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Extended X-ray absorption fine structure studies on periplasmic and intracellular molybdenum-binding proteins (1999)

Duhme, A.-K. ; Meyer-Klaucke, W. ; White, D. J. ; [et al.]

Springer

JBIC 4 (1999), S. 588-592

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ISSN: 1432-1327

Keywords: Key words Molybdenum ; Extended X-ray absorption fine structure ; Binding proteins ; Metal coordination

Source: Springer Online Journal Archives 1860-2000

Topics: Biology , Chemistry and Pharmacology

Notes: Abstract We have studied the molybdenum K-edge X-ray absorption spectra of Mo bound in the Mo-binding proteins Mop from Haemophilus influenzae, ModG from Azotobacter vinelandii and the Escherichia coli ModE transcriptional regulatory protein, and compared them with the absorption spectra of A. vinelandii ModA and monomeric molybdate. Pre-edge and extended fine structure data indicate that the Mo-binding proteins with molbindin-like domains bind tetrahedral molybdate with a Mo-O distance of 1.76 Å. The molbindin subunits or sub-domains represent a novel protein fold that is used by proteins with distinct functions to bind molybdate in the cytoplasm. The high specificity of the proteins for molybdenum does not depend on a change of coordination number or geometry.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1007/s007750050381

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A mathematical programming approach to a problem in variance penalised Markov decision processes (1994)

White, D. J.

Springer

OR spectrum 15 (1994), S. 225-230

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ISSN: 1436-6304

Keywords: Markov decision processes ; ɛ-optimal ; variance ; Markov'sche Entscheidungsprozesse ; ɛ-Optimalität ; Gewinnvarianz

Source: Springer Online Journal Archives 1860-2000

Topics: Mathematics , Economics

Description / Table of Contents: Zusammenfassung In dieser Arbeit geben wir drei Algorithmen zur Lösung eines stochastischen dynamischen Problems an. Dabei wird ein optimaler Ausgleich zwischen erwartetem Gewinn und Gewinnvarianz pro Zeiteinheit gesucht. Die Algorithmen liefern für beliebigesɛ〉0 jeweilsɛ-optimale Lösungen.

Notes: Abstract In this paper we present three algorithms for solving a problem in which it is required to get an optimal compromise between the average expected reward per unit time and the variance of the reward per unit time. The algorithms lead to anɛ-optimal solution, whereɛ〉0 is arbitrary.