ABSTRACT
The application of biotransformation dictionaries derived by expert evaluation of known metabolic pathways represents one approach to the prediction of both phase I and phase II xenobiotic metabolites. The ranking of metabolites generated by such dictionaries has previously been achieved through the use of qualitative reasoning rules and quantitative probability values. Using the biotransformation dictionary available in the Meteor expert system, we show that metabolite over-prediction by both of these methods can be reduced by the adoption of a k-nearest neighbours methodology in which the likelihood of a predicted biotransformation is determined based on comparison of a query chemical with structurally-similar substrates with known experimental metabolic data which activate the same biotransformation. Optimal performance was achieved when similarity was defined in terms of a combination of two fingerprints, one describing the overall profile of biotransformations a structure can potentially undergo and the other describing the local environment around the predicted site of metabolism for the particular biotransformation under consideration.
Subject(s)
Biotransformation/physiology , Computational Biology/methods , Animals , Humans , Metabolic Networks and PathwaysABSTRACT
The IUPHAR database (IUPHAR-DB) integrates peer-reviewed pharmacological, chemical, genetic, functional and anatomical information on the 354 nonsensory G protein-coupled receptors (GPCRs), 71 ligand-gated ion channel subunits and 141 voltage-gated-like ion channel subunits encoded by the human, rat and mouse genomes. These genes represent the targets of approximately one-third of currently approved drugs and are a major focus of drug discovery and development programs in the pharmaceutical industry. IUPHAR-DB provides a comprehensive description of the genes and their functions, with information on protein structure and interactions, ligands, expression patterns, signaling mechanisms, functional assays and biologically important receptor variants (e.g. single nucleotide polymorphisms and splice variants). In addition, the phenotypes resulting from altered gene expression (e.g. in genetically altered animals or in human genetic disorders) are described. The content of the database is peer reviewed by members of the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR); the data are provided through manual curation of the primary literature by a network of over 60 subcommittees of NC-IUPHAR. Links to other bioinformatics resources, such as NCBI, Uniprot, HGNC and the rat and mouse genome databases are provided. IUPHAR-DB is freely available at http://www.iuphar-db.org.
Subject(s)
Databases, Protein , Ion Channels/genetics , Ion Channels/physiology , Receptors, G-Protein-Coupled/genetics , Receptors, G-Protein-Coupled/physiology , Animals , Drug Discovery , Humans , Ion Channels/chemistry , Ligands , Mice , Protein Subunits/chemistry , Protein Subunits/genetics , Protein Subunits/physiology , Rats , Receptors, G-Protein-Coupled/chemistryABSTRACT
NC-IUPHAR (International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification) and its subcommittees provide authoritative reports on the nomenclature and pharmacology of G protein-coupled receptors (GPCRs) that summarize their structure, pharmacology, and roles in physiology and pathology. These reports are published in Pharmacological Reviews (http://www.iuphar.org/nciuphar_arti.html) and through the International Union of Pharmacology (IUPHAR) Receptor Database web site (http://www.iuphar-db.org/iuphar-rd). The essentially complete sequencing of the human genome has allowed the cataloging of all of the human gene sequences potentially encoding GPCRs. The IUPHAR Receptor List (http://www.iuphar-db.org/iuphar-rd/list/index.htm) presents this catalog giving IUPHAR-approved nomenclature (where available), known ligands, and gene names for all of these potential receptors (excluding sensory receptors and pseudogenes) together with links to curated sequence, descriptive information, and additional links in the Entrez Gene database (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene). This list is a major new initiative of NC-IUPHAR that, through continuing curation, defines the target of our ongoing receptor classification and invites further input from the scientific community.
Subject(s)
Receptors, G-Protein-Coupled/classification , Terminology as Topic , Animals , Humans , International Agencies , Receptors, G-Protein-Coupled/geneticsABSTRACT
The synthesis of C(4)H and C(4)Me analogues of the JNK/p38 pathway activator anisomycin, based upon an aldol or Claisen construction of the C(3)-C(4) bond, has been demonstrated. The relative activation of the JNK/SAPK1 and p38/SAPK2 pathways in RAW macrophages by these analogues, and their synthetic precursors, has been assessed using immunoblot assays against phosphorylated c-Jun and MAPKAP-K2. These studies demonstrate that some of the synthetic C(4) analogues are also potent activators of these stress kinase pathways.
Subject(s)
Anisomycin/analogs & derivatives , Mitogen-Activated Protein Kinases/metabolism , Animals , Anisomycin/chemical synthesis , Anisomycin/chemistry , Cell Line , Enzyme Activation , MAP Kinase Signaling System , Macrophages/drug effects , Macrophages/enzymology , Mice , Mitogen-Activated Protein Kinase 8 , p38 Mitogen-Activated Protein KinasesABSTRACT
[reaction: see text] A new approach to the synthesis of the antibiotic anisomycin is reported that relies upon a key aldol disconnection. The glycolate aldol coupling proceeds in 75% yield and with >95% diastereoselectivity, which allows the 13-step synthesis to proceed in 35% overall yield.
