Use of computational and experimental data to model organic...

Details Use of computational and experimental data to model organic... Use of computational and experimental data to model organic...

1999-08-05

2003-11-04

Moran, Marjorie (Department: 1631)

Data processing: measuring, calibrating, or testing

Measurement system in a specific environment

Chemical analysis

C702S030000, C703S002000, C435S025000

Reexamination Certificate

active

06643591

ABSTRACT:

FIELD OF THE INVENTION
The present invention is directed to the use of computational and other experimental data in the design of new pharmaceuticals, and in predicting the metabolism profiles thereof. Computational and other information is used to further understand drug metabolism and toxicology, particularly in relation to monooxygenase enzymes, such as those of the cytochrome P450 system, that are involved in drug metabolism. Information derived according to the practice of the invention is useful in predicting the clearance or half-life of drugs, the propensity for drug interactions, and the nature and toxicity of byproducts resulting from their metabolism. The invention provides novel and powerful new approaches to drug design.
BACKGROUND OF THE INVENTION
The opportunity to improve the efficiency of the discovery phase of drug discovery is widely recognized in the pharmaceutical industry. Combinatorial chemistry and parallel synthesis methodologies, genomics, robotics, miniaturization, high-throughput screening and information technology together have stimulated an explosion of potential new lead compounds. However, limited expertise and resources are available to move a compound from “candidate” to “lead”. This is partially because the development of new technologies to address the later stages of the lead optimization process have not kept pace with the combinatorial technologies developed for synthesis and screening. As a result, there is a bottleneck in the drug discovery process that begins with lead optimization and extends all the way to the selection of clinical development candidates.
A primary consideration in the area of lead development is a compound's metabolic fate. It would be of great value to the pharmaceutical industry if the discovery of such lead substances could be accelerated by design approaches that minimize reliance on screening synthesized compounds, but instead take advantage of quantifiable chemical or biochemical properties of a molecule in order to predict its metabolic characteristics. Predictive models can not only help alleviate the bottleneck in lead optimization but to facilitate the design and selection of drug candidates with not just adequate but with optimal absorption, distribution, metabolism and excretion/pharmacokinetic (ADME/PK) profiles for progression to the later, more costly stages of the drug discovery/development process. Compounds thus selected will not only have a greater chance of development success but will ultimately lead to better medicines.
In connection with the design of optimized pharmaceutical compounds, one particular area of interest involves a class of enzymes known as heme-containing monooxygenases, mixed function oxygenases, or alternatively cytochrome P-450s. These enzymes, which are abundant in the liver, act on a very broad range of substrate compounds, which is a trait very unusual for enzymes. These enzymes react with molecular oxygen such that one of the oxygen atoms is reduced to water, and the other is inserted into a substrate organic compound. This metabolic reaction may also be referred to as a hydroxylation reaction.
The cytochrome P450 (CYP) enzymes comprise a superfamily of heme-containing enzymes that consists of more than 700 individual isoforms, and are found in plant, bacterial and mammalian species (Nelson et al. (1996)
Pharmacogenetics
6, 1-42). These enzymes function mainly as monooxygenases (Wislocki et al. (1980) in
Enzymatic Basis of Detoxification
(Jakoby, W. B., Ed.) pp 135-82, Academic, New York). In mammals, they are responsible for the metabolism of certain endogenous as well as exogenous compounds (Gonzalez, F. J. (1992)
Trends Pharmacol. Sci.
13, 346-52). The catalytic cycle for aliphatic hydroxylation by mammalian CYP is described here briefly and shown in FIG.
1
. Substrate binding changes the equilibrium of the heme iron from the low spin to the high spin state (step
1
). This change lowers the reduction potential for the iron and facilitates electron transfer from NADPH via another enzyme, cytochrome P450 reductase (step
2
). Molecular oxygen binds and is reduced by one electron as iron changes from the ferrous to the ferric state (steps
3
and
4
). A second electron reduction of oxygen occurs and a peroxy intermediate is formed (step
5
). The peroxy species undergoes heterolytic cleavage: one atom of oxygen leaves as a hydroxyl anion and the other forms a reactive oxygen species which is coordinated with the iron (step
6
). Oxygen is transferred to the substrate (steps
7
and
8
) and product dissociates from the enzyme (step
9
). The first three steps of the cycle have been characterized spectroscopically. The next three steps occur rapidly, and have proven difficult to measure. At least two mechanisms have been proposed for the step(s) of oxygen transfer (depicted as steps
7
and
8
in FIG.
1
), and are described briefly below.
The consensus mechanism for oxygen transfer is a nonconcerted reaction. In this context, nonconcerted implies that there are two distinct steps and that each step has its own transition state. There is evidence that step
7
(
FIG. 1
) is abstraction of a hydrogen atom from the substrate by the reactive oxygen, which yields a carbon-based radical and an iron bound hydroxyl radical (White et al. (1980)
Ann. Rev. of Biochem.
49, 315-56). The next step (step
8
in
FIG. 1
) is rapid recombination of the two radical species, the “oxygen rebound” step. The magnitudes of isotope effects (Groves et al. (1978)
Biochemical
&
Biophysical Research Communications
81, 154-60; and Hjelmeland et al. (1977)
Biochem. Biophys. Res. Commun.
76, 541-9), loss of stereoselectivity (Groves et al., Ibid; and White et al. (1986)
J. Am. Chem. Soc.
108, 6024-31), and evidence for rearrangement of the radical-like product of the first step (Groves et al. (1984)
J. Am. Chem. Soc.
106, 2177-81) in various CYP-mediated reactions support the case for the oxygen rebound mechanism.
Suitable substrates for CYP include steroids, prostaglandins, fatty acids, and exogenous drugs, pesticides and other toxic environmental contaminants including many carcinogens. Hydroxylation reactions are often the first step in the metabolism of foreign substances leading, for example, to the inactivation of administered pharmaceuticals. Depending upon the mechanism of action of a drug, and its toxicological profile, it may be desirable to accelerate or delay its breakdown once it enters the body. Additionally other potential pharmaceuticals may be too toxic to administer, but appropriate structural modifications thereof may lead, for example, to structures that are decomposed to different, and less toxic, metabolites.
For example, metabolism of phenylacetonitrile at the benzylic position (
FIG. 2
, see arrow) causes the release of the toxic metabolite cyanide, whereas aromatic oxidation leads to a less toxic product (Silver et al. (1982)
Drug Metab. Dispos.
10, 495-8). The metabolism of benzo(12)pyrene (Franchetti et al. (1995)
J. Med. Chem.
38, 3829-37) by CYP and epoxide hydrolase yields several metabolites including the extremely carcinogenic compound 7(R),8(S)-dihydrodiol 9(S),10(R)-epoxide. These are examples where regioselectivity and stereoselectivity are important determinants of toxicity.
In addition, potential drug interactions can be caused by differences in metabolism of multiple drugs by a single CYP isoform, as well as the induction or inhibition of individual CYP isoforms by drugs. Polymorphic enzyme expression among individuals may cause unusual patterns of drug metabolism, which can lead to unwanted side effects.
As aforementioned, there is a tremendous need to enhance presently available methods for drug design to minimize dependence on the testing of randomly modified structures. But while progress has been made in the area of basic research, the field of predictive metabolism is not widespread in industry at this time. The two main determinants of enzymatic reactions are the steric and electronic characteristics of the enzyme and the sub

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