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Biomedical subjects

Robert Powers

Publications and source records attributed to Robert Powers.

At least 19 recordsLinked to original sources
PubMed2006

FAST-NMR: functional annotation screening technology using NMR spectroscopy.

An abundance of protein structures emerging from structural genomics and the Protein Structure Initiative (PSI) are not amenable to ready functional assignment because of a lack of sequence and structural homology to proteins of known function. We describe a high-throughput NMR methodology (FAST-NMR) to annotate the biological function of novel proteins through the structural and sequence analysis of protein-ligand interactions. This is based on basic tenets of biochemistry where proteins with similar functions will have similar active sites and exhibit similar ligand binding interactions, despite global differences in sequence and structure. Protein-ligand interactions are determined through a tiered NMR screen using a library composed of compounds with known biological activity. A rapid co-structure is determined by combining the experimental identification of the ligand binding site from NMR chemical shift perturbations with the protein-ligand docking program AutoDock. Our CPASS (Comparison of Protein Active Site Structures) software and database are then used to compare this active site with proteins of known function. The methodology is demonstrated using unannotated protein SAV1430 from Staphylococcus aureus.

Amino Acid Sequence↗
PubMed2006

Comparison of protein active site structures for functional annotation of proteins and drug design.

Rapid and accurate functional assignment of novel proteins is increasing in importance, given the completion of numerous genome sequencing projects and the vastly expanding list of unannotated proteins. Traditionally, global primary-sequence and structure comparisons have been used to determine putative function. These approaches, however, do not emphasize similarities in active site configurations that are fundamental to a protein's activity and highly conserved relative to the global and more variable structural features. The Comparison of Protein Active Site Structures (CPASS) database and software enable the comparison of experimentally identified ligand-binding sites to infer biological function and aid in drug discovery. The CPASS database comprises the ligand-defined active sites identified in the protein data bank, where the CPASS program compares these ligand-defined active sites to determine sequence and structural similarity without maintaining sequence connectivity. CPASS will compare any set of ligand-defined protein active sites, irrespective of the identity of the bound ligand.

Adenosine Triphosphate↗
PubMed2006

A topology-constrained distance network algorithm for protein structure determination from NOESY data.

This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology-constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published.

Algorithms↗
PubMed2006

NMR metabolic profiling of Aspergillus nidulans to monitor drug and protein activity.

We describe a general protocol for using comparative NMR metabolomics data to infer in vivo efficacy, specificity and toxicity of chemical leads within a drug discovery program. The methodology is demonstrated using Aspergillus nidulans to monitor the activity of urate oxidase and orotidine-5'-phosphate decarboxylase and the impact of 8-azaxanthine, an inhibitor of urate oxidase. 8-azaxanthine is shown to inhibit A. nidulans hyphal growth by in vivo inactivation of urate oxidase.

Animals↗
PubMed2006

Design and characterization of a functional library for NMR screening against novel protein targets.

In the past few years, NMR has been extensively utilized as a screening tool for drug discovery using various types of compound libraries. The designs of NMR specific chemical libraries that utilize a fragment-based approach based on drug-like characteristics have been previously reported. In this article, a new type of compound library will be described that focuses on aiding in the functional annotation of novel proteins that have been identified from various ongoing genomics efforts. The NMR functional chemical library is comprised of small molecules with known biological activity such as: co-factors, inhibitors, metabolites and substrates. This functional library was developed through an extensive manual effort of mining several databases based on known ligand interactions with protein systems. In order to increase the efficiency of screening the NMR functional library, the compounds are screened as mixtures of 3-4 compounds that avoids the need to deconvolute positive hits by maintaining a unique NMR resonance and function for each compound in the mixture. The functional library has been used in the identification of general biological function of hypothetical proteins identified from the Protein Structure Initiative.

Binding Sites↗
PubMed2005

Negative impact of noise on the principal component analysis of NMR data.

Principal component analysis (PCA) is routinely applied to the study of NMR based metabolomic data. PCA is used to simplify the examination of complex metabolite mixtures obtained from biological samples that may be composed of hundreds or thousands of chemical components. PCA is primarily used to identify relative changes in the concentration of metabolites to identify trends or characteristics within the NMR data that permits discrimination between various samples that differ in their source or treatment. A common concern with PCA of NMR data is the potential over emphasis of small changes in high concentration metabolites that would over-shadow significant and large changes in low-concentration components that may lead to a skewed or irrelevant clustering of the NMR data. We have identified an additional concern, very small and random fluctuations within the noise of the NMR spectrum can also result in large and irrelevant variations in the PCA clustering. Alleviation of this problem is obtained by simply excluding the noise region from the PCA by a judicious choice of a threshold above the spectral noise.

Adenosine Triphosphate↗
PubMed2005

Protein NMR recall, precision, and F-measure scores (RPF scores): structure quality assessment measures based on information retrieval statistics.

One of the most important challenges in modern protein NMR is the development of fast and sensitive structure quality assessment measures that can be used to evaluate the "goodness-of-fit" of the 3D structure with NOESY data, to indicate the correctness of the fold and accuracy of the resulting structure. Quality assessment is especially critical for automated NOESY interpretation and structure determination approaches. This paper describes new NMR quality assessment scores, including Recall, Precision, and F-measure scores (referred to here are "NMR RPF" scores), which quickly provide global measures of the goodness-of-fit of the 3D structures with NOESY peak lists using methods from information retrieval statistics. The sensitivity of the F-measure is improved using a scaled Fold Discriminating Power (DP) score. These statistical RPF scores are quite rapid to compute since NOE assignments and complete relaxation matrix calculations are not required. A graphical method for site-specific assessment of structure quality based on the Precision statistic is also described. These statistical measures are demonstrated to be valuable for assessing protein NMR structure accuracy. Their relationships to other proposed NMR "R-factors" and structure quality assessment scores are also discussed.

Databases, Protein↗
PubMed2005

Determining the optimal size of small molecule mixtures for high throughput NMR screening.

High-throughput screening (HTS) using NMR spectroscopy has become a common component of the drug discovery effort and is widely used throughout the pharmaceutical industry. NMR provides additional information about the nature of small molecule-protein interactions compared to traditional HTS methods. In order to achieve comparable efficiency, small molecules are often screened as mixtures in NMR-based assays. Nevertheless, an analysis of the efficiency of mixtures and a corresponding determination of the optimum mixture size (OMS) that minimizes the amount of material and instrumentation time required for an NMR screen has been lacking. A model for calculating OMS based on the application of the hypergeometric distribution function to determine the probability of a "hit" for various mixture sizes and hit rates is presented. An alternative method for the deconvolution of large screening mixtures is also discussed. These methods have been applied in a high-throughput NMR screening assay using a small, directed library.

Chemistry, Pharmaceutical↗
PubMed2005

An integrated platform for automated analysis of protein NMR structures.

Recent developments provide automated analysis of NMR assignments and three-dimensional (3D) structures of proteins. These approaches are generally applicable to proteins ranging from about 50 to 150 amino acids. In this chapter, we summarize progress by the Northeast Structural Genomics Consortium in standardizing the NMR data collection process for protein structure determination and in building an integrated platform for automated protein NMR structure analysis. Our integrated platform includes the following principal steps: (1) standardized NMR data collection, (2) standardized data processing (including spectral referencing and Fourier transformation), (3) automated peak picking and peak list editing, (4) automated analysis of resonance assignments, (5) automated analysis of NOESY data together with 3D structure determination, and (6) methods for protein structure validation. In particular, the software AutoStructure for automated NOESY data analysis is described in this chapter, together with a discussion of practical considerations for its use in high-throughput structure production efforts. The critical area of data quality assessment has evolved significantly over the past few years and involves evaluation of both intermediate and final peak lists, resonance assignments, and structural information derived from the NMR data. Methods for quality control of each of the major automated analysis steps in our platform are also discussed. Despite significant remaining challenges, when good quality data are available, automated analysis of protein NMR assignments and structures with this platform is both fast and reliable.

Data Interpretation, Statistical↗
PubMed2005

Solution structure of Archaeglobus fulgidis peptidyl-tRNA hydrolase (Pth2) provides evidence for an extensive conserved family of Pth2 enzymes in archea, bacteria, and eukaryotes.

The solution structure of protein AF2095 from the thermophilic archaea Archaeglobus fulgidis, a 123-residue (13.6-kDa) protein, has been determined by NMR methods. The structure of AF2095 is comprised of four alpha-helices and a mixed beta-sheet consisting of four parallel and anti-parallel beta-strands, where the alpha-helices sandwich the beta-sheet. Sequence and structural comparison of AF2095 with proteins from Homo sapiens, Methanocaldococcus jannaschii, and Sulfolobus solfataricus reveals that AF2095 is a peptidyl-tRNA hydrolase (Pth2). This structural comparison also identifies putative catalytic residues and a tRNA interaction region for AF2095. The structure of AF2095 is also similar to the structure of protein TA0108 from archaea Thermoplasma acidophilum, which is deposited in the Protein Data Bank but not functionally annotated. The NMR structure of AF2095 has been further leveraged to obtain good-quality structural models for 55 other proteins. Although earlier studies have proposed that the Pth2 protein family is restricted to archeal and eukaryotic organisms, the similarity of the AF2095 structure to human Pth2, the conservation of key active-site residues, and the good quality of the resulting homology models demonstrate a large family of homologous Pth2 proteins that are conserved in eukaryotic, archaeal, and bacterial organisms, providing novel insights in the evolution of the Pth and Pth2 enzyme families.

Archaea↗
PubMed2004

Identification of novel estrogen receptor alpha antagonists.

We have identified novel estrogen receptor alpha (ERalpha) antagonists using both cell-based and computer-based virtual screening strategies. A mammalian two-hybrid screen was used to select compounds that disrupt the interaction between the ERalpha ligand binding domain (LBD) and the coactivator SRC-3. A virtual screen was designed to select compounds that fit onto the LxxLL peptide-binding surface of the receptor, based on the X-ray crystal structure of the ERalpha LBD complexed with a LxxLL peptide. All selected compounds effectively inhibited 17-beta-estradiol induced coactivator recruitment with potency ranging from nano-molar to micromolar. However, in contrast to classical ER antagonists, these novel inhibitors poorly displace estradiol in the ER-ligand competition assay. Nuclear magnetic resonance (NMR) suggested direct binding of these compounds to the receptors pre-complexed with estradiol and further demonstrated that no estradiol displacement occurred. Partial proteolytic enzyme digestion revealed that, when compared with 17-beta-estradiol- and 4 hydroxy-tamoxifen (4-OHT) bound receptors, at least one of these compounds might induce a unique receptor conformation. These small molecules may represent new classes of ER antagonists, and may have the potential to provide an alternative for the current anti-estrogen therapy.

Acetyltransferases↗
PubMed2004

The application of x-ray, NMR, and molecular modeling in the design of MMP inhibitors.

The following review discusses the successful application of X-ray, NMR, and molecular modeling in the design of potent and selective inhibitors of matrix metalloproteinases (MMPs) and TNFalpha-converting enzyme (TACE) from Wyeth. The importance of protein and ligand mobility as it impacts structure-based design is also discussed. The MMPs are an active target for a variety of diseases, including cancer and arthritis.

ADAM Proteins↗
PubMed2002

Impact of mobility on structure-based drug design for the MMPs.

Structure-based approaches for drug design generally do not incorporate solvent effects and dynamic information to predict inhibitor-binding affinity because of practical limitations. The matrix metalloproteinases (MMPs) have previously been demonstrated to exhibit significant mobility in their active sites. This dynamic characteristic significantly complicates the drug design process based on static structures, which was clearly observed for a class of hydroxamic acids containing a butynyl moiety. Compound 1 was expected to be selective against MMP-1 based on predicted steric clashes between the butynyl P1' group and the S1' pocket, but the observation of complex inhibitor dynamics in the NMR structure of MMP-1:1 provides an explanation for the low nanomolar binding to MMP-1.

Binding Sites↗
PubMed2002

Applications of NMR to structure-based drug design in structural genomics.

Structural genomics is poised to have a tremendous impact on traditional structure-based drug design programs. As a result, there is a growing need to obtain rapid structural information in a reliable form that is amenable to rational drug design. In this manner, NMR has been expanding and evolving its role in aiding the design process. A variety of NMR methodologies that cover a range of inherent resolution are described in the context of structure-based drug design in the era of structural genomics.

Chromatography, Gel↗