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Results for “In silico modeling”

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At least 145 records · Page 8Linked to original sources

PubMed2005

The P450cam G248E mutant covalently binds its prosthetic heme group.

Previous studies on mammalian peroxidases and cytochrome P450 family 4 enzymes have shown that a carboxylic group positioned close to a methyl group of the prosthetic heme is required for the formation of a covalent link between a protein carboxylic acid side chain and the heme. To determine whether there are additional requirements for covalent bond formation in the P450 enzymes, a glutamic acid or an aspartic acid has been introduced into P450(cam) close to the heme 5-methyl group. Spectroscopic and kinetic studies of the resulting G248E and G248D mutants suggest that the carboxylate group coordinates with the heme iron atom, as reported for a comparable P450(BM3) mutant [Girvan, H. M., Marshall, K. R., Lawson, R. J., Leys, D., Joyce, M. G., Clarkson, J., Smith, W. E., Cheesman, M. R., and Munro, A. W. (2004) J. Biol. Chem. 279, 23274-23286]. The two P450(cam) mutants have low catalytic activity, but in contrast to the P450(BM3) mutant, incubation of the G248E (but not G248D) mutant with camphor, putidaredoxin, putidaredoxin reductase, and NADH results in partial covalent binding of the heme to the protein. No covalent attachment is observed in the absence of camphor or any of the other reaction components. Pronase digestion of the G248E P450(cam) mutant after covalent attachment of the heme releases 5-hydroxyheme, establishing that the heme is covalently attached through its 5-methyl group as predicted by in silico modeling. The results establish that a properly positioned carboxyl group is the sole requirement for autocatalytic formation of a heme-protein link in P450 enzymes, but also show that efficient covalent binding requires placement of the carboxyl close to the methyl but in a manner that prevents strong coordination to the iron atom.

Amino Acid Sequence↗

PubMed2004

Cell-surface-associated tissue transglutaminase is a target of MMP-2 proteolysis.

MT1-MMP, a prototypic member of a membrane-type metalloproteinase subfamily, is an invasion promoting protease and an activator of MMP-2. In addition, MT1-MMP proteolysis regulates the functionality of cell-surface adhesion/signaling receptors including tissue transglutaminase (tTG). tTG is known to serve as an adhesion coreceptor for beta1/beta3 integrins and as an enzyme that catalyzes the cross-linking of proteins and the conjugation of polyamines to proteins. Here, we report that MMP-2, functioning in concert with MT1-MMP, hydrolyzes cell-surface-associated tTG, thereby further promoting the effect initiated by the activator of MMP-2. tTG, in return, preferentially associates with the activation intermediate of MMP-2. This event decreases the rate of MMP-2 maturation and protects tTG against proteolysis by MMP-2. Our cell culture, in vitro experiments, and in silico modeling indicate that the catalytic domain of MMP-2 directly associates with the core enzymatic domain II of tTG (the K(d) = 380 nM). The follow-up cleavage of the domain II eliminates both the receptor and the enzymatic activity of tTG. Our data illuminate the coordinated interplay involving the MT1-MMP/MMP-2 protease tandem in the regulation of the cell receptors and explain the underlying biochemical mechanisms of the extensive tTG proteolysis that exists at the normal tissue/tumor boundary. Our findings also suggest that neoplasms, which express functionally active MT1-MMP and, therefore, activate soluble MMP-2, can contribute to the degradation of tTG expressed in neighboring host cells. The loss of adhesive and enzymatic activities of tTG at the interface between tumor and normal tissue will decrease cell-matrix interactions and inhibit matrix cross-linking, causing multiple pathological alterations in host cell adhesion and locomotion.

Catalytic Domain↗

PubMed2005

Investigation of the environment surrounding iron-sulfur cluster 4 of Escherichia coli dimethylsulfoxide reductase.

Iron-sulfur ([Fe-S]) clusters are common in electron transfer proteins, and their midpoint potentials (E(m) values) play a major role in defining the rate at which electrons are shuttled. The E(m) values of [Fe-S] clusters are largely dependent on the protein environment as well as solvent accessibility. The electron transfer subunit (DmsB) of Escherichia coli dimethylsulfoxide reductase contains four [4Fe-4S] clusters (FS1-FS4) with E(m) values between -50 and -330 mV. We have constructed an in silico model of DmsB and addressed the roles of a group of residues surrounding FS4 in electron transfer, menaquinol (MQH(2)) binding, and protein control of its E(m). Residues Pro80, Ser81, Cys102, and Tyr104 of DmsB are located at the DmsB-DmsC interface and are critical for the binding of the MQH(2) inhibitor analogue 2-n-heptyl-4-hydroxyquinoline N-oxide (HOQNO) and the transfer of electrons from MQH(2) to FS4. Because the EPR spectrum of FS4 is complicated by spectral overlap and spin-spin interactions with the other [4Fe-4S] clusters of DmsB, we evaluated mutant effects on FS4 in double mutants (with a DmsB-C102S mutation) in which FS4 is assembled as a [3Fe-4S] cluster (FS4([3Fe)(-)(4S])). The DmsB-C102S/Y104D and DmsB-C102S/Y104E mutants dramatically lower the E(m) of FS4([3Fe)(-)(4S]) from 275 to 150 mV and from 275 to 145 mV, respectively. Mutations of positively charged residues around FS4([3Fe)(-)(4S]) lower its E(m), but mutations of negatively charged residues have negligible effects. The E(m) of FS4([3Fe)(-)(4S]) in the DmsB-C102S mutant is insensitive to HOQNO as well as to changes in pH from 5 to 7. The FS4([3Fe)(-)(4S]) E(m) of the DmsB-C102S/Y104D mutant increases in the presence of HOQNO and decreasing pH. Analyses of the mutants suggest that the maximum achievable E(m) for FS4([3Fe)(-)(4S]) of DmsB is approximately 275 mV.

Amino Acid Sequence↗

PubMedDate not supplied

Use of robust classification techniques for the prediction of human cytochrome P450 2D6 inhibition.

A new in silico model is developed to predict cytochrome P450 2D6 inhibition from 2D chemical structure. Using a diverse training set of 100 compounds with published inhibition constants, an ensemble approach to recursive partitioning is applied to create a large number of classification trees, each of which yields a yes/no prediction about inhibition for a given compound. These binary classifications are combined to provide an overall prediction, which answers the yes/no question about inhibition and provides a measure of confidence about that prediction. Compared to single-tree models, the ensemble approach is less sensitive to noise in the experimental data as well as to changes in the training set. Internal validation tests indicated an overall classification accuracy of 75%, whereas predictions applied to an external set of 51 compounds yielded 80% accuracy, with all inhibitors correctly identified. The speed and 2D nature of this model make it appropriate for high-throughput processing of large chemical libraries, and the confidence level provides a continuous scale on which to prioritize compounds.

Computer-Aided Design↗

PubMedDate not supplied

Prediction of chemical carcinogenicity from molecular structure.

Carcinogens represent a serious threat to human health. In vivo determination of carcinogenicity is time-consuming and expensive, thus in silico models to predict chemical carcinogenicity are highly desirable for virtual screening of compound libraries of both pharmaceutically and other commercially interesting molecules. In the present study, a PLS-DA (partial least squares discriminant analysis) model was developed to predict carcinogenicities in each of four rodent models: male mouse (MM), female mouse (FM), male rat (MR), and female rat (FR). The data set that was used contained over 520 compounds from both the NTP and the FDA databases. All the models were built from the same molecular descriptor system, which is based on atom typing [Sun, H. J. Chem. Inf. Comput. Sci. 2004, 44, 748-757], enabling the comparison of atomic contributions to carcinogenicity with respect to species and gender. Using four components, the models were able to achieve excellent fitting and prediction, with r(2) = 0.987 and q(2) = 0.944 for MM, r(2) = 0.985 and q(2) = 0.950 for FM, r(2) = 0.989 and q(2) = 0.962 for MR, and r(2) = 0.990 and q(2) = 0.965 for FR. The models were further validated by response permutation testing and external validation, and the results indicated that the models were both statistically significant and predictive. Variable influence on projection (VIP) analysis identified the key atom types and fragments that contributed to carcinogenicities and response differences across species and gender.

Animals↗

PubMed2005

Predicting human serum albumin affinity of interleukin-8 (CXCL8) inhibitors by 3D-QSPR approach.

A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure-property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K(i)) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.

Anti-Inflammatory Agents, Non-Steroidal↗

PubMed2005

Quantitative structure-activity relationship analysis of inhibitors of the nicotine metabolizing CYP2A6 enzyme.

The purpose of this study was to develop screening and in silico modeling methods to obtain accurate information on the active center of CYP2A6, a nicotine oxidizing enzyme. The inhibitory potencies of 26 naphthalene and 16 non-naphthalene derivatives were determined for human CYP2A6 and mouse CYP2A5 enzymes. Several comparative molecular field analysis (CoMFA) models were developed to find out what types of steric and electrostatic properties are required for potent inhibitors. The IC(50) values of the tested compounds varied from 0.55 to 35 400 microM for CYP2A6 and from 1 to 1500 microM for CYP2A5. The generated CoMFA models were able to accurately predict the inhibition potencies of an external test set of chemicals. Potent and specific inhibitors of the CYP2A6 enzyme can be used in the future to increase nicotine bioavailability and thus make oral nicotine administration feasible in smoking cessation therapy.

Animals↗

PubMed2004

Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method.

This study aimed to evaluate in silico models based on quantum chemical (QC) descriptors derived using the electronegativity equalization method (EEM) and to assess the use of QC properties to predict chemical metabolism by human UDP-glucuronosyltransferase (UGT) isoforms. Various EEM-derived QC molecular descriptors were calculated for known UGT substrates and nonsubstrates. Classification models were developed using support vector machine and partial least squares discriminant analysis. In general, the most predictive models were generated with the support vector machine. Combining QC and 2D descriptors (from previous work) using a consensus approach resulted in a statistically significant improvement in predictivity (to 84%) over both the QC and 2D models and the other methods of combining the descriptors. EEM-derived QC descriptors were shown to be both highly predictive and computationally efficient. It is likely that EEM-derived QC properties will be generally useful for predicting ADMET and physicochemical properties during drug discovery.

Electricity↗

PubMed2006

Presentation of a structurally diverse and commercially available drug data set for correlation and benchmarking studies.

A multivariate analysis of drugs on the Swedish market was the basis for the selection of a small, physicochemically diverse set of 24 drug compounds. Factors such as structural diversity, commercial availability, price, and a suitable analytical technique for quantification were considered in the selection. Lipophilicity, pKa, solubility, and permeability across human Caco-2 cell monolayers were measured for the compiled data set. The results show that, by use of a physicochemically diverse data set, experimental responses over a wide range were obtained. The paper also shows how experimental difficulties due to the diversity of the data set can be overcome. We anticipate that this data set can serve as a benchmark set for validation of new experimental techniques or in silico models. It can also be used as a diverse starting data set for the development of new computational models.

Caco-2 Cells↗

PubMed2005

Synthesis of the H-cluster framework of iron-only hydrogenase.

The metal-sulphur active sites of hydrogenases catalyse hydrogen evolution or uptake at rapid rates. Understanding the structure and function of these active sites--through mechanistic studies of hydrogenases, synthetic assemblies and in silico models--will help guide the design of new materials for hydrogen production or uptake. Here we report the assembly of the iron-sulphur framework of the active site of iron-only hydrogenase (the H-cluster), and show that it functions as an electrocatalyst for proton reduction. Through linking of a di-iron subsite to a {4Fe4S} cluster, we achieve the first synthesis of a metallosulphur cluster core involved in small-molecule catalysis. In addition to advancing our understanding of the natural biological system, the availability of an active, free-standing analogue of the H-cluster may enable us to develop useful electrocatalytic materials for application in, for example, reversible hydrogen fuel cells. (Platinum is currently the preferred electrocatalyst for such applications, but is expensive, limited in availability and, in the long term, unsustainable.).

Binding Sites↗

PubMed2003

Chemistry and the hydrogenases.

The reversible reduction protons to dihydrogen: 2H+ + 2e [symbol: see text] H2 is deceptively the simplest of reactions but one that requires multistep catalysis to proceed at practical rates. How the metal-sulfur clusters of the hydrogenases catalyse this interconversion is currently the subject of extensive structural, spectroscopic and mechanistic studies of the enzymes, of synthetic assemblies and of in silico models. This is driven both by curiosity and by the view that an understanding of the underlying chemistry may inform the design of new electrocatalytic systems for hydrogen production or uptake, pertinent to energy transduction technology in an 'Hydrogen Economy'. Can chemists design materials that replace the expensive platinum metal catalysts of fuel cells with metal-sulfur cluster assemblies utilising abundant Ni, Fe and S as in the natural systems? Here we review the state of the art.

Bacteria↗

PubMed2001

The S-methylmethionine cycle in angiosperms: ubiquity, antiquity and activity.

Angiosperms synthesize S-methylmethionine (SMM) from methionine (Met) and S-adenosylmethionine (AdoMet) in a unique reaction catalyzed by Met S-methyltransferase (MMT). SMM serves as methyl donor for Met synthesis from homocysteine, catalyzed by homocysteine S-methyltransferase (HMT). MMT and HMT together have been proposed to constitute a futile SMM cycle that stops the free Met pool from being depleted by an overshoot in AdoMet synthesis. Arabidopsis and maize have one MMT gene, and at least three HMT genes that belong to two anciently diverged classes and encode enzymes with distinct properties and expression patterns. SMM, and presumably its cycle, must therefore have originated before dicot and monocot lineages separated. Arabidopsis leaves, roots and developing seeds all express MMT and HMTs, and can metabolize [35S]Met to [35S]SMM and vice versa. The SMM cycle therefore operates throughout the plant. This appears to be a general feature of angiosperms, as digital gene expression profiles show that MMT and HMT are co-expressed in leaves, roots and reproductive tissues of maize and other species. An in silico model of the SMM cycle in mature Arabidopsis leaves was developed from radiotracer kinetic measurements and pool size data. This model indicates that the SMM cycle consumes half the AdoMet produced, and suggests that the cycle serves to stop accumulation of AdoMet, rather than to prevent depletion of free Met. Because plants lack the negative feedback loops that regulate AdoMet pool size in other eukaryotes, the SMM cycle may be the main mechanism whereby plants achieve short-term control of AdoMet level.

Arabidopsis↗

PubMed2002

Evolution of drug metabolism: hitchhiking the technology bandwagon.

1. The application of a range of established and emerging technologies and experimental approaches has allowed investigation of cytochrome P450 (CYP) and uridine diphosphate-glucuronosyltransferase (UGT) at the functional, structural and molecular levels to address questions of therapeutic relevance, particularly the wide interindividual variability in metabolic clearance characteristic of drugs and chemicals metabolized by these enzymes. 2. Studies in vivo initially identified the various factors that contribute to interindividual variability. Subsequently, human liver microsomal kinetic approaches, together with the cloning and functional characterization of recombinant CYP and UGT isoforms, led to the development of in vitro strategies that allowed the qualitative prediction of those factors likely to alter the metabolic clearance of a given compound in vivo. More recently, computer (in silico) modelling has been used to complement the laboratory based procedures. 3. The application of molecular biological approaches additionally allowed identification of the mutations responsible for CYP and UGT genetic polymorphism and, in some instances, the domains and individual amino acids that confer isoform substrate and inhibitor selectivities. Homology models, developed using X-ray crystallographic data as the template, potentially enable prediction of the functional consequences of altered CYP structure. 4. The rapid advances occurring in genomics, proteomics, gene expression analysis and computer modelling will allow further unravelling of the complexities of drug metabolism and improved prospects for the individualization of drug therapy.

Animals↗

PubMed2005

The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states.

A principal aim of systems biology is to develop in silico models of whole cells or cellular processes that explain and predict observable cellular phenotypes. Here, we use a model of a genome-scale reconstruction of the integrated metabolic and transcriptional regulatory networks for Escherichia coli, composed of 1,010 gene products, to assess the properties of all functional states computed in 15,580 different growth environments. The set of all functional states of the integrated network exhibits a discernable structure that can be visualized in 3-dimensional space, showing that the transcriptional regulatory network governing metabolism in E. coli responds primarily to the available electron acceptor and the presence of glucose as the carbon source. This result is consistent with recently published experimental data. The observation that a complex network composed of 1,010 genes is organized to achieve few dominant modes demonstrates the utility of the systems approach for consolidating large amounts of genome-scale molecular information about a genome and its regulation to elucidate an organism's preferred environments and functional capabilities.

Bacterial Proteins↗

PubMed2001

Conversion of monomeric protein L to an obligate dimer by computational protein design.

Protein L consists of a single alpha-helix packed on a four-stranded beta-sheet formed by two symmetrically opposed beta-hairpins. We use a computer-based protein design procedure to stabilize a domain-swapped dimer of protein L in which the second beta-turn straightens and the C-terminal strand inserts into the beta-sheet of the partner. The designed obligate dimer contains three mutations (A52V, N53P, and G55A) and has a dissociation constant of approximately 700 pM, which is comparable to the dissociation constant of many naturally occurring protein dimers. The structure of the dimer has been determined by x-ray crystallography and is close to the in silico model.

Bacterial Proteins↗

PubMed2004

Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data.

Diverse datasets including genomic, proteomic, isotopomer, and DNA sequence variation are becoming available for human mitochondria. Thus there is a need to integrate these data within an in silico modeling framework where mitochondrial biology and related disorders can be studied and analyzed. This paper reports a reconstruction and characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. The 189 reactions included in this reconstruction are both elementally and charge-balanced and are assigned to their respective cellular compartments (mitochondrial, cytosol, or extracellular). The capabilities of the reconstructed network to fulfill three metabolic functions (ATP production, heme synthesis, and mixed phospholipid synthesis) were determined. Network-based analysis of the mitochondrial energy conversion process showed that the overall ATP yield per glucose is 31.5. Network flexibility, characterized by allowable variation in reaction fluxes, was evaluated using flux variability analysis and analysis of all of the possible optimal flux distributions. Results showed that the network has high flexibility for the biosynthesis of heme and phospholipids but modest flexibility for maximal ATP production. A subset of all of the optimal network flux distributions, computed with respect to the three metabolic functions individually, was found to be highly correlated, suggesting that this set may contain physiological meaningful fluxes. Examinations of optimal flux distributions also identified correlated reaction sets that form functional modules in the network.

Amino Acids↗

PubMed2004

Non-proteolytic, receptor/ligand interactions associate cellular membrane type-1 matrix metalloproteinase with the complement component C1q.

Membrane type-1 matrix metalloproteinase (MT1-MMP), a prototypic member of the membrane-tethered MMP family, is an essential component of a cellular proteolysis apparatus. Recognition of protein cleavage targets followed by proteolysis is a main function of MT1-MMP. For the first time, however, we present evidence that MT1-MMP and other structurally related membrane MMPs bind C1q, the recognition unit of the first component of complement C1 that initiates activation of the classical pathway of complement. These interactions involve the catalytic domain of MT1-MMP and the C1q globular domain. In silico modeling followed by mutagenesis and the in vitro and cell-based binding studies showed that the His(171)-Glu-Lys-Gln-Ala-Asp(176) and Val(223)-Arg-Asn(224) peptide sequences of MT1-MMP are directly involved in the binding with C1q. These sequence regions are spatially distant from the active site of the protease. As a result, the catalytically active and the catalytically latent forms of cellular MT1-MMP are both efficient in binding with C1q. In agreement, despite the MT1-MMP/C1q interactions, C1q is totally resistant to MT1-MMP proteolysis. The discovery of the unconventional, receptor/ligand-like interactions of MT1-MMP with C1q, an essential component of immunity, is a significant step toward a more complete understanding of the role of this membrane-tethered protease in cancer.

Amino Acid Sequence↗

PubMed2005

Complex formation between glutamyl-tRNA reductase and glutamate-1-semialdehyde 2,1-aminomutase in Escherichia coli during the initial reactions of porphyrin biosynthesis.

In Escherichia coli the first common precursor of all tetrapyrroles, 5-aminolevulinic acid, is synthesized from glutamyl-tRNA (Glu-tRNA(Glu)) in a two-step reaction catalyzed by glutamyl-tRNA reductase (GluTR) and glutamate-1-semialdehyde 2,1-aminomutase (GSA-AM). To protect the highly reactive reaction intermediate glutamate-1-semialdehyde (GSA), a tight complex between these two enzymes was proposed based on their solved crystal structures. The existence of this hypothetical complex was verified by two independent biochemical techniques. Co-immunoprecipitation experiments using antibodies directed against E. coli GluTR and GSA-AM demonstrated the physical interaction of both enzymes in E. coli cell-free extracts and between the recombinant purified enzymes. Additionally, the formation of a GluTR.GSA-AM complex was identified by gel permeation chromatography. Complex formation was found independent of Glu-tRNA(Glu) and cofactors. The analysis of a GluTR mutant truncated in the 80-amino acid C-terminal dimerization domain (GluTR-A338Stop) revealed the importance of GluTR dimerization for complex formation. The in silico model of the E. coli GluTR.GSA-AM complex suggested direct metabolic channeling between both enzymes to protect the reactive aldehyde species GSA. In accordance with this proposal, side product formation catalyzed by GluTR was observed via high performance liquid chromatography analysis in the absence of the GluTR.GSA-AM complex.

Aldehyde Oxidoreductases↗