M.p. 103°C. Noradrenaline is released in the adrenal medulla with adrenaline, and also at the sympathetic nerve endings. Its release from a nerve fibre is followed by binding to a receptor molecule on the next nerve or muscle fibre, probably causing a change in the electrical charge of the receptor-cell membrane. Biosynthetically it normally serves as a precursor for adrenaline.  [c.282]

In an extensive SFA study of protein receptor-ligand interactions, Leckband and co-workers [114] showed the importance of electrostatic, dispersion, steric, and hydrophobic forces in mediating the strong streptavidin-biotin interaction. Israelachvili and co-workers [66, 115] have measured the Hamaker constant for the dispersion interaction between phospholipid bilayers and find A = 7.5 1.5 X 10 erg in water.  [c.247]

Florin E-L, Moy V T and Gaub FI E 1994 Adhesion forces between individual ligand-receptor pairs Science 264 415  [c.1728]

Direct measurement of the interaction potential between tethered ligand (biotin) and receptor (streptavidin) have been reported by Wong et al [16] and demonstrate the possibility of controlling range and dynamics of specific biologic interactions via a flexible PEG-tether.  [c.1742]

Switching and control ( signal transduction ) in biological systems as elsewhere usually strives to achieve a highly nonlinear response, which inter alia confers a certain immunity from noise onto tire system. Cooperative binding is an easy way to achieve this end. Most signalling in biology is based on tire binding of a ligand L to an unoccupied site S on a receptor B  [c.2824]

If tliere are n independent binding sites per receptor, conservation of mass dictates tliat s = nb - c, where /jq is tire  [c.2824]

Suppose now that the sites are not independent, but that addition of a second (and subsequent) ligand next to a previously bound one (characterized by an equilibrium constant K ) is easier than the addition of the first ligand. In the case of a linear receptor B, the problem is fonnally equivalent to the one-dimensional Ising model of ferromagnetism, and neglecting end effects, one has [M]  [c.2825]

The easiest way to accomplish (ii) is to dilute the supposedly equilibrium bound state and check tliat tire predicted degree of dissociation takes place on tire time scale of tire experiment. This is often inconvenient in homogeneous assays, however. Anotlier check is to incubate tire ligand and receptor for different times r. invariance of c with i would be evidence of equilibrium having been reached, provided tliat tire range of x has been chosen judiciously. One may also compare tire amount bound after adding successive small increments of ligand L to receptor B witli tire amount bound after having added L to B in a single large increment if tire system is in tliennodynamic equilibrium, c should be patli-independent.  [c.2826]

Antibodies binding to an antigen interact witli a relatively small portion of tire molecule. The number Vof foreign antigens which must be recognized by an organism is very large, perhaps greater tlian 10, and tliere is a smaller number V ( 10 ) of self-antigens which must nothe recognized. Yet tire immunoglobulin and T-cell receptors may only contain lO" different motifs. Recognition is presumed to be accomplished by a generalized lock and key mechanism involving complementary amino acid sequences. How large should tire complementary region be, supposing tliat tire system has evolved to optimize tire task [118] (A similar problem is posed by tire olfactory system 11191.) If is tire probability tliat a random receptor recognizes a random antigen, the value of its complement = - P maximizing tire product of tire probabilities tliat each antigen is recognized by at least one receptor, and tliat none of tire self-antigens is recognized, i.e. —, is  [c.2836]

A G (z) is the ligand-receptor interfacial interaction potential (section C2.14.7.1, equation (C2.14.52), equation (C2.14.53) and equation (C2.14.54)), and D is the probability that a particle at q will return to b, equal to the ratio k (b)/k (q)[ 21l  [c.2837]

An examination of the crystal structure of the rat qj thyroid hormone receptor (TR) ligand binding domain bound with a thyroid hormone agonist (Wagner et al., 1995) suggests three entry/exit points for the hormone as shown in Fig. 5a. By applying an external force to the ligand to facilitate its unbinding from the protein, the three possible pathways were explored. In the simulations, the protein-ligand system was surrounded by a water bath. One atom of the hormone was harmonically restrained K = 10 kcal/molA 695 pN/A) to a point moving with a constant velocity V = 0.08 A/ps in a chosen direction. The investigation is still ongoing and presently only preliminary conclusions can be drawn from the SMD data.  [c.48]

Ajay and Murcko, 1995] Ajay, ajid Murcko, M. Computational methods to predict binding free energy in ligand-receptor complexes. J. Med. Chem. 38 (1995) 4953-4967  [c.60]

Damm et al., 1989] Damm, K., Thompson, C. C., and Evans, R. M. Protein encoded by v-eri>A functions as a thyroid-hormone receptor antagonist. Nature. 339 (1989) 593-597  [c.61]

Florin et al., 1994] Florin, E.-L., Moy, V. T., and Gaub, H. E. Adhesion force between individual ligand-receptor pairs. Science. 264 (1994) 415-417  [c.62]

Fig. 4. Typical AFM rupture experiment (top) Receptor molecules are fixed via linker molecules to a surface (left) in the same way, ligand molecules are connected to the AFM cantilever (right). When pulling the cantilever towards the right, the pulling force applied to the ligand can be measured. At the point of rupture of t he ligand-receptor complex the measured force abruptly drops to zero so that the rupture force can be measured. Fig. 4. Typical AFM rupture experiment (top) Receptor molecules are fixed via linker molecules to a surface (left) in the same way, ligand molecules are connected to the AFM cantilever (right). When pulling the cantilever towards the right, the pulling force applied to the ligand can be measured. At the point of rupture of t he ligand-receptor complex the measured force abruptly drops to zero so that the rupture force can be measured.
Computer rupture simulation (bottom) In the course of an MD simulation of the ligand-receptor complex at atomic detail the ligand is pulled towards the right with a computer spring , while the receptor (drawn as a ribbon model) is kept in place. Prom the elongation of the spring the pulling force during the unbinding process is computed, and, thereby, a force profile is obtained. The rupture force is interpreted as the maximum of this force.  [c.85]

E.-L. Florin, V. T. Moy, and H. E. Gaub. Adhesion forces between individual ligand-receptor pairs. Science, 264 415-417, Apr. 15 1994.  [c.96]

Florin, E. V., Moy, T. V., Gaub, H. E. Adhesion forces between individual ligand-receptor pairs. Science 264 (1994) 415-417  [c.146]

The two /3-turn structures, pc and Pe are the most stable among those considered. This is in accord with the unconstrained nanosecond simulations of linear DPDPE, which converged to these conformers [14]. Because the cyclic form is relatively rigid, it is assumed that the conformation it adopts in solution is the biologically active one, responsible for its high affinity and specificity towards the 5 opioid receptor. The relatively low population of the cyclic-like structure for the linear peptide thus agrees qualitatively with the  [c.170]

Bongrand P 1999 Ligand-receptor interactions Rep. Prog. Phys. 62 921  [c.1728]

Protems can be physisorbed or covalently attached to mica. Another method is to innnobilise and orient them by specific binding to receptor-fiinctionalized planar lipid bilayers supported on the mica sheets [15]. These surfaces are then brought into contact in an aqueous electrolyte solution, while the pH and the ionic strength are varied. Corresponding variations in the force-versus-distance curve allow conclusions about protein confomiation and interaction to be drawn [99]. The local electrostatic potential of protein-covered surfaces can hence be detemiined with an accuracy of 5 mV.  [c.1741]

The ligand-receptor complex C has changed properties which typically allow it to undergo furtlier, previously inaccessible reactions (e.g. binding to a DNA promoter sequence). The role of L is to switch B from one of its stable confonnational states to anotlier. The approximate equality of tire intramolecular, molecule-solvent and L-B binding energies is an essential feature of such biological switching reactions. An equilibrimn binding constant K q is defined according to tire law of mass action  [c.2824]

Another important noise-reduction mechanism is to incorjDorate a tlireshold into the responsive apparatus. Essentially this is why antibodies are multidentate, why serial triggering of antigen-presenting cells [59] is necessary, and so on. The benefits of a response tlireshold T in have been thoroughly investigated in the context of radiation detectors [60], and the argument can be adapted to biological detectors. Suppose that L ligands are incident on an area containing R receptors. The number arriving at any particular receptor will fluctuate around X = L/R, the mean number of ligands per receptor, and assuming a Poisson distribution for these fluctuations, the expected number of activated receptors (i.e. those receiving T or more ligands) is fR, where  [c.2825]

Great interest has recently been developed in heterogeneous systems in which B is immobilized to a solid surface and ligand binding measured directly, e.g. using a quartz crystal microbalance (QCM) or an optical metliod such as optical waveguide lightmode spectroscopy (OWLS), ellipsometry or surface plasmon resonance (SPR) [61], i.e. tire solid surface plays a dual role as botli receptor and sensing platfonn. Wlren carried out properly neitlier labelling of tire participating molecules nor calibration of tire response are required, and direct measurement of tire reverse reaction can be accomplished witli ease. These heterogeneous methods are discussed in more detail in section C2.14.7.2.  [c.2826]

Hydrogen donor/acceptor complementarity, complemented by electrostatic complementarity, although this appears to play the minor role, is the basis for a vast effort in computational dmg design based on putative receptor stmctures mostly derived from x-ray crystallography 11111. Calculations based on static stmctures without allowing for subtle stmctural modifications of the binding partners following initial association have produced less than spectacular results attempts are now being made to incoriDorate flexibility into the simulated molecules. The simple idea of docking taking place much as two rigid spacecraft interact is further complicated by the ubiquitous presence of water, itself a strongly hydrogen bonding molecule. Some interactions may involve expulsion of solvent. The omission of water in numerical simulations of docking is likely to be fatal for the accuracy and relevance of the results.  [c.2835]

A conceptually related effect occurs in immune recognition, when a ligand (antigen) present at the surface of an antigen presenting cell (APC) is bound by a T lymphocyte (TL). Binding triggers a confonnational change in the receptor protein to which the antigen is fixed, which initiates further processes within the APC, resulting in the synthesis of more receptors, and so on. Apparently, effective stimulation of these further processes depends on sustained activation at the surface pace the noise-reduction effect of a response threshold discussed in section C2.14.3.3, and cf [M])- This can be accomplished with a few, or even only one TL, provided the affinity is not too high the TL binds, triggers one receptor, then dissociates and binds anew to a nearby untriggered receptor (successive binding attempts in solution are highly correlated [114, 115 and 116]). This serial triggering [ ] can fonnally be described by  [c.2835]

The first predictions of antibody-antigen binding rates were made on the basis of the Smoluchowski equation (C2.14.20). Experimental work suggested a rate about 1000 times slower, which was understood to reflect the rather precise rotational alignment required for two molecules to dock specifically, since the area of the docking zone (epitope) is only a tiny fraction of the total surface area of the antibody. Careful calculations taking this into account indicated that the actual rates should be about a million times slower than those predicted from equation (C2.14.20), and that the experimentally measured rates were therefore a thousand times faster than expected. Two inteiqDretations for the discrepancy were proposed long range attractive forces steering the antigen to the complementary sequence on the antibody [120] and the Franck-Rabinowitsch (cage) effect [114, 116]. It was a notable early achievement of Brownian dynamics (BD) [120, 121 and 122] to elucidate the conditions under which either or both apply. In these simulations, a large number of Brownian trajectories of the ligand are started on the surface of a sphere of radius b centred on the receptor. A fraction (3 tenninate with a successful encounter, and the remainder reach the surface of a quitting sphere of radius q > b. The bimolecular association rate coefficient is (3 (/j)/[l - O (l-(3) ], where  [c.2837]

Percus J K, Percus O E and Perelson A S 1993 Predicting the size of the T-cell receptor and antibody combining region from consideration of efficient self-nonself discrimination Proc. Natl Acad. Sci. USA 90 1691-5  [c.2850]

Lancet D, Sadovsky E and Seidemann E 1993 Probability model for molecular recognition in biological receptor repertoires significance to the olfactory system Proc. Natl Acad. Sci. USA 90 3715-19  [c.2850]

As a first step in imderstanding the analysis of energy transfer experiments, it is wortliwhile to summarize tire steps in a typical experiment where CgFg is tire hot donor and carbon dioxide is tire bath receptor molecule. First, excited  [c.3003]

Molecular recognition and specific ligand-receptor interactions are central to many biochemical processes. The regulation of cellular signal-transduction pathways and gene expression, activity of enzymes, cell motility, molecular immunology and the action of hormones involve the triggering of functional responses by noncovalent associations of ligands with receptors. The prediction and design of ligands (inhibitors or substrates) for a given receptor is the main goal in rational drug design, and considerable effort is spent on the development of corresponding computational methods (Cohen et al., 1990 Colman, 1994 Marrone et al., 1997). New pharmaceuticals, e.g., the HIV protease inhibitors (Thaisrivongs et al., 1996 Lebon et al., 1996 Hanessian and Devasthale, 1996), derived in part from such methods, have made a major impact on clinical medicine, and computational modeling will be of increasing importance in the future.  [c.39]

Despite an abundance of modeling methods for ligand-receptor interactions and protein-protein docking (Strynadka et al., 1996) little is known about processes governed by adhesive interactions such as those occuring in the binding and unbinding of ligands. Presently, the prevailing point of view concerning computer simulations describing ligand binding and determining binding affinities is to strive for the ideal of reversibility, as in umbrella sampling and free energy perturbation (McCammon and Harvey, 1987 Ajay and Murcko, 1995 Gilson et al., 1997), with the hope that artifacts induced by the finite rate of conformational changes can be neglected. Reaching this ideal, however, requires extremely slow manipulation and, therefore, prohibitively expensive simulations. This chapter advocates a new computational method,  [c.39]

In SMD simulations time-dependent external forces are applied, for example, to a ligand to facilitate its unbinding from a protein, as shown in Fig. 1. The analysis of the interactions of the dissociating ligand with the binding pocket, as well as the recording (as a function of time) of applied forces and ligand position, yields important structural information about the structure-function relationships of the ligand-receptor complex, binding pathways, and mechanisms underlying the selectivity of enzymes. SMD can also be applied to investigate the molecular mechanisms that determine elastic properties exhibited by proteins subjected to deformations in AFM and optical tweezer experiments, such as stretching of titin leading to unfolding of its immunoglobulin domains (Rief et ah, 1997), or stretching of tenascin which results in unfolding of its fibronectin-III domains (Oberhauser et ah, 1998).  [c.41]

Besides yielding qualitative information, these biologically and pharmaceutically motivated applications of SMD can also yield quantitative information about the binding potential of the ligand-receptor complex. A first advance in the reconstruction of the thermodynamic potential from SMD data by discounting irreversible work was made by Balsera et al. (1997) as outlined in Sect. Reconstruction of the potential of mean force below.  [c.41]

Hormone binding to the thyroid hormone receptor initiates a series of molecular events culminating in the activation or repression of transcription of target genes. The transition between the bound and unbound form of the thyroid receptor is accompanied by a conformational change that enables the hormone-receptor complex to bind to specific sequences of DNA and other transcriptional coactivators or repressors (Brent et al., 1989 Damm et al., 1989 Andersson et al., 1992). SMD can determine likely pathways of hormone binding and unbinding, reveal components of the receptor involved in the unbinding, and thus contribute to the design of new ligands for hormone therapy.  [c.48]

Moy et al., 1994a] Moy, V. T., Florin, E.-L., and Gaub, H. E. Adhesive forces between ligand and receptor measured by AFM. Colloids and Surfaces. 93 (1994a) 343-348  [c.63]

As an example for an efficient yet quite accurate approximation, in the first part of our contribution we describe a combination of a structure adapted multipole method with a multiple time step scheme (FAMUSAMM — fast multistep structure adapted multipole method) and evaluate its performance. In the second part we present, as a recent application of this method, an MD study of a ligand-receptor unbinding process enforced by single molecule atomic force microscopy. Through comparison of computed unbinding forces with experimental data we evaluate the quality of the simulations. The third part sketches, as a perspective, one way to drastically extend accessible time scales if one restricts oneself to the study of conformational transitions, which arc ubiquitous in proteins and are the elementary steps of many functional conformational motions.  [c.79]

See pages that mention the term Receptor : [c.1709]    [c.2628]    [c.2826]    [c.2835]    [c.2835]    [c.2847]    [c.41]    [c.49]    [c.61]    [c.65]    [c.84]    [c.171]   
Chemoinformatics (2003) -- [ c.326 , c.487 , c.599 ]

Fundamentals of air pollution (1994) -- [ c.0 ]

Industrial ventilation design guidebook (2001) -- [ c.279 , c.1472 ]