ADMET

MetabolExpert

PASS

The editor Ehrhardt said: "For metabolism information to be useful, the data must have statistical relevance. Large databases provide this relevance. I commend MDL for putting together such a huge database and for making it easy to access and integrate with other scientific applications."

The huge database he means, is MDL^® Metabolite, and the book Drug Metabolism includes several chapters of "case studies". Marc Johnson in the drug discovery group at Pharmacia & Upjohn, Inc. concludes: "Metabolic databases can be used to provide statistically-based prediction rules that begin to add a measure of objective quantification to our expectations concerning the metabolic fate of a molecule."

One of the problem was to explore and compare the versatility with regard to the design of prodrugs and codrugs. The questions were:

1. What metabolic reactions might be relied upon to produce the query molecule from any type of prodrug precursor?
2. What metabolic reactions might be expected to occur on the query molecule himself?
3. Can anything be indicated about the associated rates for metabolic production of the query molecule versus its metabolic clearance?

A more detailed description of the issues above, you will find in the article "Metabolism", Molecular Connection, Spring 1999, page 5. Molecular Connection is MDL's newsmagazine for communicating with customers. Please send me an email and I will put you on the mailing list of this magazine.

In addition to Metabolite related information is available in the database Toxicity and CrossFire Beilstein.

Sometimes there is very little known about a compound of your interest. In this case you can try to simulate the metabolic pathways using Metabol Expert in the PALLAS suite of programs.

Another reason to invest in the information provided by these bioactivity databases is that you do not want to fail in a project, just before you have the glorious end in sight. Go to Fail Early.

I copied the following from the page: www.iupac.org/publications/books/author/erhardt.html

 

Contents

Introduction; Drug Metabolism Data: Past, Present and Future Considerations;

Case Studies; Metabolism Considerations During the Discovery and Development of Chlorpropamide, Pyrantel, Tetramisol and Certain Alpha-adrenergic Agonists; Use of a Metabolism Database During the Development of Zyflo; Prediction of Tebufelone Metabolism Using a Metabolism Database Approach; Use of Metabolism Databases at Parke-Davis Pharmaceutical Research, Inc.; A Perspective on the Use and Role of Metabolic Databases at Pharmacia & Upjohn, Inc.; Use of a Metabolism Database at Eli Lilly & Co.; Use of a Metabolism Database at Bayer A.G.; Construction of a Metabolism Database Emphasizing Human CYP Data at Daiichi Pharmaceutical Co., JP; A Prodrug and a Softdrug;

New Directions; High-Throughput Screening for Gastrointestinal Absorption in the Generation of SAR Databases; Screening for the Effects Cytochromes P450 on New Drugs and for the Influence of New Drugs on the Cytochromes P450; Rationale For The Development Of Databases For The Prediction Of Metabolic Drug Interactions: Experience With Antiepileptic Drugs; High-Throughput Screening For Inhibition Of Cytochrome P450 Metabolism; Three Dimensional Aspects of Metabolism in Human P450 Systems; The Use of Microorganisms in the Study of Drug Metabolism; Metalloporphrins As Synthetic Livers; Higher-Throughput In Vivo Pharmacokinetic Screening; High-Throughput Screening In Preclinical Drug Metabolism: A Burgeoning Trend; Statistics-Based Probabilities of Metabolic Possibilities; Use of Metabolic Databases To Guide Target Selection For Anti-Microbial Drug Design; Comparison of Commercially Available Metabolism Databases During the Design of Prodrugs and Codrugs; Soft Drugs: Designing Safer Drugs by Simplifying Drug Metabolism;

Emerging Products; MetabolExpert: Its Use in Metabolism Research and in Combinatorial Chemistry; META: A Program for the Prediction of the Products of Mammal Metabolism of Xenobiotics; Metabolite; Synopsys' Metabolism Database; Knowledge Based Expert Systems for Toxicity and Metabolism Prediction;

Summary; Drug Metabolism Databases: Some Key Points

115 illustrations
352 pages