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At least 19 recordsLinked to original sources
PubMed2002

Reactions of purines-containing butenolides with L-cysteine or N-acetyl-L-cysteine as model biological nucleophiles: a potent mechanism-based inhibitor of ribonucleotide reductase caused apoptosis in breast carcinoma MCF7 cells.

Thiols are the most reactive nucleophilic reagents among the biological models investigated. The reactivity of butenolides 1a-c, 2-4, and 6-8 toward L-cysteine, a model biological nucleophile, was studied spectrophotometrically. The rates of the reactions were measured and correlated with antitumour activity of these molecules. N-Acetylcysteine addition product 5, resulting from the treatment of butenolide 4 with glutathione precursor, N-acetyl-L-cysteine, was isolated. Unlike purine-containing gamma-(Z)-ethylidene-2,3-dimethoxybutenolides 1a-c, 4, 6, and 7, adduct 5 and butenolides 10-12 did not exhibit inhibitory activity against murine leukemias (L1210 and P388), breast carcinoma (MCF7), and human T-lymphoblasts (Molt4/C8 and CEM/0) cell lines. As such, the biological activity of purine-containing butenolides can be attributed to their adenine moiety as a recognition site as well as their reactivity towards the cysteine residues of functional proteins forming covalent bond via reverse Michael type addition. Adenine-containing phosphonothioanhydride derivative 8 was also synthesised. Its reaction with N-acetyl-L-cysteine produced N,S-diacetylcysteine and thiophosphonate 9. Compound 9 did not exhibit anticancer activity; yet its precursor 8 displayed the most pronounced inhibition on all the examined malignant tumour cell lines. In the presence of L-cysteine, cytotoxicity of 4 and 8 was decreased, whereas glutathione addition more influenced on the cytotoxicity of 8. It was found that adenine-containing phosphonothioanhydride 8 functions as a significant irreversible inactivator of the Escherichia coli ribonucleoside diphosphate reductase. After treatment of MCF7 cells with compound 8, fluorescence microscopy demonstrated the presence of nucleus shrinkage or segmentation. This apoptotic morphology, however, was not pronounced in the presence of glutathione or dithiotheritol.

4-Butyrolactone↗
PubMed1989

An orthogonal ARMA identifier with automatic order estimation for biological modeling.

In this paper an ARMA identification algorithm is developed for modeling biological time series data. The algorithm is based on Gram-Schmidt orthogonalization of automatically selected basis functions from a specified function space. The selection criterion is based on recursive testing of potential benefit to the model of candidate functions. The candidate functions, AR and MA terms, are tested in a pair-wise search direction until a least-squares criterion is satisfied, thereby estimating the order. Additive noise is considered and the basic algorithm extended to improve performance in noise. The algorithm is also extended to systems with inaccessible inputs (signal modeling). Modeling of biological data from speech is included, and indicates good performance. The algorithm is derived from earlier work on nonlinear systems identification.

Algorithms↗
PubMed2005

Reassembly and interfacing neural models registered on biological model databases.

The importance of modeling and simulation of biological process is growing for further understanding of living systems at all scales from molecular to cellular, organic, and individuals. In the field of neuroscience, there are so called platform simulators, the de-facto standard neural simulators. More than a hundred neural models are registered on the model database. These models are executable in corresponding simulation environments. But usability of the registered models is not sufficient. In order to make use of the model, the users have to identify the input, output and internal state variables and parameters of the models. The roles and units of each variable and parameter are not explicitly defined in the model files. These are suggested implicitly in the papers where the simulation results are demonstrated. In this study, we propose a novel method of reassembly and interfacing models registered on biological model database. The method was applied to the neural models registered on one of the typical biological model database, ModelDB. The results are described in detail with the hippocampal pyramidal neuron model. The model is executable in NEURON simulator environment, which demonstrates that somatic EPSP amplitude is independent of synapse location. Input and output parameters and variables were identified successfully, and the results of the simulation were recorded in the organized form with annotations.

Computational Biology↗
PubMed1999

Sensitivity of biological models to errors in parameter estimates.

Since A. M. Turing's paper proposing a mathematical basis for pattern formation in developing organisms many mathematical approaches have been proposed to model biological phenomenon. Continued laboratory study and recent improvements in measurement capabilities have provided an immense quantity of raw gene expression data. The level of data now available demands the development of well-characterized and tested computational tools. Thus, we have examined one mathematical model's sensitivity to errors in estimating its' parameters. Errors in parameter estimation can arise from noise in the laboratory measurements and recasting of laboratory data. We elected to examine the rule-based mathematical model of Mjolsness et al for its' sensitivity to errors in estimated parameters. We have used the technique of sensitivity equations as generally applied in nonlinear systems analysis.

Computational Biology↗
PubMed1981

Algorithmic specification as a technique for computing with informal biological models.

Conceptual biological models can sometimes be usefully expressed in algorithmic form. Models expressed in this way are often capable of capturing more aspects of the complete system than could be captured by other modeling approaches, though in general each aspect is captured in a highly simplified way. Two examples are given. The first involves algorithmic specification of the theory of evolution. The second involves a recently implemented computational model of the brain. Work with such models has, to some extent, the style of experimental work. It often suggests interesting problems or exposes subtle features of the system whose importance has been overlooked.

Biological Evolution↗
PubMed1970

Reactions of alpha methylene lactone tumor inhibitors with model biological nucelophiles.

Thiols are the most reactive nucleophilic reagents among the biological models investigated. They undergo "Michael-type" addition to the polyfunctional sesquiterpene lactones. The rapid rates of reaction with L-cysteine were measured and the reaction products were characterized. Each addition of thiol successively decreased the cytotoxicity of the adducts formed.

Antineoplastic Agents↗
PubMed1994

Mn2+ as a contrast reagent for NMR studies of 35Cl- and 81Br- transport through model biological membranes.

One major problem in using NMR to study halide ions in biological and model biological systems has been to find a contrast reagent to differentiate between halide ions in different compartments. Mn2+ is shown to be a very efficient NMR relaxation agent for the halide ions chloride and bromide and preferable to Co2+ at high magnetic fields. Its use is demonstrated in experiments in which halide ions are exchanged across the membranes of egg yolk phosphatidylcholine vesicles by the phase transfer catalysts tetrabutylammonium ion and benzyltributylammonium ion. Benzyltributylammonium ion is shown to be the more rapid anion transporter through the membrane. Valinomycin is found to cotransport ammonium ions with chloride as an ion pair at a faster rate than the phase transfer catalysts.

Biological Transport↗
PubMed1992

Structured Biological Modelling: a method for the analysis and simulation of biological systems applied to oscillatory intracellular calcium waves.

In biology signal and information processing networks are widely known. Due to their inherent complexity and non-linear dynamics the time evolution of these systems can not be predicted by simple plausibility arguments. Fortunately, the power of modern computers allows the simulation of complex biological models. Therefore the problem becomes reduced to the question of how to develop a consistent mathematical model which comprises the essentials of the real biological system. As an interface between the phenomenological description and a computer simulation of the system the proposed method of Structured Biological Modelling (SBM) uses top-down levelled dataflow diagrams. They serve as a powerful tool for the analysis and the mathematical description of the system in terms of a stochastic formulation. The stochastic treatment, regarding the time evolution of the system as a stochastic process governed by a master equation, circumvents most difficulties arising from high dimensional and non-linear systems. As an application of SBM we develop a stochastic computer model of intracellular oscillatory Ca2+ waves in non-excitable cells. As demonstrated on this example, SBM can be used for the design of computer experiments which under certain conditions can be used as cheap and harmless counterparts to the usual time-consuming biological experiments.

Calcium↗
PubMed2004

The biological model of gastric carcinogenesis.

The biological model of gastric carcinogenesis can be described as a series of sequential phases. The first consists of a chronic active inflammatory response to Helicobacter pylori infection. Infiltration of the gastric mucosa by mucosa-associated lymphoid tissue and polymorphonuclear neutrophils, as well as damage to the epithelial cells, characterize this phase. The second phase is dominated by alterations of the epithelial cell cycle, especially increased rates of apoptosis and cell proliferation. These changes may be responsible for the multifocal atrophy that characterizes the type of gastritis associated with an increased risk of cancer. The third, more advanced phase of the model displays nuclear and architectural abnormalities, which may represent progressive mutational events as expected in classical molecular models of carcinogenesis. The importance of a comprehensive view of the biological model is stressed.

Cell Differentiation↗
PubMed2002

Modelling biological processes using workflow and Petri Net models.

MOTIVATION: Biological processes can be considered at many levels of detail, ranging from atomic mechanism to general processes such as cell division, cell adhesion or cell invasion. The experimental study of protein function and gene regulation typically provides information at many levels. The representation of hierarchical process knowledge in biology is therefore a major challenge for bioinformatics. To represent high-level processes in the context of their component functions, we have developed a graphical knowledge model for biological processes that supports methods for qualitative reasoning. RESULTS: We assessed eleven diverse models that were developed in the fields of software engineering, business, and biology, to evaluate their suitability for representing and simulating biological processes. Based on this assessment, we combined the best aspects of two models: Workflow/Petri Net and a biological concept model. The Workflow model can represent nesting and ordering of processes, the structural components that participate in the processes, and the roles that they play. It also maps to Petri Nets, which allow verification of formal properties and qualitative simulation. The biological concept model, TAMBIS, provides a framework for describing biological entities that can be mapped to the workflow model. We tested our model by representing malaria parasites invading host erythrocytes, and composed queries, in five general classes, to discover relationships among processes and structural components. We used reachability analysis to answer queries about the dynamic aspects of the model. AVAILABILITY: The model is available at http://smi.stanford.edu/projects/helix/pubs/process-model/.

Animals↗
PubMed1986

Track structure in biological models.

High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.

Animals↗
PubMed2025

SBMLtoOdin and Menelmacar: interactive visualisation of systems biology models for expert and non-expert audiences.

SUMMARY: Computational models in biology can increase our understanding of biological systems, be used to answer research questions, and make predictions. Accessibility and reusability of computational models is limited and often restricted to experts in programming and mathematics. This is due to the need to implement entire models and solvers from the mathematical notation models are normally presented as. Here, we present SBMLtoOdin, an R package that translates differential equation models in SBML format from the BioModels database into executable R code using the R package odin, allowing researchers to easily reuse models. We also present Menelmacar, a web-based application that provides interactive visualisations of these models by solving their differential equations in the browser. This platform allows non-experts to simulate and investigate models using an easy-to-use interface. AVAILABILITY AND IMPLEMENTATION: SBMLtoOdin is published under the open source Apache 2.0 licence at https://github.com/bacpop/SBMLtoOdin and can be installed as an R package. The code for the Menelmacar website is published under the MIT License at https://github.com/bacpop/odinviewer, and the website can be found at https://biomodels.bacpop.org/.

Software↗
PubMed1998

Antioxidant efficacy of phytoestrogens in chemical and biological model systems.

Phytoestrogens (PEs) are diphenolic compounds from plants which can bind to estrogen receptors and have estrogen and antiestrogen effects in man and animals. Like other plant phenolics, PEs may have antioxidant properties through hydrogen/electron donation via hydroxyl groups. They might therefore act as free radical scavengers and inhibit development of coronary heart disease and cancers. The hydrogen-donating ability of a range of phytoestrogens was assessed using electron spin resonance spectroscopy, the ferric-reducing ability of plasma assay, and the Trolox equivalent antioxidant capacity. In addition, the ability of compounds to inhibit lipid peroxidation was examined in vitamin E-deficient liver microsomes. Genistein had the highest activity of the isoflavones; however, the isoflavones were relatively poor hydrogen donors compared with the other estrogenic compounds examined. Coumestrol and equol were more effective antioxidants than genistein but had relatively limited activity in comparison with Trolox. The only estrogenic compound with significant antioxidant activity was kaempferol which is better known as a dietary antioxidant than a phytoestrogen. As the concentrations of PEs used in this study exceed the estimated serum concentrations, their relatively poor antioxidant ability in vitro may indicate little significance as antioxidants in vivo.

Animals↗
PubMed2003

Interpreting time-series analyses for continuous-time biological models--measles as a case study.

An increasing number of recent studies involve the fitting of mechanistic models to ecological time-series. In some cases, it is necessary for these models to be discrete-time approximations of continuous-time processes. We test the validity of discretization in the case of measles, where time-series models have recently been developed to estimate ecological parameters directly from data. We find that a non-homogeneous contact function is necessary to capture the host-parasite interaction in a discrete-time model, even in the absence of heterogeneities due to spatial or age structure. We derive a mathematical relationship describing the expected departure from mass-action transmission in terms of the epidemiological parameters in the model, and identify conditions under which the discretization process may fail.

Birth Rate↗