Biomedical subjects

Daniel S Sem

Publications and source records attributed to Daniel S Sem.

11 recordsLinked to original sources

PubMed2006

A dithio-coupled kinase and ATPase assay.

Kinases and ATPases produce adenosine diphosphate (ADP) as a common product, so an assay that detects ADP would provide a universal means for activity-based screening of enzymes in these families. Because it is known that most kinases accept ATPbetaS (sulfur on the beta-phosphorous) as a substrate in place of adenosine triphosphate (ATP), the authors have developed a continuous assay using this substrate, with detection of the ADPbetaS product using dithio reagents. Such an assay is possible because dithio groups react selectively with ADPbetaS and not with ATPbetaS. Thiol detection was done using both Ellman's reagent (DTNB) and a recently developed fluorescent dithio reagent, DSSA. Therefore, the assay can be run in both absorbance and fluorescence detection modes. The assay was used to perform steady-state kinetic analyses of both hexokinase and myosin ATPase. It was also used to demonstrate the diastereoselectivity of hexokinase (R) and myosin ATPase (S) for the isomers of ATPbetaS, consistent with previous results. When run in fluorescence mode using a plate reader, an average Z' value of 0.54 was obtained, suggesting the assay is appropriate for high-throughput screening.

Adenosine Diphosphate↗

PubMed2006

Fluorescence-based detection of thiols in vitro and in vivo using dithiol probes.

Thiols play a central role in maintaining biological homeostasis. Their levels can change dramatically in response to oxidative stress associated with toxic insults, bacterial infection, and disease. Therefore, a reagent that can monitor thiol levels both in vitro and in vivo would be useful for assays and as a biomarker. Such a reagent should (i) be selective for thiols, (ii) be able to penetrate cell walls, and (iii) have a low reduction potential so as not to create oxidative stress in a cell. We have developed such a fluorescent reagent (DSSA) based on a dithiol linker: (i) the use of a dithiol linker makes it selective for thiols; (ii) the use of fluorophores that populate neutral states at physiological pH improves cell wall penetration; and (iii) because of the reagent's low reduction potential (-0.60 V), it will not stress cells oxidatively. For example, 5 microM of reagent is responsive to changes in glutathione levels in the physiologically relevant range of 1 to 10mM, yet this would oxidize less than 1% of cellular glutathione. In Escherichia coli, decreased thiol levels were detected in cells deficient in glutathione synthesis. In zebrafish embryos, the DSSA reagent permitted detection of unusually high thiol levels in the zebrafish chorion.

Animals↗

PubMed2005

Homology-modeled ligand-binding domains of zebrafish estrogen receptors alpha, beta1, and beta2: from in silico to in vivo studies of estrogen interactions in Danio rerio as a model system.

Homology models were constructed for the ligand-binding domains of zebrafish estrogen receptors (zfERs) alpha, beta(1), and beta(2). Estradiol-binding sites are nearly identical in zfERs and their human homologs, suggesting that zebrafish will serve as a good model system for studying human ER-binding drugs. Conversely, studies of endocrine disruptor effects on zebrafish will benefit from the wealth of data available on xenoestrogen interactions with human ERs. Compounds flagged by the Interagency Coordinating Committee on the Validation of Alternative Methods for endocrine disruptor screening were docked into our zfER homology models. Ideally, these in silico docking studies would be complemented with in vivo binding studies. To this end, fluorescently tagged estradiol was docked into zfERalpha and found to bind in the same manner as in human ERalpha, with fluorescein preferentially occupying a region between helices 11 and 12. Fluorescently tagged estradiol was synthesized and was found to localize along the path of primordial germ cell migration in the developing zebrafish embryo 3 d after fertilization, consistent with previous reports of 1) a role for estradiol in sex determination, and 2) the first appearance of ERs 2 d after fertilization. These data provide a foundation for future in silico and in vivo binding studies of estrogen agonists and antagonists with zebrafish ERs.

Amino Acid Sequence↗

PubMed2005

Cofactor fingerprinting with STD NMR to characterize proteins of unknown function: identification of a rare cCMP cofactor preference.

Proteomics efforts have created a need for better strategies to functionally categorize newly discovered proteins. To this end, we have employed saturation transfer difference NMR with pools of closely related cofactors, to determine cofactor preferences. This approach works well for dehydrogenases and has also been applied to cyclic nucleotide-binding proteins. In the latter application, a protein (radial spoke protein-2, RSP2) that plays a central role in forming the radial spoke of Chlamydomonas reinhardtii flagella was shown to bind cCMP. cCMP-binding proteins are rare, although previous reports of their presence in sperm and flagella suggest that cCMP may have a more general role in flagellar function. 31P NMR was used to monitor the preferential hydrolysis of ATP versus GTP, suggesting that RSP2 is a kinase.

Cyclic CMP↗

PubMed2004

Systems-based design of bi-ligand inhibitors of oxidoreductases: filling the chemical proteomic toolbox.

Genomics-driven growth in the number of enzymes of unknown function has created a need for better strategies to characterize them. Since enzyme inhibitors have traditionally served this purpose, we present here an efficient systems-based inhibitor design strategy, enabled by bioinformatic and NMR structural developments. First, we parse the oxidoreductase gene family into structural subfamilies termed pharmacofamilies, which share pharmacophore features in their cofactor binding sites. Then we identify a ligand for this site and use NMR-based binding site mapping (NMR SOLVE) to determine where to extend a combinatorial library, such that diversity elements are directed into the adjacent substrate site. The cofactor mimic is reused in the library in a manner that parallels the reuse of cofactor domains in the oxidoreductase gene family. A library designed in this manner yielded specific inhibitors for multiple oxidoreductases.

Animals↗

PubMed2004

Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective.

Proteomics is the study of the protein complement of a genome and employs a number of newly emerging tools. One such tool is chemical proteomics, which is a branch of proteomics devoted to the exploration of protein function using both in vitro and in vivo chemical probes. Chemical proteomics aims to define protein function and mechanism at the level of directly observed protein-ligand interactions, whereas chemical genomics aims to define the biological role of a protein using chemical knockouts and observing phenotypic changes. Chemical proteomics is therefore traditional mechanistic biochemistry performed in a systems-based manner, using either activity- or affinity-based probes that target proteins related by chemical reactivities or by binding site shape/properties, respectively. Systems are groups of proteins related by metabolic pathway, regulatory pathway or binding to the same ligand. Studies can be based on two main types of proteome samples: pooled proteins (1 mixture of N proteins) or isolated proteins in a given system and studied in parallel (N single protein samples). Although the field of chemical proteomics originated with the use of covalent labeling strategies such as isotope-coded affinity tagging, it is expanding to include chemical probes that bind proteins noncovalently, and to include more methods for observing protein-ligand interactions. This review presents an emerging role for nuclear magnetic resonance spectroscopy in chemical proteomics, both in vitro and in vivo. Applications include: functional proteomics using cofactor fingerprinting to assign proteins to gene families; gene family-based structural characterizations of protein-ligand complexes; gene family-focused design of drug leads; and chemical proteomic probes using nuclear magnetic resonance SOLVE and studies of protein-ligand interactions in vivo.

Magnetic Resonance Spectroscopy↗

PubMed2003

A path from primary protein sequence to ligand recognition.

A novel method to organize protein structural information based solely on sequence is presented. The method clusters proteins into families that correlate with the three-dimensional protein structure and the conformation of the bound ligands. This procedure was applied to nicotinamide adenine dinucleotide [NAD(P)]-utilizing enzymes to identify a total of 94 sequence families, 53 of which are structurally characterized. Each of the structurally characterized proteins within a sequence family correlates to a single protein fold and to a common bound conformation of NAD(P). A wide range of structural folds is identified that recognize NAD(P), including Rossmann folds and beta/alpha barrels. The defined sequence families can be used to identify the type and prevalence of NAD(P)-utilizing enzymes in the proteomes of sequenced organisms. The proteome of Mycobacterium tuberculosis was mined to generate a proteome-wide profile of NAD(P)-utilizing enzymes coded by this organism. This enzyme family comprises approximately 6% of the open reading frames, with the largest subgroup being the Rossmann fold, short-chain dehydrogenases. The preponderance of short-chain dehydrogenases correlates strongly with the phenotype of M. tuberculosis, which is characterized as having one of the most complex prokaryotic cell walls.

Amino Acid Sequence↗

PubMed2002

NMR-based structural characterization of large protein-ligand interactions.

Genomic research on target identification and validation has created a great need for methods that rapidly provide detailed structural information on protein-ligand interactions. We developed a suite of NMR experiments as rapid and efficient tools to provide descriptive structural information on protein-ligand complexes. The methods work with large proteins and in particular cases also without the need for a complete three-dimensional structure. We will show applications with two tetrameric enzymes of 120 and 170 kDa.

Binding Sites↗

PubMed2002

NMR in drug discovery.

NMR spectroscopy has evolved into an important technique in support of structure-based drug design. Here, we survey the principles that enable NMR to provide information on the nature of molecular interactions and, on this basis, we discuss current NMR-based strategies that can identify weak-binding compounds and aid their development into potent, drug-like inhibitors for use as lead compounds in drug discovery.

Drug Design↗

PubMedDate not supplied

Chemical proteomic tool for ligand mapping of CYP antitargets: an NMR-compatible 3D QSAR descriptor in the Heme-Based Coordinate System.

Chemical proteomic strategies strive to probe and understand protein-ligand interactions across gene families. One gene family of particular interest in drug and xenobiotic metabolism are the cytochromes P450 (CYPs), the topic of this article. Although numerous tools exist to probe affinity of CYP-ligand interactions, fewer exist for the rapid experimental characterization of the structural nature of these interactions. As a complement to recent advances in X-ray crystallography, NMR methods are being developed that allow for fairly high throughput characterization of protein-ligand interactions. One especially promising NMR approach involves the use of paramagnetic induced relaxation effects to measure distances of ligand atoms from the heme iron in CYP enzymes. Distances obtained from these T(1) relaxation measurements can be used as a direct source of 1-dimensional structural information or to restrain a ligand docking to generate a 3-dimensional data set. To facilitate such studies, we introduce the concept of the Heme-Based Coordinate System and present how it can be used in combination with NMR T(1) relaxation data to derive 3D QSAR descriptors directly or in combination with in silico docking. These descriptors should have application in defining the binding preferences of CYP binding sites using 3D QSAR models. They are especially well-suited for the biasing of fragment assembly and combinatorial chemistry drug design strategies, to avoid fragment or reagent combinations with enhanced affinity for CYP antitargets.

Computer Simulation↗

PubMedDate not supplied

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Algorithms↗