Journal of structural and functional genomics最新文献

Annotation of any newly determined protein sequence depends on the pairwise sequence identity with known sequences. However, for the twilight zone sequences which have only 15-25% identity, the pair-wise comparison methods are inadequate and the annotation becomes a challenging task. Such sequences can be annotated by using methods that recognize their fold. Bowie et al. described a 3D1D profile method in which the amino acid sequences that fold into a known 3D structure are identified by their compatibility to that known 3D structure. We have improved the above method by using the predicted secondary structure information and employ it for fold recognition from the twilight zone sequences. In our Protein Secondary Structure 3D1D (PSS-3D1D) method, a score (w) for the predicted secondary structure of the query sequence is included in finding the compatibility of the query sequence to the known fold 3D structures. In the benchmarks, the PSS-3D1D method shows a maximum of 21% improvement in predicting correctly the α + β class of folds from the sequences with twilight zone level of identity, when compared with the 3D1D profile method. Hence, the PSS-3D1D method could offer more clues than the 3D1D method for the annotation of twilight zone sequences. The web based PSS-3D1D method is freely available in the PredictFold server at http://bioinfo.bdu.ac.in/servers/ .

Matrix metalloproteinase (MMPs) and disintegrin and metalloprotease (ADAMs) belong to the zinc-dependent metalloproteinase family of proteins. These proteins participate in various physiological and pathological states. Thus, prediction of these proteins using amino acid sequence would be helpful. We have developed a method to predict these proteins based on the features derived from Chou's pseudo amino acid composition (PseAAC) server and support vector machine (SVM) as a powerful machine learning approach. With this method, for ADAMs and MMPs families, an overall accuracy and Matthew's correlation coefficient (MCC) of 95.89 and 0.90% were achieved respectively. Furthermore, the method is able to predict two major subclasses of MMP family; Furin-activated secreted MMPs and Type II trans-membrane; with MCC of 0.89 and 0.91%, respectively. The overall accuracy for Furin-activated secreted MMPs and Type II trans-membrane was 98.18 and 99.07, respectively. Our data demonstrates an effective classification of Metalloproteinase family based on the concept of PseAAC and SVM.

The solution NMR structure of protein MED25(391-543), comprising the activator interacting domain (ACID) of subunit 25 of the human mediator, is presented along with the measurement of polypeptide backbone heteronuclear 15N-{1H} NOEs to identify fast internal motional modes. This domain interacts with the acidic transactivation domains of Herpes simplex type 1 (HSV-1) protein VP16 and the Varicella-zoster virus (VZV) major transactivator protein IE62, which initiate transcription of viral genes. The structure is similar to the β-barrel domains of the human protein Ku and the SPOC domain of human protein SHARP, and provides a starting point to understand the structural biology of initiation of HSV-1 and VZV gene activation. Homology models built for the two ACID domains of the prostate tumor overexpressed (PTOV1) protein using the structure of MED25(391-543) as a template suggest that differential biological activities of the ACID domains in MED25 and PTOV1 arise from modulation of quite similar protein-protein interactions by variable residues grouped around highly conserved charged surface areas.

A structure of the apo-form of the putative transcriptional regulator SCO0520 from Streptomyces coelicolor A3(2) was determined at 1.8 Å resolution. SCO0520 belongs to the TetR family of regulators. In the crystal lattice, the asymmetric unit contains two monomers that form an Ω-shaped dimer. The distance between the two DNA-recognition domains is much longer than the corresponding distances in the known structures of other TetR family proteins. In addition, the subunits in the dimer have different conformational states, resulting in different relative positions of the DNA-binding and regulatory domains. Similar conformational modifications are observed in other TetR regulators and result from ligand binding. These studies provide information about the flexibility of SCO0520 molecule and its putative biological function.

Protein domain family YabP (PF07873) is a family of small protein domains that are conserved in a wide range of bacteria and involved in spore coat assembly during the process of sporulation. The 62-residue fragment of Dsy0195 from Desulfitobacterium hafniense, which belongs to the YabP family, exists as a homodimer in solution under the conditions used for structure determination using NMR spectroscopy. The structure of the Dsy0195 homodimer contains two identical 62-residue monomeric subunits, each consisting of five anti-parallel beta strands (β1, 23-29; β2, 31-38; β3, 41-46; β4, 49-59; β5, 69-80). The tertiary structure of the Dsy0195 monomer adopts a cylindrical fold composed of two beta sheets. The two monomer subunits fold into a homodimer about a single C2 symmetry axis, with the interface composed of two anti-parallel beta strands, β1-β1' and β5b-β5b', where β5b refers to the C-terminal half of the bent β5 strand, without any domain swapping. Potential functional regions of the Dsy0195 structure were predicted based on conserved sequence analysis. The Dsy0195 structure reported here is the first representative structure from the YabP family.

Assignment of backbone amide proton resonances is one of the most time-consuming stages of any protein NMR study when the protein samples behave non-ideally. A robust and convenient NMR procedure for analyzing spectra of marginal-to-low quality is helpful for high-throughput structure determination. The 14N selective- and inverse-labeling method is a candidate solution. Here, we present a simplified protocol for assigning protein backbone amide NMR signals. When 14N inversely labeled residues are present in a protein, their backbone NH cross peaks vanish from the protein's 1H-(15)N HSQC spectrum, and thus, their chemical shifts can be readily identified by a process of elimination. Some metabolically related amino acids, for example, Ile, Leu, and Val, cannot be individually incorporated but can be inversely labeled together. We optimized and simplified the protocol and M9-based medium formula for the 14N selective- and inverse-labeling method without any additives. Our approach should be cost-effective, because the method could be additively applied stepwise, even when the proteins of interest were found to be non-ideal.

The atomic-level structural properties of proteins, such as bond lengths, bond angles, and torsion angles, have been well studied and understood based on either chemistry knowledge or statistical analysis. Similar properties on the residue-level, such as the distances between two residues and the angles formed by short sequences of residues, can be equally important for structural analysis and modeling, but these have not been examined and documented on a similar scale. While these properties are difficult to measure experimentally, they can be statistically estimated in meaningful ways based on their distributions in known proteins structures. Residue-level structural properties including various types of residue distances and angles are estimated statistically. A software package is built to provide direct access to the statistical data for the properties including some important correlations not previously investigated. The distributions of residue distances and angles may vary with varying sequences, but in most cases, are concentrated in some high probability ranges, corresponding to their frequent occurrences in either α-helices or β-sheets. Strong correlations among neighboring residue angles, similar to those between neighboring torsion angles at the atomic-level, are revealed based on their statistical measures. Residue-level statistical potentials can be defined using the statistical distributions and correlations of the residue distances and angles. Ramachandran-like plots for strongly correlated residue angles are plotted and analyzed. Their applications to structural evaluation and refinement are demonstrated. With the increase in both number and quality of known protein structures, many structural properties can be derived from sets of protein structures by statistical analysis and data mining, and these can even be used as a supplement to the experimental data for structure determinations. Indeed, the statistical measures on various types of residue distances and angles provide more systematic and quantitative assessments on these properties, which can otherwise be estimated only individually and qualitatively. Their distributions and correlations in known protein structures show their importance for providing insights into how proteins may fold naturally to various residue-level structures.

We propose a novel method of calculation of free energy for coarse grained models of proteins by combining our newly developed multibody potentials with entropies computed from elastic network models of proteins. Multi-body potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Combining four-body non-sequential, four-body sequential and pairwise short range potentials with optimized weights for each term, our coarse-grained potential improved recognition of native structure among misfolded decoys, outperforming all other contact potentials for CASP8 decoy sets and performance comparable to the fully atomic empirical DFIRE potentials. By combing statistical contact potentials with entropies from elastic network models of the same structures we can compute free energy changes and improve coarse-grained modeling of protein structure and dynamics. The consideration of protein flexibility and dynamics should improve protein structure prediction and refinement of computational models. This work is the first to combine coarse-grained multibody potentials with an entropic model that takes into account contributions of the entire structure, investigating native-like decoy selection.

As part of the Seattle Structural Genomics Center for Infectious Disease, we seek to enhance structural genomics with ligand-bound structure data which can serve as a blueprint for structure-based drug design. We have adapted fragment-based screening methods to our structural genomics pipeline to generate multiple ligand-bound structures of high priority drug targets from pathogenic organisms. In this study, we report fragment screening methods and structure determination results for 2C-methyl-D-erythritol-2,4-cyclo-diphosphate (MECP) synthase from Burkholderia pseudomallei, the gram-negative bacterium which causes melioidosis. Screening by nuclear magnetic resonance spectroscopy as well as crystal soaking followed by X-ray diffraction led to the identification of several small molecules which bind this enzyme in a critical metabolic pathway. A series of complex structures obtained with screening hits reveal distinct binding pockets and a range of small molecules which form complexes with the target. Additional soaks with these compounds further demonstrate a subset of fragments to only bind the protein when present in specific combinations. This ensemble of fragment-bound complexes illuminates several characteristics of MECP synthase, including a previously unknown binding surface external to the catalytic active site. These ligand-bound structures now serve to guide medicinal chemists and structural biologists in rational design of novel inhibitors for this enzyme.