Chemical Ecology The Chemistry of Biotic Interaction (1995) / Chapter Skim
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Chemical Ecology: A View from the Pharmaceutical Industry
Chemical Ecology: A View from the Pharmaceutical Industry
Pages 183-202
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From page 183... ...
Analysis of Chemical Signals by Nervous Systems /177 and functional mechanisms make this system especially favorable for experimentation as well as for computational modeling (881. In this specialized subsystem, the molecular images attributable to at least the first several levels of the pathway seem, to a first approximation, to be relatively simple.
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178 I John G Hildebrand This article is dedicated to the memory of Vincent G
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Analysis of Chemical Signals by Nervous Systems /179 23. Hildebrand, J
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180 / John G Hildebrand Ferguson, H
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Analysis of Chemical Signals by Nervous Systems /181 86. Kanzaki, R., Arbas, E
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Drug discovery demands a coordinated effort among people with diverse talents. Researchers who elucidate disease mechanisms (which point to macromolecules that would make good drug discovery targets)
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While new structures that inhibit the HIV protease have emerged from natural product screens (11, 12) [one structure that inhibits aspartyl proteases, the statine moiety, had been discovered through screening bacterial natural products before the emergence of HIV (101]
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Their efforts have provided HIV protease inhibitors that are being evaluated for clinical efficacy (161. Examples of successful natural product screens directed against proven targets include screens designed to look for inhibitors of bacterial cell wall biosynthesis.
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As receptor subtypes with distinct amino acid sequences interact with distinct sets of drugs, are there endogenous molecules (perhaps metabolites of the ligand for which we have named the receptor) to which receptor subtypes are differentially sensitive or might subtypes have evolved to bind to different conformations of the same ligand?
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If we can learn to manipulate key biochemical control points that trigger or block cell death as well as these pathogens do, then we could save neurons in neurodegenerative disease or kill cells in a tumor. Cyclosporin (originally discovered due to its antifungal activity)
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Our screens span a broad range of diseases and, therefore, many molecular targets. To increase the chance of finding drugs or at least leads for a medicinal chemistry effort, we gather a diverse array of molecular structures for screens.
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~ HO: HO HOi-On I I I r \i OH OH `~OH it......... ~0 11 H C'N~ i_ OCH3 IV H~'~CH3 FIGURE 2 Examples of the Variety of structures obtained in natural product screens.
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From page 196... ...
(Gibberellins, first isolated from the phytopathogenic fungus Gibberella fujikuroi, are plant growth hormones that stimulate stem elongation, induce flowering, and overcome seed dormancy.) Thus, if asked where to look for an inhibitor of HMG-CoA reductase, a chemical ecologist studying gibberellins might have suggested screening such phytopathogenic fungi.
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INTEGRATING INFO~TION FROM ~ ORGASMS TO GAIN INSIGHT FOR DRUG DESIGN natural product screening may capture a compound, such as an antibiotic, insecticide, or HMG-CoA reductase inhibitor, designed for the
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Natural product screening allows us to sift through the extraordinary diversity that overlays these common molecular features. It may be that an interaction is fortuitous, given the number and diversity of natural products examined in pharmaceutical industry screens.
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are less conserved in this protein family. Thus, while predictions made based upon linear amino acid sequences from 11 species were confirmed, we await three-dimensional structures from diverse sources to elucidate how variant amino acids alter the orientation of the conserved amino acids to eject base-seauence-specific recognition (figure by Tom Ellenberger)
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(much as the steroid nucleus itself serves, in nature, as a scaffold on which different substituents are responsible for selective interaction with individual members of the steroid receptor protein family) ; other scaffolds may be found through screening natural products.
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This assembling of DNA sequences from different sources generates patchwork genes, such as that encoding the low density lipoprotein receptor (1031. Similarly, new serine proteases appear to have been created by duplication of DNA encoding a functional serine protease domain, followed by mutation (104)
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