An approach to the modeling of the tolerance mechanism in the drug effect. II: On the implications of compensatory regulation

In the previous paper (Peper et al., 1987: J. theor. Biol. 127, 413), a model of drug tolerance was developed based on the assumption that the decrease of drug effect after repeated administration of a drug is caused by the involved regulations in the organism adapting themselves to the presence of the drug. In the present paper, the behaviour of the model is studied with respect to the dose-response relation, the drug effect in dependent and non-dependent subjects and withdrawal symptoms. Computer simulations demonstrate the model to be highly sensitive to sudden changes of drug dose. Dependent on the open loop gain of the adaptive mechanism, a sudden decrease of drug dose might result in an effect opposite to the common drug effect. In the model, the rate of decrease of drug dose necessary for optimal drug withdrawal appears to be determined by the same mechanism as the rate of increase of dose necessary for a constant effect at the commencement of treatment. The behaviour of the model suggests the degree of drug dependence in an addicted subject to depend on the extent to which non-somatic factors are involved in the process of initiation of the adaptive mechanisms.     

An information theoretic approach to macromolecular modeling: I. Sequence alignments

We are interested in applying the principles of information theory to structural biology calculations. In this article, we explore the information content of an important computational procedure: sequence alignment. Using a reference state developed from exhaustive sequences, we measure alignment statistics and evaluate gap penalties based on first-principle considerations and gap distributions. We show that there are different gap penalties for different alphabet sizes and that the gap penalties can depend on the length of the sequences being aligned. In a companion article, we examine the information content of molecular force fields.     

Time-patterned drug administration: insights from a modeling approach

The physiological effects of a drug depend not only on its molecular structure but also on the time-pattern of its administration. One of the main reasons for the importance of temporal patterns in drug action is biological rhythms—particularly those of circadian period. These rhythms affect most physiological functions as well as drug metabolism, clearance, and dynamic processes that may alter drug availability and target cell responsiveness with reference to biological time. We present an overview of the importance of time-patterned signals in physiology focused on the insights provided by a modeling approach. We first discuss examples of pulsatile intercellular communication by hormones such as gonadotropin-releasing hormone, and by cyclic adenosine monophosphate (cAMP) signals in Dictyostelium amoebae. Models based on reversible receptor desensitization account in both cases for the existence of optimal patterns of pulsatile signaling. Turning to circadian rhythms, we examine how models can be used to account for the response of 24h patterns to external stimuli such as light pulses or gene expression, and to predict how to restore the physiological characteristics of altered rhythms. Time-patterned treatments of cancer involve two distinct lines of research. The first, currently evaluated in clinical trials, relies on circadian chronomodulation of anticancer drugs, while the second, mostly based on theoretical studies, involves a resonance phenomenon with the cell-cycle length. We discuss the implications of modeling studies to improve the temporal patterning of drug administration.     

Time-patterned drug administration: insights from a modeling approach

The physiological effects of a drug depend not only on its molecular structure but also on the time-pattern of its administration. One of the main reasons for the importance of temporal patterns in drug action is biological rhythms—particularly those of circadian period. These rhythms affect most physiological functions as well as drug metabolism, clearance, and dynamic processes that may alter drug availability and target cell responsiveness with reference to biological time. We present an overview of the importance of time-patterned signals in physiology focused on the insights provided by a modeling approach. We first discuss examples of pulsatile intercellular communication by hormones such as gonadotropin-releasing hormone, and by cyclic adenosine monophosphate (cAMP) signals in Dictyostelium amoebae. Models based on reversible receptor desensitization account in both cases for the existence of optimal patterns of pulsatile signaling. Turning to circadian rhythms, we examine how models can be used to account for the response of 24h patterns to external stimuli such as light pulses or gene expression, and to predict how to restore the physiological characteristics of altered rhythms. Time-patterned treatments of cancer involve two distinct lines of research. The first, currently evaluated in clinical trials, relies on circadian chronomodulation of anticancer drugs, while the second, mostly based on theoretical studies, involves a resonance phenomenon with the cell-cycle length. We discuss the implications of modeling studies to improve the temporal patterning of drug administration.     

Neonatal tolerance to hypoxia: a comparative-physiological approach.

Newborn mammals exhibit a number of physiological reactions which differ from normal adult physiology and are often regarded as signs of immaturity. However, when looked upon from a comparative point of view, it becomes obvious that some of these 'physiological peculiarities' bear striking similarity to adaptation mechanisms known from hypoxia-tolerant animals and may thus contribute to the well-established, yet poorly understood, phenomenon of neonatal hypoxia tolerance. As the mammalian fetus lives at oxygen partial pressures corresponding to 8000 m altitude, the first line of perinatal hypoxia defense consists of long-term adaptations to limited intrauterine oxygen supply: (1) improved O2 transport by fetal acclimatization to high altitude, (2) reduced metabolic rate by hibernation-like deviation from metabolic size allometry, (3) diminished cerebral vulnerability by functional analogies to diving turtle brain, and (4) enhanced metabolic flexibility by optional repartitioning of energy supply from growth to maintenance metabolism. In the case of birth asphyxia, these background mechanisms are complemented by short-term responses to acute oxygen lack: (1) reduction of body temperature as in natural torpor, (2) reduction of heart rate and redistribution of circulation as in diving mammals, (3) reduction of respiration rate typical of 'hypoxic hypometabolism', and (4) reduction of blood pH according to the concept of 'acidotic torpidity'. Although anaerobic metabolism is improved in neonatal mammals by increased glycogen stores, reduced metabolic demands, and sustained wash-out of acid metabolites, neonatal hypoxia tolerance seems to be primarily based on the ability to maintain tissue aerobiosis as long as possible. This is even reflected by isoenzyme patterns which do not consistently favour anaerobic glycolysis and, thus, are reminiscent of the 'lactate paradox' found in high altitude adaptation. Altogether, from a biological point of view, the perinatal period appears as a source of adaptive mechanisms that can be refound, in varying combinations, in many survival strategies. From a clinical point of view, the interplay of long- and short-term mechanisms offers a novel approach to estimation of the newborn's ability to withstand temporary oxygen lack. However, most of these mechanisms are not unambiguous and, above all, not unlimited in their protective effect so that they do not release obstetricians or neonatologists from their obligation to counteract fetal or neonatal hypoxia without delay.     

An information theoretic approach to macromolecular modeling: II. Force fields

In this article, we explore the information content of molecular force-field calculations. We make use of exhaustive lattice models of molecular conformations and reduced alphabet sequences to determine the relative resolving power of pairwise interaction-based force fields. We find that sequence-specific interactions that operate over longer distances offer greater amounts of information than nearest-neighbor or non-sequence-specific interactions. In a companion article in this issue, we explored the information content of sequence alignment procedures and the calculation of gap penalties. Both articles have implications for protein and nucleic-acid computations.     

A theory of drug tolerance and dependence I: a conceptual analysis

A mathematical model of drug tolerance and its underlying theory is presented. The model extends a first approach, published previously. The model is essentially more complex than the generally used model of homeostasis, which is demonstrated to fail in describing tolerance development to repeated drug administrations. The model assumes the development of tolerance to a repeatedly administered drug to be the result of a regulated adaptive process. The oral detection and analysis of exogenous substances is proposed to be the primary stimulus for the mechanism of drug tolerance. Anticipation and environmental cues are in the model considered secondary stimuli, becoming primary only in dependence and addiction or when the drug administration bypasses the natural-oral-route, as is the case when drugs are administered intravenously. The model considers adaptation to the effect of a drug and adaptation to the interval between drug taking autonomous tolerance processes. Simulations with the mathematical model demonstrate the model's behavior to be consistent with important characteristics of the development of tolerance to repeatedly administered drugs: the gradual decrease in drug effect when tolerance develops, the high sensitivity to small changes in drug dose, the rebound phenomenon and the large reactions following withdrawal in dependence. The mathematical model verifies the proposed theory and provides a basis for the implementation of mathematical models of specific physiological processes. In addition, it establishes a relation between the drug dose at any moment, and the resulting drug effect and relates the magnitude of the reactions following withdrawal to the rate of tolerance and other parameters involved in the tolerance process. The present paper analyses the concept behind the model. The next paper discusses the mathematical model.     

Sitamaquine as a putative antileishmanial drug candidate: from the mechanism of action to the risk of drug resistance

Sitamaquine is a 8-aminoquinoline in development for the treatment of visceral leishmaniasis by oral route, no activity being observed on the experimental cutaneous leishmaniasis experimental models. Recent data explain how sitamaquine accumulate in Leishmania parasites, however its molecular targets remain to be identified. An advantage of sitamaquine is its short elimination half-life, preventing a rapid resistance emergence. The antileishmanial action of its metabolites is not known. The selection of a sitamaquine-resistant clone of L. donovani in laboratory and the phase II clinical trials pointing out some adverse effects such as methemoglobinemia and nephrotoxicity are considered for a further development decision.     

The iterative two-stage population approach to IVGTT minimal modeling: improved precision with reduced sampling. Intravenous glucose tolerance test

The minimal model method is widely used to estimate glucose effectiveness (S(G)) and insulin sensitivity (S(I)) from intravenous glucose tolerance test (IVGTT) data. In the standard protocol (sIVGTT, 0.33 g/kg glucose bolus given at time 0), which allows the simultaneous assessment of beta-cell function, the precision of the individualized estimates often degrades and particularly so in the presence of reduced sampling schedules. Here, we investigated the use of a population approach, the iterative two-stage (ITS) approach, to analyze 16 sIVGTTs in healthy subjects and to obtain refined estimates of S(G) and S(I) in the population and in the individual subjects. The ITS is based on calculation of the population mean and standard deviation of the parameters at each iteration and then use of them as prior information for the individual analyses. Theoretically, the use of a prior in the ITS should improve the precision of the individual estimates. The customary approach (standard two stage, STS), where modeling is performed separately for each individual subject, does not take the population knowledge into account. We used both frequent (FSS, 30 samples) and (quasi-optimally) reduced (RSS, 14 samples) sampling schedules. For the FSS, STS gave estimates (mean +/- SD) for S(G) = 2.66 +/- 1.09 x 10(-2). min(-1) and S(I) = 6.46 +/- 6.99 10(-4). min(-1). microU(-1). ml, with an average precision of 51 (range 5-176) and 33% (3-91), respectively. RSS radically worsened the precision of both S(G) and S(I). However, RSS and ITS gave S(G) = 2.59 +/- 0.73 and S(I) = 6.06 +/- 7.28, with an average precision of 23 (12-42) and 27% (), respectively. In conclusion, population minimal modeling of sIVGTT data improves the precision of individual estimates of glucose effectiveness and insulin sensitivity, as the theory predicts, and, even with reduced sampling, the improvement is substantial.     

Structure-activity relationships of benzothiazole and benzimidazole anthelmintics: a molecular modeling approach to in vivo drug efficacy

An investigation of the biochemical effects of an anthelmintic, tioxidazole (TIOX, methyl 6-[n-propoxy]benzothiazole-2-carbamate), on Hymenolepis diminuta in experimentally infected rats is reported. The chemotherapeutic actions of TIOX on H. diminuta in vivo were accompanied by marked changes in worm weight and chemical composition. Tapeworms recovered from rats that had received a therapeutically effective dose of TIOX 24 hr earlier were significantly smaller and contained much less glycogen (as a percentage of the wet weight) than worms from untreated controls. In TIOX-treated worms, protein concentrations rose at a rate sufficient to offset the decline in glycogen concentration. Glycogen/protein ratios in TIOX-treated worms were considerably lower than the corresponding control-values. Differences in the absolute amounts of glycogen and protein between control and drug-treated worms were even more pronounced. Administration of a subcurative dose of TIOX to the rat produced in H. diminuta another change, the onset of which preceded the gross alterations in worm weight and chemical composition. In vitro studies, carried out 18 hr after treatment, revealed that TIOX-treated worms absorbed and metabolized much smaller quantities of exogenous glucose than did the controls and that the ability of the worm to accumulate glucose against a concentration difference was significantly depressed. A mode of action common to the structurally related benzothiazole and benzimidazole anthelmintics is indicated by the similarity of their biochemical and physiological effects on the tapeworms and their time course of action when administered to rats infected with H. diminuta. Molecular modeling revealed that the benzothiazole and benzimidazole anthelminitics are congruent electronically and structurally. In vivo drug efficacy depends upon the magnitude of the molecular dipole moment and the percentage of polar surface area. Within the benzimidazole series, structural and electronic congruence is found between the 2-thiazolyl and 2-methyl carbamate groups, suggesting that these groups behave similarly in transport to, and binding at, the active site. Finally, anthelmintics that have the 5' substituents twisted out-of-plane were more active than those anthelminitics with 5' substituents in-plane. All of these factors implicate a highly polar, L-shaped cleft to which the anthelmintics bind at the active site.     

The effect of continuous physical disturbance on mayflies of a tropical stream: an experimental approach

Field experiments to examine the effect of continuous physical disturbance on the Ephemeroptera of the Naro Moru River, Kenya, wereundertaken from June 1993 to January 1994. Continuous disturbance wasadministered on a randomly selected subsite of the sediment surface.Artificial physical disturbance within the experimental subsite involvedcontinuous local displacement, shifting and stirring of the streambedsurface substrates (about 10 cm depth) by hand every one minute for 10 or 14min. Three control samples were also taken randomly from the sedimentsurface of an undisturbed stratified area of the study riffle at the startof each disturbance occasion. All samples were collected using a Hesssampler (surface sampling area of 3.142 dm²; meshsize 80μm). Seven mayfly species were particularly abundant and these included Afronurus sp., Afroptilum sudafricanum LESTAGE, Baetis s.l., Baetis(Nigrobaetis) sp. 1, Baetis (Nigrobaetis) sp. 2, Caenis sp. and Choroterpes(Euthraulus) sp. About 83,8% of the total mayfly density and88.1% of the biomass were removed from the streambed surface withinthe first three minutes of continuous physical disturbance. A mayfly biomassof 33.7391 mg dm² and total density of 1357.6 inddm² were collected from the disturbed subsite during the studyduration. Further, a biomass of about 42.8335 mg dm⁻²and total density of 2366 ind dm⁻² were collected fromthe control sites. There was a near-complete depletion of mayflyindividuals from the topmost sediment layer within 14 min of continuousdisturbance. This revised version was published online in July 2006 with corrections to the Cover Date.     

Systems modeling: a pathway to drug discovery

Systems modeling is emerging as a valuable tool in therapeutics. This is seen by the increasing use of clinically relevant computational models and a rise in systems biology companies working with the pharmaceutical industry. Systems models have helped understand the effects of pharmacological intervention at receptor, intracellular and intercellular communication stages of cell signaling. For instance, angiogenesis models at the ligand-receptor interaction level have suggested explanations for the failure of therapies for cardiovascular disease. Intracellular models of myeloma signaling have been used to explore alternative drug targets and treatment schedules. Finally, modeling has suggested novel approaches to treating disorders of intercellular communication, such as diabetes. Systems modeling can thus fill an important niche in therapeutics by making drug discovery a faster and more systematic process.     

An in silico modeling approach to understanding the dynamics of sarcoidosis

Background

Sarcoidosis is a polygenic disease with diverse phenotypic presentations characterized by an abnormal antigen-mediated Th1 type immune response. At present, progress towards understanding sarcoidosis disease mechanisms and the development of novel treatments is limited by constraints attendant to conducting human research in a rare disease in the absence of relevant animal models. We sought to develop a computational model to enhance our understanding of the pathological mechanisms of and predict potential treatments of sarcoidosis.

Methodology/Results

Based upon the literature, we developed a computational model of known interactions between essential immune cells (antigen-presenting macrophages, effector and regulatory T cells) and cytokine mediators (IL-2, TNFα, IFNγ) of granulomatous inflammation during sarcoidosis. The dynamics of these interactions are described by a set of ordinary differential equations. The model predicts bistable switching behavior which is consistent with normal (self-limited) and “sarcoidosis-like” (sustained) activation of the inflammatory components of the system following a single antigen challenge. By perturbing the influence of model components using inhibitors of the cytokine mediators, distinct clinically relevant disease phenotypes were represented. Finally, the model was shown to be useful for pre-clinical testing of therapies based upon molecular targets and dose-effect relationships.

Conclusions/Significance

Our work illustrates a dynamic computer simulation of granulomatous inflammation scenarios that is useful for the investigation of disease mechanisms and for pre-clinical therapeutic testing. In lieu of relevant in vitro or animal surrogates, our model may provide for the screening of potential therapies for specific sarcoidosis disease phenotypes in advance of expensive clinical trials.     

In vitro effect of cryptophycin 52 on microtubule assembly and tubulin: molecular modeling of the mechanism of action of a new antimitotic drug.

Cryptophycin 52 (C52) is a new synthetic compound of the cryptophycin family of antitumor agents that is currently undergoing clinical evaluation for cancer chemotherapy. The cryptophycin class of compounds acts on microtubules. This report details the mechanism by which C52 substoichiometrically inhibits tubulin self-assembly into microtubules. The inhibition data were analyzed through a model described by Perez-Ramirez [Perez-Ramirez, B., Andreu, J. M., Gorbunoff, M. J., and Timasheff, S. N. (1996) Biochemistry 35, 3277-3285]. We thereby determined the values of the apparent binding constant of the tubulin-C52 complex to the end of a growing microtubule (K(i)) and the apparent binding constant of C52 to tubulin (K(b)). The binding of C52 depended on tubulin concentration, and binding induced changes in the sedimentation pattern of tubulin, which indicates that C52 induces the self-association of tubulin and tubulin aggregates other than microtubules. Using analytical ultracentrifugation and electron microscopy, we show that C52 induces tubulin to form ring-shaped oligomers (single rings). We also show that C52 inhibits the formation of double rings from either GTP- or GDP-tubulin. In addition, the advances made by electron crystallography in understanding the structure of the tubulin and the microtubule allowed us to visualize the putative binding site of C52 and to reconstruct C52-induced ring oligomers by molecular modeling.     

Salt tolerance in Aster tripolium L. I. The effect of salinity on growth

Abstract A study of the growth of the maritime halophyte Aster tripolium L. has been carried out over a range of salinity treatments. The regression approach to growth analysis using frequent small harvests has been used to allow ‘continuous’ measurement of growth over a period of 36 d. Salinity was applied with the major ions present in ratios typical of those found in seawater. Growth was inhibited in terms of both dry weight production and leaf expansion at salinity levels equivalent to 0.625 strength sea water (full culture solution 300) and above, with the greatest effect being seen in terms of leaf area. Aster tripolium did not show increased succulence at high salinity, leaf fresh weight to dry weight ratio in fact declined, whilst leaf fresh weight per unit area remained constant. It should be noted that the plants exhibit low growth rates due to the low light intensity used.     

Microbial metabolism as an evolutionary response: the cybernetic approach to modeling

The growth and metabolic capabilities of microorganisms depend on their interactions with the culture medium. Many media contain two or more key substrates, and an organism may have different preferences for the components. Microorganisms adjust their preferences according to the prevailing conditions so as to favor their own survival. Cybernetic modeling describes this evolutionary strategy by defining a goal that an organism tries to attain optimally at all times. The goal is often, but not always, maximization of growth, and it may require the cells to manipulate their metabolic processes in response to changing environmental conditions. The cybernetic approach overcomes some of the limitations of metabolic control analysis (MCA), but it does not substitute MCA. Here we review the development of the cybernetic modeling of microbial metabolism, how it may be combined with MCA, and what improvements are needed to make it a viable technique for industrial fermentation processes.