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PubMed1999

Drug interactions of HIV protease inhibitors.

All the currently available protease inhibitors are metabolised by the cytochrome P450 (CYP) enzyme system. All are inhibitors of CYP3A4, ranging from weak inhibition for saquinavir to very potent inhibition for ritonavir. Thus, they are predicted to have numerous drug interactions, although few such interactions have actually been documented either in pharmacokinetic studies or in clinical reports. This article reviews the published literature with an emphasis on the magnitude of interactions and on practical recommendations for management. Many of the drugs commonly taken by patients with HIV have a strong potential to interact with the protease inhibitors. In particular, the non-nucleoside reverse transcriptase inhibitors are also metabolised by CYPand have been shown to interact with protease inhibitors. Delaviridine is an inhibitor of CYP3A4, but nevirapine and efavirenz are inducers of CYP3A4. The protease inhibitors also interact with each other, and these interactions are being explored for their potential therapeutic benefits. Other commonly used drugs are also known to affect protease inhibitor metabolism, including inhibitors such as clarithromycin and the azole antifungals and inducers such as the rifamycins. Drugs that are known to be significantly affected by the protease inhibitors include ethinylestradiol and terfenadine; many other drugs have lesser or potential interactions. Although little specific data is available on the drug interactions of protease inhibitors, this lack of data should not be interpreted as a lack of interaction. Retrospective chart reviews have demonstrated that potentially severe drug interactions are frequently overlooked. Much more clinical data is needed, but pharmacists and physicians must always be vigilant for drug interactions, both those that are already documented and those that are predictable from pharmacokinetic profiles, in patients receiving protease inhibitors.

Anti-Infective Agents↗
PubMed2005

Prevalence of potentially severe drug-drug interactions in ambulatory patients with dyslipidaemia receiving HMG-CoA reductase inhibitor therapy.

BACKGROUND: Drug-drug interactions (DDIs) are a well known risk factor for adverse drug reactions. HMG-CoA reductase inhibitors ('statins') are a cornerstone in the treatment of dyslipidaemia and patients with dyslipidaemia are concomitantly treated with a variety of additional drugs. Since DDIs are associated with adverse reactions, we performed a cross-sectional study to assess the prevalence of potentially critical drug-drug and drug-statin interactions in an outpatient adult population with dyslipidaemia. METHODS: Data from patients with dyslipidaemia treated with a statin were collected from 242 practitioners from different parts of Switzerland. The medication list was screened for potentially harmful DDIs with statins or other drugs using an interactive electronic drug interaction program. RESULTS: We included 2742 ambulatory statin-treated patients (mean age +/- SD 65.1 +/- 11.1 years; 61.6% males) with (mean +/- SD) 3.2 +/- 1.6 diagnoses and 4.9 +/- 2.4 drugs prescribed. Of those, 190 patients (6.9%) had a total of 198 potentially harmful drug-statin interactions. Interacting drugs were fibrates or nicotinic acid (9.5% of patients with drug-statin interactions), cytochrome P450 (CYP) 3A4 inhibitors (70.5%), digoxin (22.6%) or ciclosporin (cyclosporine) [1.6%]. The proportion of patients with a potential drug-statin interaction was 12.1% for simvastatin, 10.0% for atorvastatin, 3.8% for fluvastatin and 0.3% for pravastatin. Additionally, the program identified 393 potentially critical non-statin DDIs in 288 patients. CONCLUSIONS: CYP3A4 inhibitors are the most frequent cause of potential drug interactions with statins. As the risk for developing rhabdomyolysis is increased in patients with drug-statin interactions, clinicians should be aware of the most frequently observed drug-statin interactions and how these interactions can be avoided.

Aged↗
PubMed1996

Drug interactions with antiviral drugs.

Antiviral drug interactions are a particular problem among immuno-compromised patients because these patients are often receiving multiple different drugs, i.e. antiretroviral drugs and drugs effective against herpesvirus. The combination of zidovudine and other antiretroviral drugs with different adverse event profiles, such as didanosine, zalcitabine and lamivudine, appears to be well tolerated and no relevant pharmacokinetic interactions have been detected. The adverse effects of didanosine and zalcitabine (i.e. peripheral neuropathy and pancreatitis) should be taken into account when administering these drugs with other drugs with the same tolerability profile. Coadministration of zidovudine and ganciclovir should be avoided because of the high rate of haematological intolerance. In contrast, zidovudine and foscarnet have synergistic effect and no pharmacokinetic interaction has been detected. No major change in zidovudine pharmacokinetics was seen when the drug was combined with aciclovir, famciclovir or interferons. However, concomitant use of zidovudine and ribavirin is not advised. Although no pharmacokinetic interaction was documented when didanosine was first administered with intravenous ganciclovir, recent studies have shown that concentration of didanosine are increased by 50% or more when coadministered with intravenous or oral ganciclovir. The mechanism of this interaction has not been elucidated. Lack of pharmacokinetic interaction was demonstrated between foscarnet and didanosine or ganciclovir. Clinical trials have shown that zidovudine can be administered safely with paracetamol (acetaminophen), nonsteroidal anti-inflammatory drugs, oxazepam or codeine. Inhibition of zidovudine glucuronidation has been demonstrated with fluconazole, atovaquone, valproic acid (valproate sodium), methadone, probenecid and inosine pranobex; however, the clinical consequences of this have not been fully investigated. No interaction has been demonstrated with didanosine per se but care should be taken of interaction with the high pH buffer included in the tablet formulation. Drugs that need an acidic pH for absorption (ketoconazole, itraconazole but not fluconazole, dapsone, pyrimethamine) or those that can be chelated by the ions of the buffer (quinolones and tetracyclines) should be administered 2 hours before or 6 hours after didanosine. Very few interaction studies have been undertaken with other antiviral drugs. Coadministration of zalcitabine with the antacid 'Maalox' results in a reduction of its absorption. Dapsone does not influence the disposition of zalcitabine. Cotrimoxazole (trimethoprim-sulfamethoxazole) causes an increase in lamivudine concentrations by 43%. Saquinavir, delavirdine and atevirdine appeared to be metabolised by cytochrome P450 and interactions with enzyme inducers or inhibitors could be anticipated. Some studies showed that interferons can reduce drug metabolism but only a few studies have evaluated the pathways involved. Further studies are required to better understand the clinical consequences of drug interactions with antiviral drugs. Drug-drug interactions should be considered in addition to individual drug clinical benefits and safety profiles.

Antiviral Agents↗
PubMed1997

Selective serotonin reuptake inhibitors and CNS drug interactions. A critical review of the evidence.

The potential for drug-drug interactions in psychiatric patients is very high as combination psychopharmacotherapy used to treat comorbid psychiatric disorders, to treat the adverse effects of a medication, to augment a medication effect or to treat concomitant medical illnesses. Interactions can be pharmacodynamic or pharmacokinetic in nature. This paper focuses on the metabolic kinetic interactions between selective serotonin reuptake inhibitors (SSRIs) and other central nervous system (CNS) drugs. The evidence for and clinical significance of these interactions are reviewed, with special emphasis on antipsychotics, tricyclic antidepressants and benzodiazepines. Many psychotropic medications have an affinity for the cytochrome P450 (CYP) enzymes which promote elimination by transforming lipid soluble substances into more polar compounds. SSRIs serve both as substrates and inhibitors of these enzymes. In vitro studies provide a screening method for evaluating drug affinities for substrates, inhibitors or inducers of CYP enzymes. Although in vitro data are important as a starting point for predicting these metabolic kinetic drug interactions, case reports and controlled experimental studies in humans are required to fully evaluate their clinical significance. Several factors must be considered when evaluating the clinical significance of a potential interaction including: (a) the nature of each drugs' activity at an enzyme site (substrate, inhibitor or inducer); (b) the potency estimations for the inhibitor/inducer; (c) the concentration of the inhibitor/inducer at the enzyme site; (d) the saturability of the enzyme; (e) the extent of metabolism of the substrate through this enzyme (versus alternative metabolic routes); (f) the presence of active metabolites of the substrate; (g) the therapeutic window of the substrate; (h) the inherent enzyme activity of the individual, phenotyping/genotyping information; (i) the level of risk of the individual experiencing adverse effects (e.g. the elderly) and (j) from an epidemiological perspective, the probability of concurrent use. This paper systematically reviews both the in vitro and in vivo evidence for drug interactions between SSRIs and other CNS drugs. As potent inhibitors of CYP2D6, both paroxetine and fluoxetine have the potential to increase the plasma concentrations of antipsychotic medications metabolised through this enzyme, including perphenazine, haloperidol, thioridazine and risperidone in patients who are CYP2D6 extensive metabolisers. Controlled studies have demonstrated this for perphenazine with paroxetine and haloperidol with fluoxetine. Fluvoxamine, as a potent inhibitor of CYP1A2, can inhibit the metabolism of clozapine, resulting in higher plasma concentrations. Drug interactions between the SSRIs and tricyclic antidepressants (TCAs) can occur. Fluoxetine and paroxetine, as potent inhibitors of CYP2D6, can increase the plasma concentrations of secondary and tertiary tricyclic antidepressants. Sertraline and citalopram are less likely to have this effect. Fluvoxamine can increase the plasma concentrations of tertiary TCAs. Fluvoxamine inhibits, via CYP3A. CYP2C19 and CYP1A2, the metabolism of several benzodiazepines, including alprazolam, bromazepam and diazepam. Fluoxetine increases the plasma concentrations of alprazolam and diazepam by inhibiting CYP3A and CYP2C19, respectively. The clinical importance of the interaction with diazepam is attenuated by the presence of its active metabolite. Sertraline inhibits these enzymes only mildely to moderately at usual therapeutic doses. Therefore the potential for interactions is less; however, the in vivo evidence is minimal. Paroxetine and citalopram are unlikely to cause interactions with benzodiazepines. The evidence is conflicting for an interaction between carbamazepine and the SSRIs fluoxetine and fluvoxamine. These combinations should be used cautiously, and be accompanied by monitoring for adverse events and carb

Anti-Anxiety Agents↗
PubMed2005

Design and structure of peptide and peptidomimetic antagonists of protein-protein interaction.

Peptides based on the amino acid sequences found at protein-protein interaction sites make excellent leads for antagonist development. A statistical picture of amino acids involved in protein-protein interactions indicates that proteins recognize and interact with one another through the restricted set of specialized interface amino acid residues, Pro, Ile, Tyr, Trp, Asp and Arg. These amino acids represent residues from each of the three classes of amino acids, hydrophobic, aromatic and charged, with one anionic and one cationic residue at neutral pH. The use of peptides as drug leads has been successfully used to search for antagonists of cell-surface receptors. Peptide, peptidomimetic, and non-peptide organic inhibitors of a class of cell surface receptors, the integrins, currently serve as therapeutic and diagnostic imaging agents. In this review, we discuss the structural features of protein-protein interactions as well as the design of peptides, peptidomimetics, and small organic molecules for the inhibition of protein-protein interactions. Information gained from studying inhibitors of integrin functions is now being applied to the design and testing of inhibitors of other protein-protein interactions. Most drug development progress in the past several decades has been made using the enzyme binding-pocket model of drug targets. Small molecules are designed to fit into the substrate-binding pockets of proteins based on a lock-and-key, induced-fit, or conformational ensemble model of the protein binding site. Traditionally, enzymes have been used as therapeutic drug targets because it was easier to develop rapid, sensitive screening assays, and to find low molecular weight inhibitors that blocked the active site. However, for proteins which interact with other proteins, rather than with small substrate molecules, the lack of binding pockets means that this approach will not generally succeed. There exist many diseases in which the inhibition of protein-protein interactions would provide therapeutic benefit, but there are no general methods available to address such problems. The focus of the first part of this review is to discuss the features of protein-protein interactions which may serve as general guidelines for the development and design of inhibitors for protein-protein interactions. In the second part we focus on the design of peptides (lead compounds) and their conversion into peptidomimetics or small organic molecules for the inhibition of protein-protein interactions. We draw examples from the important and emerging area of integrin-based cell adhesion and show how the principles of protein-protein interactions are followed in the discovery, optimization and usage of specific protein interface peptides as drug leads.

Amino Acids↗
PubMed2005

[Drug interactions in the prescription of medical patients at hospital discharge].

OBJECTIVES: To detect and evaluate the clinical significance of drugs interactions in patients discharged from hospital. MATERIAL AND METHODS: We retrospectively screened the medication for potential drug interactions of 412 patients discharged. Interactions were catalogued according to clinical importance following the Hansten and Horn's classification. RESULTS: Three hundred twenty-nine potential interactions were detected. The 39.9% of the patients had at least one potentially interacting drug combination. The 52.6% of the interactions were catalogued as Class 3, bearing in mind minimizing the risk of the interaction. We did not find any Class 1 or 2 interactions, which have potentially major severity. Oral anticoagulants and digoxin were the most frequently implicated drugs. The patient monitoring was well done in the 100% of the interactions of Oral anticoagulants with other drug, but in the interactions of digoxin with another, this control was not done adequately. One patient was rehospitalised due to high levels of digoxin, he had been discharged with two potential interactions. CONCLUSIONS: The frequently of potential drug interactions in medical patients at hospital discharged was high, but the clinical significance appear to be low.

Adult↗
PubMed2001

Clinical interpretation of pharmacokinetic and pharmacodynamic propofol-opioid interactions.

This manuscript describes the pharmacokinetic and pharmacodynamic interactions between propofol and the opioids. PHARMACOKINETIC INTERACTIONS: In vitro studies describe the reduced clearance of opioids in the presence of propofol, midazolam and etomidate due to interaction at the cytochrome P450 enzyme system. In vivo, however, pharmacokinetic interaction studies by mixed effects modelling predominantly focus on haemodynamic factors affecting distribution and elimination of concomitantly administered agents. In the presence of propofol the elimination clearance and rapid and slow distribution clearance of alfentanil is decreased. Consequently, plasma alfentanil concentrations are increased in the presence of propofol. Vice versa alfentanil reduces propofol elimination clearance and increases the deep volume of distribution. PHARMACODYNAMIC INTERACTIONS: Propofol and the opioids interact in a synergistic manner for various clinical end points. The magnitude of interaction is similar between the various opioids and hypnotic agents, taken into consideration the differences in potency between the opioids. CLINICAL INTERPRETATION OF PK/PD INTERACTIONS: A. Speed of induction. Using PK/PD interaction data speed of induction can be optimised. Of importance are the magnitude of PD interaction between propofol and the various opioids, the rate of administration and the time to peak effect of the agents involved. B. Haemodynamic stability. In ASA 1-2 patients the opioid induced hypnotic dose reduction is not associated with an increased haemodynamic stability of induction of loss of consciousness. In elderly patients or patients known with cardiovascular instability high opioid-low propofol anaesthesia may be associated with improved haemodynamic stability during induction of anaesthesia, however, no data are available regarding this yet. C. Speed of recovery. Time to return of consciousness after termination of propofol-opioid infusions of various duration can be reduced using optimal propofol-opioid concentrations. In general, optimal propofol target concentrations to assure this are 5 micrograms/ml in the presence of fentanyl, 3.5 micrograms/ml in the presence of alfentanil and sufentanil and 2.5 micrograms/ml in the presence of remifentanil. D. Spontaneous respiration. For single agents some data allow proper targeting of a drug concentration that is associated with adequate intraoperative respiration. However, no data exist on drug interactions regarding the respiratory depressant effects of hypnotic-opioid combinations. CONCLUSION: The proper exploration and use of published pharmacokinetic and pharmacodynamic interaction data allows the clinical anaesthesiologist to optimise the clinical administration of propofol and the various opioids when given alone or in combination.

Analgesics, Opioid↗
PubMed1992

Spinal interactions between opioid and noradrenergic agonists in mice: multiplicativity involves delta and alpha-2 receptors.

The nature of the interaction between spinally administered opioid and alpha-2 agonists was investigated using the substance P behavioral test in mice. Morphine and agonists which more selectively activate mu or delta opioid receptors were co-administered intrathecally with direct and indirect acting adrenergic agonists norepinephrine, cocaine or clonidine and the behavioral responses to intrathecally coadministered substance P were evaluated. The ED50 values for agonists administered separately and concurrently were computed and drug interactions were evaluated using isobolographic analyses. After separate administration, all the opioid and adrenergic agonists inhibited the substance P-induced behavioral responses. Upon coadministration of opioid and adrenergic agonists, a multiplicative interaction was observed between morphine or the delta agonist D-Pen2-D-Pen-5-enkephalin and the adrenergic agonists. Additive or antagonistic interactions were found between the mu agonist Tyr-D-Ala-NMe-Phe-Gly(ol) and the same adrenergic agonists. The opioid antagonist naloxone and the alpha-2 adrenergic antagonist idazoxan were given as intrathecal pretreatments at doses chosen to shift the dose-response curves of their corresponding agonist (given alone) 4- to 10-fold to the right; this always resulted in a smaller, but significant (2- to 4-fold) shift in the dose-response curve of the other agonist given alone. Intrathecal pretreatment with naloxone or idazoxan altered some interactions between the opioids and clonidine. Although naloxone blocked completely the multiplicative interaction between morphine and clonidine, idazoxan did not. Both naloxone and idazoxan changed the antagonistic interaction between Tyr-D-Ala-NMe-Phe-Gly(ol) and clonidine to a multiplicative interaction. Neither antagonist blocked the multiplicative interaction between D-Pen2-D-Pen5-enkephalin and clonidine. These results suggest that: 1) interactions between opioid and adrenergic agonists in mouse spinal cord are mediated by delta and alpha-2 receptor subtypes; 2) the synergistic interaction between morphine and alpha-2 adrenergic agonists may involve action at delta opioid receptors; and 3) antagonist action on these drug interactions is complex.

Adrenergic alpha-Antagonists↗
PubMedDate not supplied

Nutritional implications of the interactions between minerals.

It is well recognized that the absorption, retention and metabolism of most essential minerals can be markedly influenced by the presence of antinutrient factors in the diet (i.e. fiber and phytate). However, in addition, interactions can also occur between essential minerals. Indeed, under some circumstances, these interactions can be profound and have significant implications for human health. Interactions between essential minerals can be broadly classified as direct or indirect. Direct interactions are generally competitive phenomena that occur during the intestinal absorption and/or during the tissue utilization of a mineral. Indirect interactions occur when one of the minerals is involved in the metabolism of the other mineral, or when a deficiency or toxicity of one of the minerals results in hormonal changes or tissue damage which affects the metabolism of the other mineral. In this review we have focused our comments on direct interactions between essential minerals, and we present suggested levels at which an excess of a mineral (coined "X") can significantly alter the metabolism of another mineral (coined "Y") for several of the known competitive interactions. This level is characterized as the lowest X/Y ratio of the dietary intakes which has been shown to produce negative consequences on the metabolism of the element Y (assuming the intake of Y is physiological). Moreover, the importance of the physiological status of the animal with regard to the determination of these ratios is discussed. The calculated X/Y ratio at which interactions may be predicted to occur is generally higher than the ratio calculated for most minerals using typical dietary intakes of X and Y in Western-type diets. However, ratios which might be predicted to result in negative interactions do occur in select food products, and can be reached as a consequence of supplementation (either through food enrichment or therapeutic use of supplements). In fact, considering the ready availability of dietary supplements, such interactions may become commonplace. Finally, the interactions between essential and non-essential minerals (heavy metals) are briefly discussed, as are indirect mineral interactions.

Animals↗
PubMed1996

Systematic screening for pharmacokinetic interactions during drug development.

The possible involvement of a new chemical entity in pharmacokinetic drug interactions is an important safety issue. Not all relevant drug combinations for evaluation of the interactive potential of a new drug can be examined. Therefore, experiments should be selected to provide information which is valid not only for the interaction investigated, but which can be extrapolated to other comedications. In this respect the typical approaches currently used, including interaction studies with high risk drugs and compounds frequently given as comedication, or studies involving standard inhibitors and standard substrates are unsatisfactory. A better approach is to characterize drugs according to their effects on the underlying pharmacokinetic processes. Indeed, recent progress in understanding drug interaction mechanisms and in the development and refinement of in vitro test systems enables in many cases experiments to be designed which predict the occurrence of drug interactions. This paper illustrates systematic investigational procedures based on mechanism of interaction. Interaction mechanisms involving drug absorption, distribution, metabolism, and/or excretion are briefly summarized. Detailed proposals are derived which allow identification of the possible role of a new drug in interaction mechanisms for which valid test systems are available. Emphasis is placed on the rational selection of experiments with optimal cost-effectiveness. In vitro methods are integrated in the schemes wherever possible. In addition, it is proposed that pharmacoepidemiological screening, starting in phase II of drug development, be used to identify those relevant drug interactions missed by the mechanism-based approach. As exemplified by several recently discovered interactions it should be possible, by implementation of the proposed procedure, to avoid most serious unexpected adverse effects due to pharmacokinetic drug interactions.

Animals↗
PubMedDate not supplied

Automatic annotation of BIND molecular interactions from three-dimensional structures.

Software to automate the process of extracting molecular interactions from three-dimensional (3D) structures has been developed that records these as Biomolecular Interaction Network Database (BIND) pairwise interaction records. Full annotation of BIND records is provided through a database processing tool called MMDBind, including detailed atom-atom and residue-residue level interaction information. BIND three-dimensional interaction annotation is synthesized by combining information from the Molecular Modeling Database (MMDB), and the HET (heterogen) group dictionary of small molecules in the macromolecular Crystallographic Information Format (mmCIF). Interactions are validated using the Protein Quaternary Structure (PQS) system. A total of 18,166 interactions were removed as being redundant or biologically irrelevant after PQS validation. This first pass MMDBind annotation creates two new divisions of BIND, 3D Biopolymers (BIND-3DBP) comprising 16,737 initial interaction records, and 3D Small Molecules (BIND-3DSM) comprising 48,219 records. Visualization of interacting residues and nucleotides within a macromolecular structure is possible directly from the BIND database owing to added 3D feature annotation within the BIND records that can be conveniently seen using Cn3D ("see-in-3D") after query from the BIND Data Manager. These interaction records provide a further demonstration of the completeness of the BIND data specification and its capabilities as storage and exchange format for all kinds of molecular interactions, including RNA, DNA, protein, and small molecules. Data from the 3DBP and 3DSM sets are available for downloading in Abstract Syntax Notation.1 (ASN.1) or Extensible Markup Language (XML) formats at ftp://ftp.bind.ca/DB/MMDBBind. Data from the 3DBP set is available for interactive query from the BIND Data Manager at www.bind.ca.

Crystallography, X-Ray↗
PubMed1982

Analysis of inphase interaction pattern in EEG.

Inphase interactions among EEG signals recorded using eight electrodes were investigated. The inphase interaction parameters are presented in two ways: (1) matrix form in which the number of inphase interactions are tabulated; and (2) histogram in which the number of inphase interactions are plotted pair-wise between two sites as a function of phase delays in milliseconds. The highest number of interactions occurs between 0 and 8 ms in normal brains. The values of interactions parameters are enhanced by various activities. For example, inphase interaction parameters increase in the motor area in the right hemisphere if the EEG is recorded during repeated left fist clenching. Inphase interactions are drastically altered by the presence of a tumor. We studied the inphase interactions of the EEG of a patient having an occipital tumor. The interaction parameters are greatly diminished in this area, indicating a severe impairment of neuronal communications between both hemispheres in the occipital region. The confidence limits of the changes in inphase interaction parameters during fist clenching are tested statistically using the Student's test. The test shows that the interaction parameters increase, in general, with 1-5% confidence limits in respective cortex areas as a result of fist clenching.

Brain↗
PubMed1997

Hydrogen bonding interactions between glutamine and asparagine in alpha-helical peptides.

We have measured the strength of a Gln-Asn side-chain-side-chain interaction spaced i, i+4 in an alpha-helix by placing pairs of interacting residues in the middle, N and C termini of Ala-based peptides. Experimental helicities for peptides containing Gln-Asn spaced i, i+4, as measured by circular dichroism, are considerably higher than those of a peptide with Gln-Asn spaced i, i+5, and that predicted by a modified form of Lifson-Roig helix-coil transition theory that does not include side-chain interactions. A model that includes side-chain-side-chain interactions successfully fits the experimental data and gives a free energy of interaction of between -0.4 and -0.7 kcal mol-1. This favourable interaction is evident in a statistical survey of alpha-helices from a set of non-homologous crystal structures. The Asn-Gln orientation has an interaction energy of less than that of Gln-Asn and close to zero. This difference shows that the free energy of interaction is sensitive to the geometry of the interacting groups. Because i, i+4 interactions can occur only when the side-chain chi1 angle of residue i is trans and that of residue i+4 is gauche+, and because side-chains are free to rotate in peptides, we have corrected interaction free energies from this and other studies to remove the conformational entropy cost of placing them in these conformations so that they are comparable with studies of hydrogen bonding in mutant proteins. The corrected DeltaG is -1 kcal mol-1, which is slightly lower than that reported for hydrogen bonds in folded proteins; however, this value is similar to that for hydrophobic i, i+4 interactions in peptides. We conclude that even in highly mobile, surface-exposed regions, hydrogen bonds can significantly stabilise proteins, provided that their geometric requirements can be achieved.

Asparagine↗
PubMed1997

Psychophysiological and modulatory interactions in neuroimaging.

In this paper we introduce the idea of explaining responses, in one cortical area, in terms of an interaction between the influence of another area and some experimental (sensory or task-related) parameter. We refer to these effects as psychophysiological interactions and relate them to interactions based solely on experimental factors (i.e., psychological interactions), in factorial designs, and interactions among neurophysiological measurements (i.e., physiological interactions). We have framed psychophysiological interactions in terms of functional integration by noting that the degree to which the activity in one area can be predicted, on the basis of activity in another, corresponds to the contribution of the second to the first, where this contribution can be related to effective connectivity. A psychophysiological interaction means that the contribution of one area to another changes significantly with the experimental or psychological context. Alternatively these interactions can be thought of as a contribution-dependent change in regional responses to an experimental or psychological factor. In other words the contribution can be thought of as modulating the responses elicited by a particular stimulus or psychological process. The potential importance of this approach lies in (i) conferring a degree of functional specificity on this aspect of effective connectivity and (ii) providing a model of modulation, where the contribution from a distal area can be considered to modulate responses to the psychological or stimulus-specific factor defining the interaction. Although distinct in neurobiological terms, these are equivalent perspectives on the same underlying interaction. We illustrate these points using a functional magnetic resonance imaging study of attention to visual motion and a position emission tomography study of visual priming. We focus on interactions among extrastriate, inferotemporal, and posterior parietal regions during visual processing, under different attentional and perceptual conditions.

Attention↗
PubMed1977

Ipsilateral utricular and semicircular canal interactions from electrical stimulation of individual vestibular nerve branches recorded in the descending medial longitudinal fasciculus.

Interactions from electrical stimulation of individual vestibular end organ nerves recorded from second order vestibular neurons projecting caudally in the medial longitudinal fasciculus (MLF) have been investigated in unanesthetized, decerebrate decerebellate cats. Canal-canal and utricle-canal interactions were recorded using various condition-test parameters. The brain stem was sectioned to eliminate influence of the contralateral vestibular nuclei, and the condition-test experiments were repeated. The type of interaction observed (inhibition or facilitation) and the degree to which it occurred were dependent on the MLF recording site. Also, in the case of utricular interactions, these were dependent on the site of utricular stimulation. These dependencies indicate a topological arrangement from receptor cell through the second order neuronal projection pathways. Sectioning of the brain stem produced changes in the interaction patterns, indicating masking and/or balancing of the ipsilateral interactions. In interactions between the anterior and posterior canals, instances of no apparent interaction occurring before sectioning converted to inhibition after sectioning. This indicates that some facilitative interaction occurs involving feedback from the contralateral vestibular nuclei, and this facilitation masks or balances ipsilateral inhibition. In interactions between the anterior and horizontal canals, contralateral inhibitory influence masks ipsilateral facilitatory interactions. Contralateral facilitatory influence again balances ipsilateral inhibition in interactions between the horizontal and posterior canals. The degree of inhibition and facilitation observed indicates that considerably more polysynaptic ipsilateral convergence on second order vestibular neurons occurs than has been demonstrated in intracellular studies. Only inhibition was observed when the anterior canal was conditioned by stimulation of the utricular nerve after sectioning. In all other pairings, mixed effects were observed. It is suggested that this is related to known functional connections of semicircular canal second order neurons with neck motoneurons. Not only is canal output affected by utricular activity, but each canal affects utricular output in a different manner.

Afferent Pathways↗
PubMed1984

The time-course of rod-cone interaction.

The time-course of rod-cone interaction (change of scotopic sensitivity caused by photopic background stimulation) was measured in the presence of briskly exchanged, scotopically matched, 490- and 630-nm background disks. In all conditions, interaction rose and fell quickly with changes of photopic stimulation. When the background was a small 0.6 degree-diameter disk, photopic stimulation produced relatively constant maintained interaction of about 0.6 log units. When the background was a large 7.8 degree-dia disk, photopic stimulation produced larger initial (0.6-1.0 log unit) than maintained (0.2 log unit) interaction. When a 0.6 degree by 7.8 degree annulus was used instead of a background, photopic stimulation produced substantial interaction only at offset, a transitory interaction. Thus, the spatial dependence of transitory interactions differs from that of maintained interaction: transitory interactions can be large even when maintained interaction is small or absent. The results are discussed in terms of a simple center-surround model of rod-cone interaction that unifies both maintained and transient interaction.

Dark Adaptation↗
PubMed1982

Culture-produced subendothelium. II. Effect of plasma, F.VIIIR:WF and fibronectin on interaction of normal platelets with normal and von Willebrand porcine aortic subendothelium.

Culture-produced normal and von Willebrand (vWd) porcine aortic subendothelium (SE) was prepared on glass and fibronectin (FN)-coated surfaces. Washed porcine platelets reacted extensively with normal SE (on glass) as single adherent non-spread and spread (5%) platelets, whereas vWd SE (on glass)-platelet interaction was decreased with no spreading. Normal porcine plasma increased normal SE-platelet interaction 3 to 5-fold and spreading 5-fold (20-30%); vWd SE-platelet interaction was increased 2 to 4-fold with no spreading. vWd porcine plasma did not affect normal or vWd SE-platelet interaction or spreading. Purified porcine F.VIIIR:WF (0.5-2 U/ml) increased both normal and vWd SE-platelet interaction 2 to 4-fold without increasing spreading. Purified human FN (50-200 micrograms/ml) did not increase normal of vWd SE-platelet interaction but increased spreading 5 to 7-fold (25-35%) with normal SE. F.VIIIR:WF (2 U/ml) plus FN (200 micrograms/ml) increased normal SE-platelet interaction 4 to 5-fold and spreading 8 to 9-fold (41%) with extensive SE-associated microaggregate formation; vWd SE-platelet interaction was increased about 6-fold with no spreading. Platelets reacted more extensively with normal and vWd SE prepared on FN-coated surfaces than SE on glass. Normal SE (on FN)-platelet interaction increased 6 to 7-fold and spreading 12-fold (60%); vWd SE (on FN)-platelet interaction increased about 110-fold with about 10% spreading. Plasma (normal and vWd), and F.VIIIR:WF did not significantly increase normal or Vwd SE (on FN)-platelet interaction or spreading. Results suggest a possible role for FN as a spreading factor in SE-platelet interactions.

Animals↗
PubMed2005

Severe acute respiratory syndrome coronavirus membrane protein interacts with nucleocapsid protein mostly through their carboxyl termini by electrostatic attraction.

The severe acute respiratory syndrome coronavirus (SARS-CoV) membrane protein is an abundant virion protein, and its interaction with the nucleocapsid protein is crucial for viral assembly and morphogenesis. Although the interacting region in the nucleocapsid protein was mapped to residues 168-208, the interacting region in the membrane protein and the interaction nature are still unclear. In this work, by using yeast two-hybrid and surface plasmon resonance techniques, the residues 197-221 of the membrane protein and the residues 351-422 of the nucleocapsid protein were determined to be involved in their interaction. Sequence analysis revealed that these two fragments are highly charged at neutral pH, suggesting that their interaction may be of ionic nature. Kinetic assays indicated that the endodomain (aa102-221) of the membrane protein interacts with the nucleocapsid protein with high affinity (K(D)=0.55+/-0.04 microM), however, this interaction could be weakened greatly by acidification, higher salt concentration (400 mM NaCl) and divalent cation (50 mM Ca2+), which suggests that electrostatic attraction might play an important role in this interaction. In addition, it is noted that two highly conserved amino acids (L218 and L219) in the membrane protein are not involved in this interaction. Here, we show that electrostatic interactions between the carboxyl termini of SARS-CoV membrane protein and nucleocapsid protein largely mediate the interaction of these two proteins. These results might facilitate therapeutic strategies aiming at the disruption of the association between SARS-CoV membrane and nucleocapsid proteins.

Nucleocapsid Proteins↗