Statistical potentials for fold assessment

A protein structure model generally needs to be evaluated to assess whether or not it has the correct fold. To improve fold assessment, four types of a residue-level statistical potential were optimized, including distance-dependent, contact, Phi/Psi dihedral angle, and accessible surface statistical potentials. Approximately 10,000 test models with the correct and incorrect folds were built by automated comparative modeling of protein sequences of known structure. The criterion used to discriminate between the correct and incorrect models was the Z-score of the model energy. The performance of a Z-score was determined as a function of many variables in the derivation and use of the corresponding statistical potential. The performance was measured by the fractions of the correctly and incorrectly assessed test models. The most discriminating combination of any one of the four tested potentials is the sum of the normalized distance-dependent and accessible surface potentials. The distance-dependent potential that is optimal for assessing models of all sizes uses both C(alpha) and C(beta) atoms as interaction centers, distinguishes between all 20 standard residue types, has the distance range of 30 A, and is derived and used by taking into account the sequence separation of the interacting atom pairs. The terms for the sequentially local interactions are significantly less informative than those for the sequentially nonlocal interactions. The accessible surface potential that is optimal for assessing models of all sizes uses C(beta) atoms as interaction centers and distinguishes between all 20 standard residue types. The performance of the tested statistical potentials is not likely to improve significantly with an increase in the number of known protein structures used in their derivation. The parameters of fold assessment whose optimal values vary significantly with model size include the size of the known protein structures used to derive the potential and the distance range of the accessible surface potential. Fold assessment by statistical potentials is most difficult for the very small models. This difficulty presents a challenge to fold assessment in large-scale comparative modeling, which produces many small and incomplete models. The results described in this study provide a basis for an optimal use of statistical potentials in fold assessment.     

Overexpression of 15-lipoxygenase-1 induces growth arrest through phosphorylation of p53 in human colorectal cancer cells

To investigate the function of 15-lipoxygenase-1 (15-LOX-1) in human colorectal cancer, we overexpressed 15-LOX-1 in HCT-116 human colorectal cancer cells. Clones expressing the highest levels of 15-LOX-1 displayed reduced viability compared with the HCT-116-Vector control cells. Further, by cell cycle gene array analyses, the cyclin-dependent kinase inhibitor p21WAF1/CIP1 and MDM2 genes were up-regulated in 15-LOX-1-overexpressing cells. The induction of p21(WAF1/CIP1) and MDM2 were linked to activation of p53 by 15-LOX-1, as there was a dramatic induction of phosphorylated p53 (Ser15) in 15-LOX-1-overesxpressing cells. However, the 15-LOX-1 metabolites 13(S)-hydroxyoctadecadienoic acid and 15(S)-hydroxyeicosatetraenoic acid failed to induce phosphorylation of p53 at Ser15, and the 15-LOX-1 inhibitor PD146176 did not inhibit the phosphorylation of p53 at Ser15 in 15-LOX-1-overexpressing cells. Nonetheless, the growth-inhibitory effects of 15-LOX-1 were p53 dependent, as 15-LOX-1 overexpression had no effect on cell growth in p53 (-/-) HCT-116 cells. Finally, treatment of HCT-116-15-LOX-1 cells with different kinase inhibitors suggested that the effects of 15-LOX-1 on p53 phosphorylation and activation were due to effects on DNA-dependent protein kinase. Collectively, these findings suggest a new mechanism to explain the biological activity of 15-LOX-1, where 15-LOX plays a stoichiometric role in activating a DNA-dependent protein kinase-dependent pathway that leads to p53-dependent growth arrest.     

EVA: continuous automatic evaluation of protein structure prediction servers.

Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. AVAILABILITY: http://cubic.bioc.columbia.edu/eva. CONTACT: eva@cubic.bioc.columbia.edu     

New York-Structural GenomiX Research Consortium (NYSGXRC): A Large Scale Center for the Protein Structure Initiative

Structural GenomiX, Inc. (SGX), four New York area institutions, and two University of California schools have formed the New York Structural GenomiX Research Consortium (NYSGXRC), an industrial/academic Research Consortium that exploits individual core competencies to support all aspects of the NIH-NIGMS funded Protein Structure Initiative (PSI), including protein family classification and target selection, generation of protein for biophysical analyses, sample preparation for structural studies, structure determination and analyses, and dissemination of results. At the end of the PSI Pilot Study Phase (PSI-1), the NYSGXRC will be capable of producing 100–200 experimentally determined protein structures annually. All Consortium activities can be scaled to increase production capacity significantly during the Production Phase of the PSI (PSI-2). The Consortium utilizes both centralized and de-centralized production teams with clearly defined deliverables and hand-off procedures that are supported by a web-based target/sample tracking system (SGX Laboratory Information Data Management System, LIMS, and NYSGXRC Internal Consortium Experimental Database, ICE-DB). Consortium management is provided by an Executive Committee, which is composed of the PI and all Co-PIs. Progress to date is tracked on a publicly available Consortium web site (http://www.nysgxrc.org) and all DNA/protein reagents and experimental protocols are distributed freely from the New York City Area institutions. In addition to meeting the requirements of the Pilot Study Phase and preparing for the Production Phase of the PSI, the NYSGXRC aims to develop modular technologies that are transferable to structural biology laboratories in both academe and industry. The NYSGXRC PI and Co-PIs intend the PSI to have a transforming effect on the disciplines of X-ray crystallography and NMR spectroscopy of biological macromolecules. Working with other PSI-funded Centers, the NYSGXRC seeks to create the structural biology laboratory of the future. Herein, we present an overview of the organization of the NYSGXRC and describe progress toward development of a high-throughput Gene→Structure platform. An analysis of current and projected consortium metrics reflects progress to date and delineates opportunities for further technology development.     

Understanding protein folding via free-energy surfaces from theory and experiment

The ability of protein molecules to fold into their highly structured functional states is one of the most remarkable evolutionary achievements of biology. In recent years, our understanding of the way in which this complex self-assembly process takes place has increased dramatically. Much of the reason for this advance has been the development of energy surfaces (landscapes), which allow the folding reaction to be described and visualized in a meaningful manner. Analysis of these surfaces, derived from the constructive interplay between theory and experiment, has led to the development of a unified mechanism for folding and a recognition of the underlying factors that control the rates and products of the folding process.     

PIBASE: a comprehensive database of structurally defined protein interfaces

MOTIVATION: In recent years, the Protein Data Bank (PDB) has experienced rapid growth. To maximize the utility of the high resolution protein-protein interaction data stored in the PDB, we have developed PIBASE, a comprehensive relational database of structurally defined interfaces between pairs of protein domains. It is composed of binary interfaces extracted from structures in the PDB and the Probable Quaternary Structure server using domain assignments from the Structural Classification of Proteins and CATH fold classification systems. RESULTS: PIBASE currently contains 158,915 interacting domain pairs between 105,061 domains from 2125 SCOP families. A diverse set of geometric, physiochemical and topologic properties are calculated for each complex, its domains, interfaces and binding sites. A subset of the interface properties are used to remove interface redundancy within PDB entries, resulting in 20,912 distinct domain-domain interfaces. The complexes are grouped into 989 topological classes based on their patterns of domain-domain contacts. The binary interfaces and their corresponding binding sites are categorized into 18,755 and 30,975 topological classes, respectively, based on the topology of secondary structure elements. The utility of the database is illustrated by outlining several current applications. AVAILABILITY: The database is accessible via the world wide web at http://salilab.org/pibase SUPPLEMENTARY INFORMATION: http://salilab.org/pibase/suppinfo.html.     

Definition of general topological equivalence in protein structures. A procedure involving comparison of properties and relationships through simulated annealing and dynamic programming

A protein is defined as an indexed string of elements at each level in the hierarchy of protein structure: sequence, secondary structure, super-secondary structure, etc. The elements, for example, residues or secondary structure segments such as helices or beta-strands, are associated with a series of properties and can be involved in a number of relationships with other elements. Element-by-element dissimilarity matrices are then computed and used in the alignment procedure based on the sequence alignment algorithm of Needleman & Wunsch, expanded by the simulated annealing technique to take into account relationships as well as properties. The utility of this method for exploring the variability of various aspects of protein structure and for comparing distantly related proteins is demonstrated by multiple alignment of serine proteinases, aspartic proteinase lobes and globins.     

Structural-functional organization of the SV40 virus chromosome. II. Characteristics of viral genome containing deletion in the regulatory region

Structure of SV40 wild type virus genome differing from the well known 776 strain has been characterized. This particular strain (SV40) was used previously for viral chromatin analysis. We show here that SV40 strain differs from 776 strain by deletion in the beginning of the "late" region (enhancer). Restriction nucleases mapping and nucleotide sequencing through this region reveal the absence of one full-length copy of 72 bp repeat.     

The active DNA-PK holoenzyme occupies a tensed state in a staggered synaptic complex

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