Publisher Summary This chapter discusses the integrated methods for the construction of three-dimensional models and computational probing of structure–function relations in G protein-coupled receptors (GPCR). The rapid pace of cloning and expression of G protein-coupled receptors offers attractive opportunities to probe the structural basis of signal transduction mechanisms at the level of these cell-surface receptors. Major insights have emerged from comparisons and classifications of the amino acid sequences of GPCRs into families defined by evolutionary developments and adapted to perform selective functions. Structural data on GPCRs, based on biochemical, immunological, and biophysical approaches have validated consensus architecture of GPCRs with an extracellular N-terminus, a cytoplasmic C-terminus, and a transmembrane portion comprised of seven-transmembrane helical domains connected by loops. Developments in the molecular modeling and computational exploration of GPCR proteins indicate a tantalizing potential to alleviate some of these difficulties. These expectations are based on the increased rate of success achieved by molecular modeling and computational simulation methods in providing structural insights relevant to the functions of biological molecules.

[19] Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors

The study of pain in awake animals raises ethical, philosophical, and technical problems. We review the ethical standards for studying pain in animals and emphasize that there are scientific as well as moral reasons for keeping to them. Philosophically, there is the problem that pain cannot be monitored directly in animals but can only be estimated by examining their responses to nociceptive stimuli; however, such responses do not necessarily mean that there is a concomitant sensation. The types of nociceptive stimuli (electrical, thermal, mechanical, or chemical) that have been used in different pain models are reviewed with the conclusion that none is ideal, although chemical stimuli probably most closely mimic acute clinical pain. The monitored reactions are almost always motor responses ranging from spinal reflexes to complex behaviors. Most have the weakness that they may be associated with, or modulated by, other physiological functions. The main tests are critically reviewed in terms of their sensitivity, specificity, and predictiveness. Weaknesses are highlighted, including 1) that in most tests responses are monitored around a nociceptive threshold, whereas clinical pain is almost always more severe; 2) differences in the fashion whereby responses are evoked from healthy and inflamed tissues; and 3) problems in assessing threshold responses to stimuli, which continue to increase in intensity. It is concluded that although the neural basis of the most used tests is poorly understood, their use will be more profitable if pain is considered within, rather than apart from, the body's homeostatic mechanisms.

Animal Models of Nociception

http://yael-nissan.weebly.com/uploads/5/2/9/2/5292348/the_introduction_to_pain_an_integrative_review_-_millan.pdf

The induction of pain: an integrative review

Recent developments in G protein-coupled receptor (GPCR) structural biology and pharmacology have greatly enhanced our knowledge of receptor structure-function relations, and have helped improve the scientific foundation for drug design studies. The GPCR database, GPCRdb, serves a dual role in disseminating and enabling new scientific developments by providing reference data, analysis tools and interactive diagrams. This paper highlights new features in the fifth major GPCRdb release: (i) GPCR crystal structure browsing, superposition and display of ligand interactions; (ii) direct deposition by users of point mutations and their effects on ligand binding; (iii) refined snake and helix box residue diagram looks; and (iii) phylogenetic trees with receptor classification colour schemes. Under the hood, the entire GPCRdb front- and back-ends have been re-coded within one infrastructure, ensuring a smooth browsing experience and development. GPCRdb is available at http://www.gpcrdb.org/ and it's open source code at https://bitbucket.org/gpcr/protwis.

/pdf/gpcrdb-an-information-system-for-g-protein-coupled-receptors-1ohvnbu880.pdf

GPCRDB: an information system for G protein-coupled receptors.

Psychopharmacology: The Fourth Generation of Progress.

In recent years, pharmacokinetic/pharmacodynamic (PK/PD) modeling has developed from an empirical descriptive discipline into a mechanistic science that can be applied at all stages of drug development. Mechanism-based PK/PD models differ from empirical descriptive models in that they contain specific expressions to characterize processes on the causal path between drug administration and effect. Mechanism-based PK/PD models have much improved properties for extrapolation and prediction. As such, they constitute a scientific basis for rational drug discovery and development. In this report, a novel classification of biomarkers is proposed. Within the context of mechanism-based PK/PD modeling, a biomarker is defined as a measure that characterizes, in a strictly quantitative manner, a process, which is on the causal path between drug administration and effect. The new classification system distinguishes seven types of biomarkers: type 0, genotype/phenotype determining drug response; type 1, concentration of drug or drug metabolite; type 2, molecular target occupancy; type 3, molecular target activation; type 4, physiological measures; type 5, pathophysiological measures; and type 6, clinical ratings. In this paper, the use of the new biomarker classification is discussed in the context of the application of mechanism-based PK/PD analysis in drug discovery and development.

Mechanism-Based Pharmacokinetic–Pharmacodynamic Modeling—A New Classification of Biomarkers

The steady-state plasma concentrations of antipsychotic drugs show large interpatient variations but remain relatively stable from day to day in each individual patient. Monitoring of antipsychotic drug concentrations in plasma might be of value provided the patients are treated with only 1 antipsychotic drug. Some studies have reported a relationship between therapeutic response and serum antipsychotic drug 'concentrations' as measured using the radioreceptor assay (RRA) method, which measures dopamine receptor-blocking activity in plasma. Most studies, however, have failed to demonstrate such a relationship, and the RRA does not seem to provide the generally useful tool for plasma concentration monitoring of antipsychotic drugs that was hoped for initially. A lack of correlation between dopamine receptor-blocking activity in plasma and therapeutic response may be due to differences in the blood-brain distribution of both antipsychotic drugs and their active metabolites. Chemical assay methods (e.g. GLC and HPLC) have been used in studies which examined the relationships between therapeutic response and antipsychotic drug concentrations in red blood cells and in plasma. It seems that for these drugs, measuring red blood cell concentrations does not offer any significant advantage over measuring plasma concentrations. Reasonably controlled studies of plasma concentration-response relationships using randomly allocated, fixed dosages of chlorpromazine, fluphenazine, haloperidol, perphenazine, sulpiride, thioridazine and thiothixene have been published but often involve relatively few patients. A correlation between therapeutic response and plasma concentrations of thioridazine and its metabolites has not been demonstrated, and plasma level monitoring of thioridazine and its metabolites therefore appears to have no clinical value. Clinical behavioural deterioration concomitant with high plasma concentrations of chlorpromazine and haloperidol have been reported. A dosage reduction might be considered after 2 to 4 weeks' treatment in non-responders who have plasma chlorpromazine concentrations above 100 to 150 micrograms/L or plasma haloperidol concentrations above 20 to 30 micrograms/L. Non-responders and good responders to chlorpromazine treatment, however, have plasma drug concentrations in the same range, and a therapeutic range of plasma chlorpromazine levels has not been defined. Therapeutic plasma haloperidol concentrations (i.e. 'window') in the range of 5 to 20 micrograms/L have been reported by some investigators, but others have found no such relationship.(ABSTRACT TRUNCATED AT 400 WORDS)

Plasma level monitoring of antipsychotic drugs. Clinical utility.

A three-dimensional model of the dopamine D2 receptor, assumed to be a target of antipsychotic drug action, was constructed from its amino acid sequence. The model was based on structural similarities within the super-family of guanine nucleotide-binding regulatory (G) protein-coupled neuroreceptors and has seven alpha-helical transmembrane segments that form a central core with a putative ligand-binding site. The space between two residues postulated to be involved in agonist binding, Asp-80 and Asn-390, perfectly accommodated an anti-dopamine molecule. Molecular electrostatic potentials were mainly negative on the synaptic side of the receptor model and around aspartate residues lining the central core and positive in the cytoplasmic domains. The docking of dopamine into a postulated binding site was examined by molecular dynamics simulation. The protonated amino group became oriented toward negatively charged aspartate residues in helix 2 and helix 3, whereas the dopamine molecule fluctuated rapidly between different anti and gauche conformations during the simulation. The receptor model suggests that protonated ligands are attracted to the binding site by electrostatic forces and that protonated agonists may induce conformational changes in the receptor, leading to G-protein activation, by increasing the electrostatic potentials near Asp-80.

https://www.pnas.org/content/pnas/88/18/8111.full.pdf

Molecular dynamics of dopamine at the D2 receptor.

Transporter proteins in biological membranes may be divided into channels and carriers. Channels function as selective pores that open in response to a chemical or electrophysiological stimulus, allowing movement of a solute down an electrochemical gradient. Active carrier proteins use an energy producing process to translocate a substrate against a concentration gradient. Secondary active transporters use the movement of a solute down a concentration gradient to drive the translocation of another substrate across a membrane. ATP-binding cassette (ABC) transporters couple hydrolysis of adenosine triphosphate (ATP) to the translocation of various substrates across cell membranes. High-resolution three-dimensional structures have now been reported from X-ray crystallographic studies of six different transporters, including two ATP-binding cassette (ABC) transporters. These structures have explained the results from many previous biochemical and biological studies and shed new light on their functional mechanisms. All these transporters have α-helical structures of the membrane-spanning domains, as suggested from many previous studies, and some of the helices have irregular shapes with kinks and bends. Together these crystal structures demonstrate the large flexibility of transporter proteins and that substantial movements take place during the substrate translocation process, which to a certain extent may distinguish active carriers from channel proteins. These structures and other low-resolution structures of membrane proteins have served as a basis for construction of three-dimensional protein models that have provided insight into functional mechanisms and molecular structures and enabled formulation of new hypotheses regarding transporter structure and function, which may be experimentally validated.

https://jpet.aspetjournals.org/content/jpet/early/2004/02/26/jpet.103.059972.full.pdf

Structures and Models of Transporter Proteins

A database system and computer programs for storage and retrieval of information about guanine nucleotide-binding protein (G protein) -coupled receptor mutants and associated biological effects have been developed. Mutation data on the receptors were collected from the literature and a database of mutants and effects of mutations was developed. The G protein-coupled receptor, family A, point mutation database (GRAP) provides detailed information on ligand-binding and signal transduction properties of more than 2130 receptor mutants. The amino acid sequences of receptors for which mutation experiments have been reported were aligned, and from this alignment mutation data may be retrieved. Alternatively, a search form allowing detailed specification of which mutants to retrieve may be used, for example, to search for specific amino acid substitutions, substitutions in specific protein domains or reported biological effects. Furthermore, ligand and bibliographic oriented queries may be performed. GRAP is available on the Internet (URL: http://www-grap.fagmed.uit.no/GRAP/+ +homepage.html) using the World-Wide Web system.

Svein G. Dahl

Papers

Mechanism-Based Pharmacokinetic–Pharmacodynamic Modeling—A New Classification of Biomarkers

Plasma level monitoring of antipsychotic drugs. Clinical utility.

Molecular dynamics of dopamine at the D2 receptor.

Structures and Models of Transporter Proteins

A database of mutants and effects of site‐directed mutagenesis experiments on G protein‐coupled receptors