Drug-drug interactions involving cytochrome P(450) (CYP) are an important factor in whether a new chemical entity will survive through to the development stage. Therefore, the identification of this potential as early as possible in vitro could save considerable future unnecessary investment. In vitro CYP interaction screening data generated for CYP2C9, CYP2D6, and CYP3A4 were initially analyzed to determine the correlation of IC(50) from 10- and 3-point determinations. A high correlation (r = 0.99) prompted the further assessment of predicting the IC(50) by a single value of percent inhibition at either 10, 3, or 1 microM. Statistical analysis of the initial proprietary compounds showed that there was a strong linear relationship between log IC(50) and percent inhibition at 3 microM, and that it was possible to predict a compound's IC(50) by the percent inhibition value obtained at 3 microM. Additional data for CYP1A2, CYP2C19, and the recombinant CYP2D6 were later obtained and used together with the initial data to demonstrate that a single statistical model could be applicable across different CYPs and different in vitro microsomal systems. Ultimately, the data for all five CYPs and the recombinant CYP2D6 were used to build a statistical model for predicting the IC(50) with a single point. The 95% prediction boundary for the region of interest was about +/- 0.37 on log(10) scale, comparable to the variability of in vitro determinations for positive control IC(50) data. The use of a single inhibitor concentration would enable determination of more IC(50) values on a 96-well plate and result in more economical use of compounds, human liver or expressed enzyme microsomes, substrates, and reagents. This approach would offer the opportunity to increase screening for CYP-mediated drug-drug interactions, which may be important given the challenges provided by the generation of orders of magnitude more new chemical entities in the field of combinatorial chemistry. In addition, the algorithmic approach we propose would obviously be applicable for other in vitro bioactivity and therapeutic target enzyme and receptor screens.
Ether, ester, and carbonate derivatives of the antirheumatic oxindole 1 were prepared and screened as potential prodrugs of 1. This effort led to the discovery of the (alpha-L-alanyloxy)-methyl ether and hemifumarate derivatives of 1 which deliver the drug efficiently into the circulation of test animals, are stable in the solid state, and possess good stability in solution at low pH as required to ensure gastric stability. Success in achieving acceptable bioavailabilities of 1 across species (rats, dogs, and monkeys) followed the inclusion of ionizable functionality within the promoiety to compensate for masking the polar enolic OH group of the free drug. However, the introduction of ionizable functionality was often associated with decreased stability, as demonstrated by the hemisuccinate, hemiadipate, hemisuberate, and alpha-amino ester derivatives of 1 which could not be isolated. A clear exception was the hemifumarate derivative of 1 which was not only isolable but actually more stable at neutral pH than the nonionizable ester analogues. The solution and solid state stability of the hemifumarate, together with its activity as a prodrug of 1, suggests that hemifumarate be considered as an alternative to hemisuccinate as a prodrug derivative for alcohols, particularly in situations where solution state stability is an issue.
In spite of considerable effort to predict wildland fire behaviour, the effects of firebrand lift-off, the ignition of resulting spot fires and their effects on fire spread, remain poorly understood. We developed a cellular automata model integrating key mathematical models governing current fire spread models with a recently developed model that estimates firebrand landing patterns. Using our model we simulated a wildfire in an idealised Pinus ponderosa ecosystem. Varying values of wind speed, surface fuel loading, surface fuel moisture content and canopy base height, we investigated two scenarios: (i) the probability of a spot fire igniting beyond fuelbreaks of various widths and (ii) how spot fires directly affect the overall surface fire’s rate of spread. Results were averages across 2500 stochastic simulations. In both scenarios, canopy base height and surface fuel loading had a greater influence than wind speed and surface fuel moisture content. The expected rate of spread with spot fires occurring approached a constant value over time, which ranged between 6 and 931% higher than the predicted surface fire rate of spread. Incorporation of the role of spot fires in wildland fire spread should be an important thrust of future decision-support technologies.
Conformational features of the oligoribonucleic acid (oligo-RNA) A1-U2-C3-C4-A5 are explored by proton nuclear magnetic resonance (NMR). The sequence is a molecular cognate of a portion of the T psi C loop and stem regions of yeast tRNAPhe. The molecule forms at least two classes of flexible yet ordered structures. Class I states are similar in spectral properties to the component oligomers, AU, AUC, and AUCC, and are likely to be standard right-helical structures. Class II states are characterized by a 2'-endo pucker at A1 and unusually large shielding of several C3 and U2 protons. Most of these features are consistent with identifying the class II solution structures with the "arch" conformation for the T psi C region determined by X-ray crystallography of yeast tRNAPhe.
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