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Receptor description

Competitive antagonists affinity of, 261-264 description of, 75 IC50 correction factors for, 223 Schild analysis, 261-264 Concentration-dependent antagonism, 99 Concentration-response curve, 13 Confidence intervals, 228-229 Conformations, 13-14 Constitutive activity of receptors description of, 49—51 receptor density and, 56 Schild analysis, 108-111 Context-dependent biological effect, 188 Correction factors, 211-213, 223 Correlational research, 231 CP320626, 128... [Pg.294]

A previously created receptor description file (RDF) can be used (Fig. 1), or a new protein.rdf file (Fig. 2) can be created by pressing Create. The RDF file can be customized by enabling Customize RDF File, which allows the addition of metals, cofactors, or water molecules and the determination of the protonation state of several amino acid residues (Fig. 3) ... [Pg.72]

Fig. 2. Creation of the receptor description file (RDF) for use with FlexX. Protein Structure Specify the correct PDB structure. Active-Site File The FlexX binding pocket can be defined as the amino acid residues within 7 A from a reference structure (e.g., a ligand structure translated to the protein active site midpoint as determined by PASS see Subheading 3.3.2.). Customize RDF File enables specification of metals, cofactors, protonation states, and torsions of residues (see Fig. 3). Fig. 2. Creation of the receptor description file (RDF) for use with FlexX. Protein Structure Specify the correct PDB structure. Active-Site File The FlexX binding pocket can be defined as the amino acid residues within 7 A from a reference structure (e.g., a ligand structure translated to the protein active site midpoint as determined by PASS see Subheading 3.3.2.). Customize RDF File enables specification of metals, cofactors, protonation states, and torsions of residues (see Fig. 3).
Fig. 3. Customization of the receptor description file. Chains allows specification of the chains present in the protein that have to be included (grayed out if only one chain is present) Templates to add specific metals, cofactors, and/or water molecules or determine protonation state of Asp, Cys, Glu, His, Ser Torsions allows setting of the dihedral angle of the terminal hydrogen atom of the specified residue. Fig. 3. Customization of the receptor description file. Chains allows specification of the chains present in the protein that have to be included (grayed out if only one chain is present) Templates to add specific metals, cofactors, and/or water molecules or determine protonation state of Asp, Cys, Glu, His, Ser Torsions allows setting of the dihedral angle of the terminal hydrogen atom of the specified residue.
Jones G, P Willett and R C Glen 1995b. Molecular Recognition of Receptor Sites Using a Geneti Algorithm with a Description of Desolvation. Journal of Molecular Biology 245 43-53. [Pg.739]

B and W J Howe 1991. Computer Design of Bioactive Molecules - A Method for Receptor-Based Novo Ligand Design. Proteins Structure, Function and Genetics 11 314-328. i H L 1965. The Generation of a Unique Machine Description for Chemical Structures - A hnique Developed at Chemical Abstracts Service. Journal of Chemical Documentation 5 107-113. J 1995. Computer-aided Estimation of Symthetic Accessibility. PhD thesis. University of Leeds, itan R, N Bauman, J S Dixon and R Venkataraghavan 1987. Topological Torsion A New )lecular Descriptor for SAR Applications. Comparison with Other Descriptors. Journal of emical Information and Computer Science 27 82-85. [Pg.740]

These, such as the black box that was the receptor at the turn of the century, usually are simple input/output functions with no mechanistic description (i.e., the drug interacts with the receptor and a response ensues). Another type, termed the Parsimonious model, is also simple but has a greater number of estimatable parameters. These do not completely characterize the experimental situation completely but do offer insights into mechanism. Models can be more complex as well. For example, complex models with a large number of estimatable parameters can be used to simulate behavior under a variety of conditions (simulation models). Similarly, complex models for which the number of independently verifiable parameters is low (termed heuristic models) can still be used to describe complex behaviors not apparent by simple inspection of the system. [Pg.43]

Weiss, J. M., Morgan, P. H., Lutz, M. W., and Kenakin, T. P. (1996a). The cubic ternary complex receptor-occupancy model. I. Model description. J. Theroet. Biol. 178 151-167. [Pg.58]

Operational model, devised and published by James Black and Paul Leff (Proc. R. Soc. Lond. Biol. 220,141-162, 1983), this model uses experimental observation to describe the production of a physiological response by an agonist in general terms. It defines affinity and the ability of a drug to induce a response as a value of x, which is a term describing the system (receptor density and efficiency of the cell to convert an activated receptor stimulus into a response) and the agonist (efficacy). It has provided a major advance in the description of functional effects of drugs see Chapter 3.6 for further discussion. [Pg.281]

Cheng-Prasoff relationship, 65-66, 214 Cholecystokinin receptor antagonists, 80 Cimetidine, 9-10 Clark, Alfred J., 3, 3f, 12, 41 Clark plot, 114 Clearance, 165—166 Clinical pharmacokinetics, 165 Cocaine, 149, 150f Competitive antagonism description of, 114 Gaddum equation for, 101-102, 113,... [Pg.294]

Free drug concentration description of, 36-37 measurement of, in receptor compartment, 39 Frovatriptan, 163f Full agonism, 200-202 Full agonists affinity of, 261 description of, 27—30 dose-response curves for, 90, 200-202 Furchgott method for affinity measurements, 261 potency ratios for, 202—204, 219—220 Functional assays... [Pg.295]

One-way analysis of variance, 229-230, 230f—231f Operational model derivation of, 54-55 description of, 45—47, 46f function for variable slope, 55 for inverse agonists, 221 of agonism, 47f orthosteric antagonism, 222 partial agonists with, 124, 220-221 Opium, 147 Orphan receptors, 180 Orthosteric antagonism... [Pg.297]

Screening. See High-throughput screening Second messenger systems calcium ion, 83 description of, 24 production of, 25f Series hyperbolae, 38 Serotonin, 150, 151 f Seven transmembrane receptors, 3-4 Shennong Herbal, 147 Short interfering RNA duplex molecules, 184... [Pg.298]

Tang Herbal, 147 Target-based drug discovery biological targets, 180-184 chemical end point in, 180 chemical tools, 178-179 definition of, 5 description of, 175-177 linear approach, 176 orphan receptors, 180 preclinical process in, 176-177 random variation in gene expression, 178... [Pg.299]


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See also in sourсe #XX -- [ Pg.12 ]




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