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Search Results: 1 - 10 of 326531 matches for " Debra S. Goldberg "
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Questioning the Ubiquity of Neofunctionalization
Todd A. Gibson ,Debra S. Goldberg
PLOS Computational Biology , 2009, DOI: 10.1371/journal.pcbi.1000252
Abstract: Gene duplication provides much of the raw material from which functional diversity evolves. Two evolutionary mechanisms have been proposed that generate functional diversity: neofunctionalization, the de novo acquisition of function by one duplicate, and subfunctionalization, the partitioning of ancestral functions between gene duplicates. With protein interactions as a surrogate for protein functions, evidence of prodigious neofunctionalization and subfunctionalization has been identified in analyses of empirical protein interactions and evolutionary models of protein interactions. However, we have identified three phenomena that have contributed to neofunctionalization being erroneously identified as a significant factor in protein interaction network evolution. First, self-interacting proteins are underreported in interaction data due to biological artifacts and design limitations in the two most common high-throughput protein interaction assays. Second, evolutionary inferences have been drawn from paralog analysis without consideration for concurrent and subsequent duplication events. Third, the theoretical model of prodigious neofunctionalization is unable to reproduce empirical network clustering and relies on untenable parameter requirements. In light of these findings, we believe that protein interaction evolution is more persuasively characterized by subfunctionalization and self-interactions.
A First Attempt to Bring Computational Biology into Advanced High School Biology Classrooms
Suzanne Renick Gallagher,William Coon,Kristin Donley,Abby Scott,Debra S. Goldberg
PLOS Computational Biology , 2011, DOI: 10.1371/journal.pcbi.1002244
Abstract: Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of growing concern to the computational biology community and biology teachers who would like to acquaint their students with updated approaches in the discipline. We present a first attempt to correct this absence by introducing a computational biology element to teach genetic evolution into advanced biology classes in two local high schools. Our primary goal was to show students how computation is used in biology and why a basic understanding of computation is necessary for research in many fields of biology. This curriculum is intended to be taught by a computational biologist who has worked with a high school advanced biology teacher to adapt the unit for his/her classroom, but a motivated high school teacher comfortable with mathematics and computing may be able to teach this alone. In this paper, we present our curriculum, which takes into consideration the constraints of the required curriculum, and discuss our experiences teaching it. We describe the successes and challenges we encountered while bringing this unit to high school students, discuss how we addressed these challenges, and make suggestions for future versions of this curriculum.We believe that our curriculum can be a valuable seed for further development of computational activities aimed at high school biology students. Further, our experiences may be of value to others teaching computational biology at this level. Our curriculum can be obtained at http://ecsite.cs.colorado.edu/?page_id=1?49#biology or by contacting the authors.
Improving protein function prediction methods with integrated literature data
Aaron P Gabow, Sonia M Leach, William A Baumgartner, Lawrence E Hunter, Debra S Goldberg
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-198
Abstract: We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder, but co-occurrence data still proves beneficial.Co-occurrence data is a valuable supplemental source for graph-theoretic function prediction algorithms. A rapidly growing literature corpus ensures that co-occurrence data is a readily-available resource for nearly every studied organism, particularly those with small protein interaction databases. Though arguably biased toward known genes, co-occurrence data provides critical additional links to well-studied regions in the interaction network that graph-theoretic function prediction algorithms can exploit.The putative characterization for unknown proteins has traditionally relied on sequence homology, for example as assessed by BLAST score. This approach is inadequate for proteomic-wide function identification as it has a failure rate of 20–40% in newly sequenced genomes [1]. Sources of error stem
Motifs, themes and thematic maps of an integrated Saccharomyces cerevisiae interaction network
Zhang Lan V,King Oliver D,Wong Sharyl L,Goldberg Debra S
Journal of Biology , 2005, DOI: 10.1186/jbiol23
Abstract: Background Large-scale studies have revealed networks of various biological interaction types, such as protein-protein interaction, genetic interaction, transcriptional regulation, sequence homology, and expression correlation. Recurring patterns of interconnection, or 'network motifs', have revealed biological insights for networks containing either one or two types of interaction. Results To study more complex relationships involving multiple biological interaction types, we assembled an integrated Saccharomyces cerevisiae network in which nodes represent genes (or their protein products) and differently colored links represent the aforementioned five biological interaction types. We examined three- and four-node interconnection patterns containing multiple interaction types and found many enriched multi-color network motifs. Furthermore, we showed that most of the motifs form 'network themes' – classes of higher-order recurring interconnection patterns that encompass multiple occurrences of network motifs. Network themes can be tied to specific biological phenomena and may represent more fundamental network design principles. Examples of network themes include a pair of protein complexes with many inter-complex genetic interactions – the 'compensatory complexes' theme. Thematic maps – networks rendered in terms of such themes – can simplify an otherwise confusing tangle of biological relationships. We show this by mapping the S. cerevisiae network in terms of two specific network themes. Conclusion Significantly enriched motifs in an integrated S. cerevisiae interaction network are often signatures of network themes, higher-order network structures that correspond to biological phenomena. Representing networks in terms of network themes provides a useful simplification of complex biological relationships.
A man from the river Niger: Kélétigui Abdourahmane Mariko
Debra S Boyd
Tydskrif vir letterkunde , 2005,
Abstract:
Atherosclerosis: Viewing the Problem from a Different Perspective Including Possible Treatment Options
Joel S. Goldberg
Lipid Insights , 2012, DOI: 10.4137/LPI.S7912
Abstract: This paper proposes that atherosclerosis is initiated by a signaling event that deposits calcium hydroxyapatite (Ca-HAP). This event is preceded by a loss of mechanical structure in the arterial wall. After Ca-HAP has been deposited, it is unlikely that it will be reabsorbed because the solubility product constant (Ksp) is very small, and the large stores of Ca+2 and PO4-3 in the bones oppose any attempts to dissolve Ca-HAP by decreasing the common ions. The hydroxide ion (OH-) of Ca-HAP can be displaced in nature by fluoride (F-) and carbonate (CO3-2) ions, and it is proposed that anions associated with cholesterol ester hydrolysis and, in very small quantities, the enolate of 7-ketocholesterol could also displace the OH- of Ca-HAP, forming an ionic bond. The free energy of hydration of Ca-HAP at 310 K is most likely negative, and the ionic radii of the anions associated with the hydrolysis of cholesterol ester are compatible with the substitution. Furthermore, examination of the pathology of atherosclerotic lesions by Raman and NMR spectroscopy and confocal microscopy supports deposition of Ca-HAP associated with cholesterol. Investigating the affinity of intermediates of cholesterol hydrolysis for Ca-HAP compared to lipoproteins such as HDL, LDL, and VLDL using isothermic titration calorimetry could add proof of this concept and may lead to the development of a new class of medications targeted at the deposition of cholesterol within Ca-HAP. Treatment of acute ischemic events as a consequence of atherosclerosis with denitrogenation and oxygenation is discussed.
Stereocomplexes Formed From Select Oligomers of Polymer d-lactic Acid (PDLA) and l-lactate May Inhibit Growth of Cancer Cells and Help Diagnose Aggressive Cancers—Applications of the Warburg Effect
Joel S. Goldberg
Perspectives in Medicinal Chemistry , 2012, DOI: 10.4137/PMC.S6229
Abstract: It is proposed that select oligomers of polymer d-lactic acid (PDLA) will form a stereocomplex with l-lactate in vivo, producing lactate deficiency in tumor cells. Those cancer cells that utilize transport of lactate to maintain electrical neutrality may cease to multiply or die because of lactate trapping, and those cancer cells that benefit from utilization of extracellular lactate may be impaired. Intracellular trapping of lactate produces a different physiology than inhibition of LDH because the cell loses the option of shuttling pyruvate to an alternative pathway to produce an anion. Conjugated with stains or fluorescent probes, PDLA oligomers may be an agent for the diagnosis of tissue lactate and possibly cell differentiation in biopsy specimens. Preliminary experimental evidence is presented confirming that PDLA in high concentrations is cytotoxic and that l-lactate forms a presumed stereocomplex with PDLA. Future work should be directed at isolation of biologically active oligomers of PDLA.
Selected Gamma Aminobutyric Acid (GABA) Esters may Provide Analgesia for Some Central Pain Conditions
Joel S. Goldberg
Perspectives in Medicinal Chemistry , 2012, DOI: 10.4137/PMC.S5490
Abstract: Central pain is an enigmatic, intractable condition, related to destruction of thalamic areas, resulting in likely loss of inhibitory synaptic transmission mediated by GABA. It is proposed that treatment of central pain, a localized process, may be treated by GABA supplementation, like Parkinson’s disease and depression. At physiologic pH, GABA exists as a zwitterion that is poorly permeable to the blood brain barrier (BBB). Because the pH of the cerebral spinal fluid (CSF) is acidic relative to the plasma, ion trapping may allow a GABA ester prodrug to accumulate and be hydrolyzed within the CSF. Previous investigations with ester local anesthetics may be applicable to some GABA esters since they are weak bases, hydrolyzed by esterases and cross the BBB. Potential non-toxic GABA esters are discussed. Many GABA esters were investigated in the 1980s and it is hoped that this paper may spark renewed interest in their development.
Low Molecular Weight Opioid Peptide Esters Could be Developed as a New Class of Analgesics
Joel S. Goldberg
Perspectives in Medicinal Chemistry , 2012, DOI: 10.4137/PMC.S6803
Abstract: Low molecular weight opioid peptide esters (OPE) could become a class of analgesics with different side effect profiles than current opiates. OPE may have sufficient plasma stability to cross the blood brain barrier (BBB), undergo ester hydrolysis and produce analgesia. OPE of dipeptides, tyr-pro and tyr-gly conjugated to ethanol have a structure similar to the anesthestic agent, etomidate. Based upon the analgesic activity of dipeptide opioids, Lipinski’s criteria, and permeability of select GABA esters to cross the BBB, opioid peptides (OP) conjugated to ethanol, cholesterol or 3-glucose are lead recommendations. Preliminary animal data suggests that tyr-pro-ethyl ester crosses the BBB and unexpectedly produces hyperalgesia. Currently, there are no approved OP analgesics available for clinical use. Clinical trials of good manufacturing practice OP administered to patients suffering from chronic pain with indwelling intrathecal pumps could resolve the issue that OP may be superior to opiates and may redirect research.
Stereochemical Basis for a Unified Structure Activity Theory of Aromatic and Heterocyclic Rings in Selected Opioids and Opioid Peptides
Joel S. Goldberg
Perspectives in Medicinal Chemistry , 2012, DOI: 10.4137/PMC.S3898
Abstract: This paper presents a novel unified theory of the structure activity relationship of opioids and opioid peptides. It is hypothesized that a virtual or known heterocyclic ring exists in all opioids which have activity in humans, and this ring occupies relative to the aromatic ring of the drug, approximately the same plane in space as the piperidine ring of morphine. Since the rings of morphine are rigid, and the aromatic and piperidine rings are critical structural components for morphine’s analgesic properties, the rigid morphine molecule allows for approximations of the aromatic and heterocyclic relationships in subsequent drug models where bond rotations are common. This hypothesis and five propositions are supported by stereochemistry and experimental observations. Proposition #1 The structure of morphine provides a template. Proposition #2 Steric hindrance of some centric portion of the piperidine ring explains antagonist properties of naloxone, naltrexone and alvimopam. Proposition #3 Methadone has an active conformation which contains a virtual heterocyclic ring which explains its analgesic activity and racemic properties. Proposition #4 The piperidine ring of fentanyl can assume the morphine position under conditions of nitrogen inversion. Proposition #5 The first 3 amino acid sequences of beta endorphin (l-try-gly-gly) and the active opioid dipeptide, l-tyr-pro, (as a result of a peptide turn and zwitterion bonding) form a virtual piperazine-like ring which is similar in size, shape and location to the heterocyclic rings of morphine, meperidine, and methadone. Potential flaws in this theory are discussed. This theory could be important for future analgesic drug design.
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