calculating protein similarity is developed by introducing a distance-dependent similarity field. Similarity of two proteins is derived from similarity field indices between amino acids based on various criteria such as hydrophobicity, residue replacement factors and conformational similarity, each showing a one factor Gaussian dependence. Results on comparisons of misfolded protein models with data sets of correctly folded structures show that discrimination between correctly folded and misfolded structures is possible. Tests were carried out on five different proteins, comparing a misfolded protein structure with members of the same topology, architecture, family and domain according to the CATH classification.

Computational Biology↗

PubMed2004

The structure and refinement of apocrustacyanin C2 to 1.3 A resolution and the search for differences between this protein and the homologous apoproteins A1 and C1.

The blue carotenoprotein alpha-crustacyanin of Homarus gammarus lobster carapace is comprised chemically of five 20 kDa subunits. Only two genes for the proteins have been isolated (J. B. C. Findlay, personal communication) and the five apoproteins fall into two sets of homologous proteins based on their chemical properties (CRTC, consisting of apoproteins C(1), C(2) and A(1), and CRTA, consisting of apoproteins A(2) and A(3)). The diffraction quality of apo C(2) has been improved from 2.2 to 1.3 A and its structure solved. The structure is compared with the A(1) and C(1) proteins determined at 1.4 A [Cianci et al. (2001), Acta Cryst. D57, 1219-1229] and 1.15 A, respectively [Gordon et al. (2001), Acta Cryst. D57, 1230-1237] and found to be very similar. Normalized B-factor difference plots per residue of different types were used to try to find chemically modified residues; none were found at these resolutions. It remains possible that the differences between the CRTC proteins result from differences in amidation. By comparison of a crystal grown with glycerol (studied at 1.6 A) and one grown without glycerol (studied at 1.3 A) it was seen that glycerol bound at the astaxanthin site.

Animals↗

PubMed2003

A consensus view of fold space: combining SCOP, CATH, and the Dali Domain Dictionary.

We have determined consensus protein-fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein-fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web.

Amino Acid Motifs↗

PubMed2003

Finding evolutionary relations beyond superfamilies: fold-based superfamilies.

Superfamily classifications are based variably on similarity of sequences, global folds, local structures, or functions. We have examined the possibility of defining superfamilies purely from the viewpoint of the global fold/function relationship. For this purpose, we first classified protein domains according to the beta-sheet topology. We then introduced the concept of kinship relations among the classified beta-sheet topology by assuming that the major elementary event leading to creation of a new beta-sheet topology is either an addition or deletion of one beta-strand at the edge of an existing beta-sheet during the molecular evolution. Based on this kinship relation, a network of protein domains was constructed so that the distance between a pair of domains represents the number of evolutionary events that lead one from the other domain. We then mapped on it all known domains with a specific core chemical function (here taken, as an example, that involving ATP or its analogs). Careful analyses revealed that the domains are found distributed on the network as >20 mutually disjointed clusters. The proteins in each cluster are defined to form a fold-based superfamily. The results indicate that >20 ATP-binding protein superfamilies have been invented independently in the process of molecular evolution, and the conservative evolutionary diffusion of global folds and functions is the origin of the relationship between them.

Adenosine Triphosphate↗

PubMed2005

A novel approach to structural alignment using realistic structural and environmental information.

In the era of structural genomics, it is necessary to generate accurate structural alignments in order to build good templates for homology modeling. Although a great number of structural alignment algorithms have been developed, most of them ignore intermolecular interactions during the alignment procedure. Therefore, structures in different oligomeric states are barely distinguishable, and it is very challenging to find correct alignment in coil regions. Here we present a novel approach to structural alignment using a clique finding algorithm and environmental information (SAUCE). In this approach, we build the alignment based on not only structural coordinate information but also realistic environmental information extracted from biological unit files provided by the Protein Data Bank (PDB). At first, we eliminate all environmentally unfavorable pairings of residues. Then we identify alignments in core regions via a maximal clique finding algorithm. Two extreme value distribution (EVD) form statistics have been developed to evaluate core region alignments. With an optional extension step, global alignment can be derived based on environment-based dynamic programming linking. We show that our method is able to differentiate three-dimensional structures in different oligomeric states, and is able to find flexible alignments between multidomain structures without predetermined hinge regions. The overall performance is also evaluated on a large scale by comparisons to current structural classification databases as well as to other alignment methods.

Algorithms↗

PubMed2006

Secondary structure spatial conformation footprint: a novel method for fast protein structure comparison and classification.

BACKGROUND: Recently a new class of methods for fast protein structure comparison has emerged. We call the methods in this class projection methods as they rely on a mapping of protein structure into a high-dimensional vector space. Once the mapping is done, the structure comparison is reduced to distance computation between corresponding vectors. As structural similarity is approximated by distance between projections, the success of any projection method depends on how well its mapping function is able to capture the salient features of protein structure. There is no agreement on what constitutes a good projection technique and the three currently known projection methods utilize very different approaches to the mapping construction, both in terms of what structural elements are included and how this information is integrated to produce a vector representation. RESULTS: In this paper we propose a novel projection method that uses secondary structure information to produce the mapping. First, a diverse set of spatial arrangements of triplets of secondary structure elements, a set of structural models, is automatically selected. Then, each protein structure is mapped into a high-dimensional vector of "counts" or footprint, where each count corresponds to the number of times a given structural model is observed in the structure, weighted by the precision with which the model is reproduced. We perform the first comprehensive evaluation of our method together with all other currently known projection methods. CONCLUSION: The results of our evaluation suggest that the type of structural information used by a projection method affects the ability of the method to detect structural similarity. In particular, our method that uses the spatial conformations of triplets of secondary structure elements outperforms other methods in most of the tests.

Computational Biology↗

PubMed2000

Anti-sense approach to anticholinesterase therapeutics.

The acetylcholine-hydrolyzing enzyme, acetylcholinesterase, is the molecular target of approved drugs for Alzheimer's disease and myasthenia gravis. However, recent data implicate AChE splicing variants in the etiology of complex diseases such as AD and MG. Despite the large arsenal of anti-AChE drugs, therapeutic inhibitors are primarily targeted towards an active site shared by all variants. In contrast, anti-sense oligonucleotides attack unique mRNA sequences rather than tertiary protein structures. AS-ODNs thus offer a means to target gene expression in a highly discriminative manner using very low concentrations of drug. In light of the likely role(s) of specific AChE variants in various diseases affecting cholinergic neurotransmission, the potential contribution that anti-sense technology can make towards improved approaches to anti-AChE therapeutics deserves serious attention.

Acetylcholinesterase↗

PubMed2006

[Prediction of the possible tertiary structure alterations of p53 protein following point mutation in p53 gene condon 282 in lung cancer cells].

This study was carried out to predict the possible tertiary structure alterations of p53 protein after point mutation of p53 gene condon 282 in lung cancer cells based on the latest 3D structure analysis platform series of Phyre software. It was found that the p53 gene condon 282 mutation (Arg/Leu) may destabilize the H2 helix and DNA binding in the major groove by compromising the contacts of p53 protein with the beta-hairpin of DNA binding surface.

Amino Acid Sequence↗

PubMed1992

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

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

Amino Acid Sequence↗

PubMed2006

Abundance of intrinsic disorder in protein associated with cardiovascular disease.

Evidence that many protein regions and even entire proteins lacking stable tertiary and/or secondary structure in solution (i.e., intrinsically disordered proteins) might be involved in protein-protein interactions, regulation, recognition, and signal transduction is rapidly accumulating. These signaling proteins play a crucial role in the development of several pathological conditions, including cancer. To test a hypothesis that intrinsic disorder is also abundant in cardiovascular disease (CVD), a data set of 487 CVD-related proteins was extracted from SWISS-PROT. CVD-related proteins are depleted in major order-promoting residues (Trp, Phe, Tyr, Ile, and Val) and enriched in some disorder-promoting residues (Arg, Gln, Ser, Pro, and Glu). The application of a neural network predictor of natural disordered regions (PONDR VL-XT) together with cumulative distribution function (CDF) analysis, charge-hydropathy plot (CH plot) analysis, and alpha-helical molecular recognition feature (alpha-MoRF) indicator revealed that CVD-related proteins are enriched in intrinsic disorder. In fact, the percentage of proteins with 30 or more consecutive residues predicted by PONDR VL-XT to be disordered was 57 +/- 4% for CVD-associated proteins. This value is close that described earlier for signaling proteins (66 +/- 6%) and is significantly larger than the content of intrinsic disorder in eukaryotic proteins from SWISS-PROT (47 +/- 4%) and in nonhomologous protein segments with a well-defined three-dimensional structure (13 +/- 4%). Furthermore, CDF and CH-plot analyses revealed that 120 and 36 CVD-related proteins, respectively, are wholly disordered. This high level of intrinsic disorder could be important for the function of CVD-related proteins and for the control and regulation of processes associated with cardiovascular disease. In agreement with this hypothesis, 198 alpha-MoRFs were predicted in 101 proteins from the CVD data set. A comparison of disorder predictions with the experimental structural and functional data for a subset of the CVD-associated proteins indicated good agreement between predictions and observations. Thus, our data suggest that intrinsically disordered proteins might play key roles in cardiovascular disease.

3',5'-Cyclic-AMP Phosphodiesterases↗

PubMed2002

Thermal stability: a means to assure tertiary structure in therapeutic proteins.

To be both safe and effective, a therapeutic product must have the correct chemical structure and be free of harmful contaminants. Structure in protein therapeutic products, however, implies not only the correct sequence of amino acids (primary structure) but also the proper folding of that amino acid chain in three-dimensional space (tertiary structure). This work is part of a general strategy to develop a battery of physico-chemical methods that could give assurances of structure (and hence function) in formulated therapeutic proteins in the absence of in vivo data. It focuses on recombinant human growth hormone (rhGH), a well-characterized therapeutic protein, and examines the utility of thermodynamic parameters in assessing its tertiary structure. Resistance of solutions of formulated rhGH to thermal denaturation was followed using Fourier Transform Infrared Spectroscopy (FTIR) by observing decreases in total helicity and increases in intermolecular beta-sheet formation. Under conditions known to induce changes in the intra-molecular ionic and H-bonding patterns stabilizing the tertiary structure but not affecting the protein's secondary structure or global fold, we have observed upwards of a 12 degrees C shift in the melting temperature of the protein. Furthermore, our results indicated that the T(m) of unfolding of rhGH was sensitive to much more subtle changes in the protein structure. Thus, resistance to thermal denaturation may well be a useful means to measure structure in formulations of well-characterized therapeutic proteins.

Deuterium↗