Publications by authors named "L R Lareo"

We present various molecular electronic descriptors of agonists and antagonists for Glycine(B)-iGluR-NMDA receptor with a view to identify computational measures that help differentiate between these two classes of biologically active compounds. We use as reference the glycine site in the NR1 subunit of the NMDA receptor (Glycine(B)-iGluR-NMDA). Glycine(B)-iGluR-NMDA receptor is important in learning and memory, and it is involved in various neurodegenerative diseases such as Alzheimer, Parkinson, and Huntington as well as in neuropathies such as schizophrenia and depression.

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Introduction: Mathematical models that correlate chemical structure with biological activity have been useful in the design of new drugs and can be used to predict biological behavior of new, chemically related molecules.

Objectives: A mathematical model was generated to correlate the substrate affinities with variations in the molecular topology of glycine antagonists in NMDA sub-class glutamate receptor and, subsequently, to propose new molecules with antagonist activity.

Materials And Methods: By use of molecular connectivity indexes, the electronic structure and atomic bonding patterns of 45 glycine antagonists were coded.

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Introduction: Hunter syndrome (MC KUSIK 309900) or mucopolysacharidosis type II is due to the deficiency of the enzyme iduronate 2 sulfate sulfatase (E.C. 3.

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The N-methyl-D-aspartate (NMDA) receptor subunit NR1 gene can produce eight isoforms in rat brain. A novel methodology for purifying NMDA receptor NR1 subunit from rat brain is reported here using chicken polyclonal antibodies (IgYs) against synthetic peptides corresponding to N1, C1 and C2' cassettes. The isolated protein was recognized by produced IgYs and commercial anti-NR1 IgGs, shown by MALDI-TOF MS a MW = 131,192 Da (glycosylated form); the enzymatically deglycosylated protein revealed a MW = 102,754 Da.

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Statistical analysis of amino acid patterns in approximately 160,000 alpha-helices in experimentally determined structures revealed di-, tri-, and tetrapeptides, whose frequencies deviate most from the statistical model. Importantly, some sequences were never found in alpha- helices. This fact was detected initially with tripeptides, where nearly 1% of the possible sequences were never seen in the helical segments.

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