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1 An efficient steroid pharmacophore-based strategy to identify new aromatase inhibitors

1 An efficient steroid pharmacophore-based strategy to identify new aromatase inhibitors
1 An efficient steroid pharmacophore-based strategy to identify new aromatase inhibitors

Original article

An ef?cient steroid pharmacophore-based strategy to identify new aromatase inhibitors

Marco A.C.Neves a ,Teresa C.P.Dinis b ,Giorgio Colombo c ,*,M.Luisa Sa

′e Melo a ,**a

Centro de Estudos Farmace

?uticos,Lab.Qu?′mica Farmace ?utica,Faculdade de Farma ′cia,Universidade de Coimbra,3000-548Coimbra,Portugal b

Centro de Neurocie

?ncias,Lab.Bioqu?′mica,Faculdade de Farma ′cia,Universidade de Coimbra,3000-548Coimbra,Portugal c

Istituto di Chimica del Riconoscimento Molecolare,CNR,20131Milano,Italy

a r t i c l e i n f o

Article history:

Received 20November 2008Accepted 7May 2009

Available online 19May 2009Keywords:

Pharmacophore modeling Virtual screening Aromatase inhibitors Breast cancer

a b s t r a c t

Aromatase,an enzyme involved in the conversion of androgens into estrogens,is an important target for the endocrine treatment of breast cancer.Aromatase inhibition is usually achieved with steroids struc-turally related to the substrate of catalysis or,alternatively,with azole non-steroid compounds.Substituted androstenedione derivatives with D 1,D 6and D 1,6unsaturations and 6-alkyl/6-phenyl aliphatic substitutions,are among the most potent steroid aromatase inhibitors known to date.In this paper we have combined the common pharmacophoric and shape features of these molecules into a new pharmacophore model,useful for virtual screening of large compound databases.Small subsets of the best ?tting anti-aromatase candidates were extracted from the NCI database and experimentally tested on an in vitro assay with human placental aromatase.New potent aromatase inhibitors were identi?ed such as compounds 8and 14.Considering the lack of a crystal structure for the aromatase enzyme,this ligand-based method is a valuable tool for the virtual screening of new aromatase inhibitors.

ó2009Elsevier Masson SAS.All rights reserved.

1.Introduction

Estrogen deprivation is an effective approach for the endocrine treatment of hormone sensitive breast cancer in postmenopausal women.Aromatase,the enzyme responsible for the conversion of androgens into estrogens,is therefore an important pharmacolog-ical target [1].The aromatization reaction is a three-step trans-formation involving two hydroxylations at the 19-methyl group of androstenedione and testosterone,and a ?nal oxidative decar-bonylation.Each reaction consumes a single mole of molecular oxygen and NADPH [2].

Since androstenedione is the preferred substrate for the enzyme [3],the initial development of aromatase inhibitors was focused on this basic scaffold,substituted at several positions.Most of these molecules are competitive inhibitors and bind to the same active

site cavity as the natural substrate [4].Formestane and exemestane,second and third generation aromatase inhibitors,are successful examples of steroid aromatase inhibitors developed with this approach.Indeed,both compounds have been approved for clinical use [5,6].Other examples of potent inhibitors include androstene-dione derivatives with D 1,D 6and D 1,6unsaturations and 6-n -alkyl or 6-n -phenyl aliphatic substitutions [7–10].These compounds high-lighted the presence of a hydrophobic pocket close to the C6posi-tion of the steroid nucleus.The length and shape of this substitution were found to be critically important to the activity [11].

Besides competitive aromatase binding,several steroid aroma-tase inhibitors are converted by the enzyme into reactive inter-mediates,which are able to cause time-dependent inactivation.These compounds are known as mechanism-based inactivators.The activation step is triggered during a normal catalytic process and depends on the presence of NADPH.Typically,a reactive electrophilic intermediate is formed and immediately reacts with a nucleophilic residue within the active site [12].

Although a crystallographic 3D structure of the aromatase enzyme is still not available,several X-ray structures of homologous mammalian and human cytochrome P450enzymes [13–16]have been used as templates to build homology models [17–19].Key atomic details that ultimately determine molecular interactions were identi?ed in structure-based studies and used in the rational design of new aromatase inhibitors [20–22].Despite clear advances in the

Abbreviations:AG,aminoglutethimide;ESP,electrostatic surface potential;HBA,hydrogen bond acceptor;HOMO,highest occupied molecular orbital;HYD,hydrophobic group;LUMO,lowest unoccupied molecular orbital;NCI,National Cancer Institute;PSA,polar surface area;RMSD,root mean square deviation;VS,virtual screening.

*Corresponding author.Tel.:t390228500031;fax:t390228901239.**Corresponding author.Tel.:t351239488475;fax:t351239488471.

E-mail addresses:g.colombo@https://www.sodocs.net/doc/7c7095843.html,r.it (G.Colombo),samelo@ci.uc.pt

(M.L.Sa

′e

Melo).Contents lists available at ScienceDirect

European Journal of Medicinal Chemistry

journal hom epage:https://www.sodocs.net/doc/7c7095843.html, /locate

/ejmech

0223-5234/$–see front matter ó2009Elsevier Masson SAS.All rights reserved.

doi:10.1016/j.ejmech.2009.05.003

European Journal of Medicinal Chemistry 44(2009)4121–4127

overall quality of aromatase homology models,their usefulness in ligand–protein high throughput docking experiments of large compound databases remains to be demonstrated.On the other hand,ligand-based pharmacophore models such as 3D-QSAR CoMFA developed for several classes of aromatase inhibitors,led to the design of very potent molecules [23–26],and a recent study by Langer and coworkers highlighted the value of pharmacophore models in virtual screening of large electronic compound databases,using a model derived from potent non-steroid aromatase inhibitors [27].

In this work,we have summarized information about C6-substituted androstenedione derivatives,potent steroid aromatase

2.Results and discussion 2.1.Pharmacophore modeling

Androstenedione derivatives are among the most potent steroid aromatase inhibitors found to date.In particular,it has been postulated that n -alkyl and n -phenyl aliphatic groups linked at position C6increase the anti-aromatase activity due to the pres-ence of a hydrophobic cavity at the enzyme binding site.In this sense,we have used a training set of potent C6-substituted androstenedione derivatives reported in the literature [7–10](Fig.1A),namely,6b -ethylandrosta-1,4-diene-3,17-dione (1),6-ethylandrosta-1,4,6-triene-3,17-dione (2),6-n -propylandrosta-1,4,6-triene-3,17-dione (3),6-benzylandrosta-4,6-diene-3,17-dione (4),6a -phenethylandrost-4-ene-3,17-dione (5)and 6-phenethy-landrosta-1,4,6-triene-3,17-dione (6),to derive a common-features pharmacophore model using the HipHop [28]algorithm of the Catalyst software [29].Brie?y,the program identi?es chemical features common to a training set of active compounds and generates hypotheses for their activity.These hypotheses are spatial dispositions of pharmacophoric points providing the compounds’relative alignment in the binding site of the enzyme.

Each point accounts for an important chemical feature,such as hydrogen bond donors/acceptors,hydrophobic groups,negative/positive ionizable groups and aromatics.Due to the basic structures of the compounds used,hydrogen bond acceptors (HBA)and hydrophobic groups (HYD)were selected for the common-features alignment procedure.Besides its strong potency,this training set of molecules was chosen in order to account for the effect of different lengths,shapes and volumes of the hydrophobic moiety at C6,as well as its stereochemistry in relation to the steroid framework.Ten different pharmacophore hypotheses were automatically had only two acceptors and two hydrophobic groups.Visual inspection of the training set molecules aligned to the top ranked solution,STR-HYP (Fig.1B),revealed that the two hydrogen bond acceptors matched the 3-oxo (HBA1)and the 17-oxo (HBA2)groups.One of the hydrophobic groups,HYD1,superimposes the 19-methyl and the A–B ring junction,HYD2matches ring C and the 18-methyl,and the third apolar feature,HYD3,is related to the hydrophobic moiety linked at C6.Due to the rigid nature of the steroid scaffold,most of the common-features solutions were very similar to the top ranked pharmacophore model,with slight differences in the projection vectors of HBA1and HBA2(the loca-tion of hypothetical hydrogen bond donors)and the positioning of HYD3.The top ranked solution was therefore selected for the following steps.

Fig.1.A)Training set of C6-substituted steroid aromatase inhibitors used for the common-features pharmacophore model generation [7–10].B)Common-features pharmacophore model of C6-substituted steroid aromatase inhibitors.The STR-HYP pharmacophoric query had ?ve features:two hydrogen bond acceptors (HBA1and HBA2,green)and three hydrophobic groups (HYD1,HYD2and HYD3,cyan).The training set inhibitors (1,cyan,2,brown,3,yellow,4,blue,5,green,6,purple)are represented at the best ?t alignment to the model.(For interpretation of the references to colour in ?gure legends,the reader is refered to the web version of this article).

Table 1

Compound 5was converted into a shape query and combined with the initial hypothesis.The minimum similarity tolerance was set to 0.5.b

Filters applied:Lipinski Rule of Five,rotatable bonds 8,PSA <150.

M.A.C.Neves et al./European Journal of Medicinal Chemistry 44(2009)4121–4127

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Cytochrome P450enzymes have an inner binding cavity accessible from the outside through one or more ligand channels [31].Therefore,in order to bind to the active site,aromatase inhibitors must have appropriate shape and volume.A set of inclusion volumes based on the shape of compound 5were applied to STR-HYP,and the steric tolerance was adjusted to allow good shape complementarity with the training set molecules.A new pharmacophore model combining pharmacophoric and shape features was obtained (STR-HYP tShape).2.2.Virtual screening

The NCI open chemical repository collection is a large library of synthetic and natural compounds,with more than 260000different structures [32].This library has been used to screen,both in vitro and in vivo,for new anti-cancer and anti-viral agents,with the goal of identifying and evaluating novel chemical leads and their underlying biological mechanisms of action.The electronic version of the NCI repository (NCI database)was downloaded from the ZINC website [33]and converted into a multiconformer data-base using the catDB utility program of the Catalyst software [29].

An initial virtual screening (VS)run with the STR-HYP pharma-cophore model identi?ed 16212hits (5.6%of the database,Table 1),and the modi?ed pharmacophore hypothesis,STR-HYP tShape,yielded 2189hits (0.8%of total number of compounds,Table 1).Most of the molecules excluded,based on shape features,are

expected to be false positives due to the presence of protruding groups that might clash with aromatase binding site residues.

Furthermore,in order to increase the ‘‘drug-likeness’’of the new anti-aromatase candidates,several ?lters were applied,namely a Lipinski Rule of Five ?lter [34],and ?lters based on the maximum number of rotatable bonds (not more than 8)and polar surface area (PSA <150).This procedure reduced the number of compounds to 1462(0.5%of the database,Table 1).The molecules were then superimposed with the pharmacophore model and visually inspec-ted,19of them being selected based on a good root mean square deviation (RMSD)?t to the model.Of these,10were available from the NCI database (Fig.2)and were obtained for experimental evaluation.

Before performing the biochemical evaluation,the hits were inspected on a large electronic collection of organic chemistry (CrossFire Beilstein)using the MDL CrossFire Commander [35].Additional searches were performed using the PubChem Compound database [36],a publicly available resource with chemical and biological information of small molecules,including results from NCI anti-cancer drug screenings.It was found that none of them had been previously tested experimentally as aro-matase inhibitor.

2.3.

Biochemical evaluation

The compounds selected using our ligand-based VS strategy were biochemically evaluated for the ability to inhibit the enzyme aromatase.The molecules were initially screened at 10m M and 100m M concentrations,followed by a full concentration–response study,allowing the determination of the half-maximal inhibitory concentration (IC 50)reported in Table 2.Formestane and amino-glutethimide (AG),second and ?rst generation aromatase inhibi-tors,were also tested,in the same assay conditions,as reference compounds.

Fig.2.NCI database hits selected based on the STR-HYP tShape pharmacophore model.

Table 2

Aromatase inhibition activity of NCI hits selected based on the STR-HYP tShape pharmacophore model.Aminoglutethimide and formestane were tested as refer-Results are shown as the mean ?SEM of three independent experiments.b Inhibition at 30m M.

c

Inhibition was not observed at concentrations 100m M.

Table 3

Enzyme kinetic parameters for compounds 8and 14,and type of aromatase inhi-Apparent inhibition constants (K i )were calculated by a nonlinear regression analysis using the Michaelis–Menten equation,and the type of inhibition was determined by a Lineweaver–Burk plot.b

K I and k inact were obtained by a Kitz–Wilson plot.c

Inactivation was not observed at concentrations 2m M.

M.A.C.Neves et al./European Journal of Medicinal Chemistry 44(2009)4121–41274123

Most of the compounds selected showed anti-aromatase activity in the assay conditions used(Table2).Compounds7,13,15and16 are weak aromatase inhibitors with IC50higher than100m M. Compounds9(IC50?9.8m M)and10(IC50?15.5m M),have anti-aromatase potencies comparable to the?rst generation aromatase inhibitor tested,aminoglutethimide(IC50?10.0m M),and,more interestingly,compounds8and14have an IC50in the nanomolar https://www.sodocs.net/doc/7c7095843.html,pound8(IC50?0.274m M)is36times more active than aminoglutethimide,and compound14(IC50?0.678m M)15times more potent than AG.However,these two molecules are less active than formestane(IC50?0.092m M),the second generation aroma-tase inhibitor tested.

Kinetic analysis of the enzyme activity was also performed.The kinetic constants,Michaelis–Menten constant(K m?0.094m M)and maximum velocity of catalysis(V max?163.7pmol of sub-strate minà1mgà1of protein)were calculated under initial velocity conditions.The type of inhibition was characterized using a Line-weaver–Burk plot.As expected,the most potent aromatase inhib-itors(compounds8,K i?0.266m M,and14,K i?0.385m M), inhibited the enzyme in a competitive manner(Table3).

Compounds8and14were further tested for their ability to cause time-dependent inactivation of https://www.sodocs.net/doc/7c7095843.html,pound14, but not compound8,was able to inactivate the enzyme in the presence of NADPH,with a pseudo?rst order kinetics during the?rst12min of incubation(Fig.3).Kitz–Wilson analysis[37]of the results obtained,gave a k inact of0.608minà1and K I of21.4m M. Since the K i observed from the competition kinetics is lower than the K I obtained from the inactivation experiments,this suggests that the covalent binding of the inhibitor to the active site of the enzyme is the rate-limiting step of the inactivation.On the other hand,addition of substrate androstenedione in excess prevented inactivation(Fig.4A),as well as not including NADPH in the medium(Fig.4B).This suggests that the inhibitor acts at or near the active site of aromatase,and,since NADPH was essential for the time-dependent aromatase activity loss by compound14,that the inhibitor transformation into a reactive intermediate depends on enzyme catalysis.Furthermore,the nucleophilic trapping agent L-cysteine did not prevent enzyme inactivation to a signi?cant extent (Fig.4C),suggesting a covalent bond formation at the active site, between aromatase and the reactive electrophilic intermediate, therefore preventing diffusion of the activated inhibitor to the surrounding media.

2.4.Stereoelectronic characterization

The strong anti-aromatase activity of compound8,a B-nor steroid with similar hydrophobic core compared to the substrate androstenedione,prompted us to further evaluate the molecular geometry and electronic properties of these structures using

high Fig.4.Effect of androstenedione(A),NADPH(B)and L-cysteine(C)on the time-dependent inactivation of human placental aromatase by compound14.A)7.5m M of androste-nedione was incubated with(-)or without(:)7.5m M of inhibitor.Incubations of7.5m M of inhibitor without androstenedione(;)were also performed.B)7.5m M of inhibitor was incubated with(:)or without(-)NADPH.C)0.5mM of L-cysteine was incubated with(-)or without(:)7.5m M of inhibitor.Incubations of7.5m M of inhibitor without L-cysteine (;)were also performed.Each point represents the mean of three independent assays and the vertical bars,the standard error of the

mean.

Fig.3.Time-and concentration-dependent inactivation of human placental aromatase

by compound14in the presence of NADPH.The concentrations of inhibitor used were

0m M(-),2.5m M(:),5m M(;)and7.5m M(A).A Kitz–Wilson plot of the same data

is shown in the inset.Each point represents the mean of three independent assays and

the vertical bars,the standard error of the mean(SEM).

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level ab initio quantum chemistry methods.It was found that the geometries of androstenedione and its B-nor derivative are very superimposable,with an RMSD of 0.31?based on pairwise align-ment of the A,C and D ring carbons (Fig.5A).Furthermore,the distances between the hydrogen bond acceptor groups,an impor-tant pharmacophoric feature in our model,are very similar (10.44?in androstenedione and 10.38?in the B-nor derivative).Slight differences were however identi?ed,namely the shape and size of the B ring,and the location of the acceptor linked to the ring A.The B ring of the nor-steroid,a cyclopentane,adopts an envelope conformation which is less bulky than the cyclohexane chair in androstenedione.The 3-oxo groups are located 0.63?apart based on our superimposition.

Electronic properties of the molecules were also calculated,namely the electrostatic surface potential (ESP)and the valence orbitals,i.e.the highest occupied molecular orbital (HOMO)and the lowest unoccupied molecular orbital (LUMO).These properties are similar in both compounds (Fig.5B).Negative potential was found in both carbonyls and along the O ]C3–C4]C5conjugation due to p electron delocalization.The HOMO and the LUMO are located at the A-ring,on the delocalized system.Therefore,both compounds are expected to share a similar aromatase recognition mechanism and reactivity.3.Conclusions

In this paper we have built a new pharmacophore model for an important class of aromatase inhibitors and used it in a virtual screening study for new anti-aromatase hits.Previous knowledge on the binding determinants of C6-substituted androstenedione derivatives to the aromatase active site was essential to this ligand-based approach.A hydrophobic pocket close to the C6of steroid inhibitors was explored to improve the binding af?nity of the new anti-aromatase candidates.Therefore,the combination of essential pharmacophoric features with steric restrictions and ‘‘drug-like-ness’’?lters allowed the isolation of a small subset,enriched in strong aromatase inhibitors,from the large NCI database.

The screening methodology was validated experimentally by testing some of the most promising VS hits on an in vitro assay,and new potent aromatase inhibitors were found.6-Methyl-B-nor-androstenedione (8)was one of the most interesting compounds identi?ed,with a low nanomolar IC 50and a competitive mechanism of inhibition.The strong anti-aromatase potency was rationalized based on structural and physicochemical similarities between the B-nor-androstenedione scaffold and the natural substrate of the enzyme.To the best of our knowledge,this is the ?rst report of B-nor-androgens as aromatase inhibitors.These compounds repre-sent an important new structural class of anti-aromatase agents and should be further https://www.sodocs.net/doc/7c7095843.html,pound 14was another interesting molecule identi?ed,combining strong competitive inhibition properties with mechanism-based inactivation of the https://www.sodocs.net/doc/7c7095843.html,pounds 9and 10had anti-aromatase potencies comparable to aminoglutethimide.

The value of experimentally validated virtual screening approa-ches of large compound databases relies on fast and affordable identi?cation of new hit compounds for particular targets of interest.However,hits identi?ed with such approaches are usually non-opti-mized structures.Therefore,it is not surprising that the new aroma-tase inhibitors reported in this study are less potent than formestane.Nonetheless,starting with a training set of compounds from a single class,we were able to increase the chemical diversity of aromatase inhibitors,identifying interesting new scaffolds which can be further explored by lead optimization.

In conclusion,we have described and validated a new ligand-based VS methodology for new aromatase inhibitors based on a pharmacophore model with common-features of steroid inhibi-tors.The screening of a large compound database was very fast and new potent and chemically diverse aromatase inhibitors could

be

Fig.5.A)Superimposition of the minimized structures of androstenedione (grey)and B-nor-androstenedione (white)at the ab initio HF/6-31G **level.The molecules were superimposed based on RMSD of carbon atoms at the A,C and D rings,and represented on a side (right)and top view (left).B)Electrostatic surface potential (ESP),HOMO and LUMO valence orbitals derived for androstenedione (top)and B-nor-androstenedione (bottom).The ESP was mapped on the 0.02e/?3electron density isocontour derived from ab initio HF/6-31G **calculations (V ?0.1eV,blue;V ?à0.1eV,red).The HOMO and LUMO are represented at an orbital amplitude of 0.1(blue)and à0.1(red).(For interpretation of the references to colour in ?gure legends,the reader is refered to the web version of this article).

M.A.C.Neves et al./European Journal of Medicinal Chemistry 44(2009)4121–41274125

identi?ed.Moreover,this methodology has a broader application for a large variety of compound databases.

https://www.sodocs.net/doc/7c7095843.html,putational and experimental methods

4.1.Materials and general methods

The NCI selected compounds were obtained from the Drug Synthesis and Chemistry Branch,Developmental Therapeutics Program,Division of Cancer Treatment and Diagnosis of the National Cancer Institute.DL-Aminoglutethimide,androstenedione,for-mestane and NADPH were purchased from Sigma–Aldrich(St.Louis, MO,U.S.A.).The[1b-3H]androstenedione(speci?c activity of25.3Ci/ mmol)and the liquid scintillation cocktail Optiphase Hisafe2were purchased from PerkinElmer(Boston,MA,U.S.A.).Radioactive samples were counted on a Packard Tri-Carb2900TR Liquid Scin-tillation Analyzer.All the other reagents were of adequate grade for biochemical analysis.

4.2.Pharmacophore modeling

Pharmacophore design was performed using the Catalyst soft-ware[29].The aromatase inhibitors were initially submitted to the catDB utility program and a conformational search with internal energy minimization was performed using the best quality gener-ation type.A maximum of250conformers were saved within an energy window of20kcal/mol above the global minimum.The HipHop algorithm[28]of Catalyst was used for the common-

cules(all but one feature was forced to map)and default settings were used for the other options.A similarity tolerance of0.5was used in the shape query.This value was chosen in order to match all training set molecules.

4.3.Virtual screening

The NCI database was downloaded from the2007release of the ZINC database[33]and converted into a multiconformer Catalyst database using the‘‘FAST’’conformational analysis model of the catDB utility program.A maximum of100conformations were generated and saved for each molecule.Pharmacophore searches were performed with‘‘fast?exible database search’’settings.

Instant JChem[38]was used for management,search and prediction of molecular descriptors for the NCI hits.A Lipinski Rule of Five[34]?lter was applied(molecular weight under500g/mol, not more than5hydrogen bond donors,not more than10hydrogen bond acceptors and calculated partition coef?cient,c log P,less than 5),as well as a?lter based on the maximum number of rotatable bonds(not more than8)and the maximum PSA(less than150).

4.4.Human placental isolation

Human term placental microsomes were obtained by differen-tial centrifugation,according to the method described by Ryan[39], and were used as a source of aromatase.The microsomes were obtained by differential centrifugation and were resuspended in a buffer containing sodium phosphate(0.1M),sucrose(0.25M), glycerol(20%)and dithiothreitol(0.5mM),pH7.4,and stored in aliquots atà80 C until needed.

Microsomal protein content was determined by the biuret method using bovine serum albumin as standard.

4.5.Concentration–response and kinetic studies

Aromatase activity was evaluated according to the method described by Siiteri and Thompson[40].The concentration–response and initial velocity experiments were performed as previously described[20,41].Brie?y,microsomal protein(30m g), [1b-3H]androstenedione(6.6?105dpm)and NADPH(270m M) were used for the concentration–response experiment with an incubation time of20min.The molecules in study were initially tested at10m M and100m M concentrations,followed by a full concentration–response study with at least8concentrations ranging from0.01m M to160m M.For the initial velocity study the concentration of[1b-3H]androstenedione was varied from7.5to 100nM and the incubation time was set to5min.Three different concentrations of each inhibitor were tested.The tritiated water formed during the conversion of the tritiated substrate,[1b-3H] androstenedione,to estrone was quanti?ed by liquid scintillation counting.Each assay was performed three times in duplicate and the results were treated by nonlinear regression analysis.

4.6.Time-dependent inactivation assay

Several concentrations of compounds8and14(up to ca.10times the IC50)were incubated at37 C in a medium containing sodium phosphate buffer(67mM),pH7.5,microsomal protein(300m g)and NADPH(900m M),in a?nal volume of500m L.Aliquots(50m L)were removed in duplicate at several times(0,4,8and12min),and immediately diluted in sodium phosphate buffer(67mM),pH7.5, [1b-3H]androstenedione(6.6?105dpm)and NADPH(270m M)in a?nal volume of500m L.The mixture was then incubated at37 C for 20min,and the extent of the aromatization reaction was deter-mined by liquid scintillation counting as described previously.Each assay was performed three times.First order inactivation constants (k obs),at each inactivator concentration,were obtained from the slope of linear regressions of log aromatase activity remaining versus incubation time plots,multiplied by2.303.The K I and k inact were determined from the slope and y intercept of a Kitz–Wilson plot[37],respectively.Inactivation studies in the absence of NADPH were performed in the same manner,but NADPH was omitted in the initial incubation.For the same studies in the presence of andros-tenedione or L-cysteine,the substrate(7.5m M)or L-cysteine (0.5mM)was included in the initial incubation.

4.7.Ab initio calculation details

The minimum energy conformations and electronic properties were determined by ab initio quantum chemistry calculations. Building blocks from the standard libraries of MAESTRO[42]were used to generate the initial geometry for the molecules in study, followed by a conformational search with the Systematic Unbounded Multiple Minimum(SUMM)[43]routine implemented in MACROMODEL v8.1[44],using the Merck Molecular Force Field (MMFF)[45]and the Generalized Born equation/Surface Area(GB/ SA)continuum solvation model[46]with parameters for water (dielectric constant3of78).The molecular mechanics geometries were further optimized with Gaussian98[47]using a split-valence basis set with polarization d-orbitals added to heavy atoms and polarization p-orbitals added to hydrogens(HF/6-31G**).

The optimized geometries were used to calculate electronic properties,namely the total density,ESP,HOMO and LUMO. Contour surfaces were represented using Molden v4.6software [48].

M.A.C.Neves et al./European Journal of Medicinal Chemistry44(2009)4121–4127 4126

Acknowledgements

We thank Funda?a?o para a Cie?ncia e a Tecnologia(FCT)through POCI for?nancial support and the Drug Synthesis and Chemistry Branch,Developmental Therapeutics Program,Division of Cancer Treatment and Diagnosis of the National Cancer Institute for kindly providing the compounds screened in this study.We also acknowl-edge the Maternity Daniel de Matos,Coimbra,Portugal for providing the human placenta.M.A.C.Neves thanks FCT for a Ph.D.grant (SFRH/BD/17624/2004).

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第八章蛋白质的酶促降解 生物体内的各种蛋白质经常处于动态更新之中,蛋白质的更新包括蛋白质的分解代谢和蛋白质的合成代谢;前者是指蛋白质分解为氨基酸及氨基酸继续分解为含氮的代谢产物、二氧化碳和水并释放出能量的过程。构成蛋白质的氨基酸共有20种,其共同点是均含氨基和羧基,不同点是它们的碳骨架各不相同,因此,脱去氨基后各个氨基酸的碳骨架的分解途径有所不同,这就是个别氨基酸的代谢,也可称之为氨基酸的特殊代谢。以上这些内容均属蛋白质分解代谢的范畴,并且由于这一过程是以氨基酸代谢为中心,故称为蛋白质分解和氨基酸代谢。这是本章的中心内容。此外,蛋白质的营养问题与饮食卫生和临床实践关系密切,亦在本章讨论。 第一节蛋白质的生理功能和营养作用 一、蛋白质和氨基酸的主要生理功能 维持组织的生长、更新和修补,此功能为蛋白质所特有,不能由糖或脂类代替。产生一些生理活性物质,包括胺类、神经递质、激素、嘌呤、嘧啶等。某些蛋白质具有特殊的生理功能,如血红蛋白运输氧,血浆中多种凝血因子参加血液凝固,肌肉中的肌动球蛋白与肌肉收缩有关。此外,酶、抗体、受体都是蛋白质。供给能量,每克蛋白质在体内氧化分解产生17.19kJ(4.1千卡)的能量,蛋白质的这种生理功能可由糖及脂类代替。一般情况下,蛋白质供给的能量占食物总供热量的10%~15%。 二、氮平衡(nitrogen balance)和蛋白质的需要量 体内蛋白质的代谢情况可以根据该实验来评价。蛋白质中氮的平均含量为16%, 食物中的含氮物质主要是蛋白质。故通过测定食物中氮的含量可以推算出其中的蛋白质含量。蛋白质在体内代谢后产生的含氮物质主要经尿、粪、汗排出。因此,测定每天从食物摄入的氮含量和每天排泄物(包括尿、粪、汗等)中的氮含量,可评价蛋白质在体内的代谢情况。 氮的总平衡:摄入氮 = 排出氮,见于正常成人。 氮的正平衡:摄入氮 > 排出氮,表示体内蛋白质的合成大于蛋白质的分解,见于儿童、孕妇及病后恢复期。

人教版一年级语文上册课文完整版

人教版一年级语文上册课文 1 画 远看山有色,近听水无声。春去花还在,人来鸟不惊。 2 四季 草芽尖尖, 他对小鸟说:“我是春天。”荷叶圆圆, 他对青蛙说:“我是夏天。”谷穗弯弯, 他鞠着躬说:“我是秋天。” 雪人大肚子一挺, 他顽皮地说: “我就是冬天。” 3 小小竹排画中游 小竹排,顺水流,鸟儿唱,鱼儿游。 两岸树木密, 禾苗绿油油。 江南鱼米乡, 小小竹排画中游。 4 哪座房子最漂亮 一座房,两座房, 青青的瓦,白白的墙,

宽宽的门,大大的窗。 三座房,四座房, 房前花果香, 屋后树成行。 哪座房子最漂亮 要数我们的小学堂。 5 爷爷和小树 我家门口有一棵小树。 冬天到了,爷爷给小树穿上暖和的衣裳。小树不冷了。 夏天到了,小树给爷爷撑开绿色的小伞。爷爷不热了。 6 静夜思 床前明月光, 疑是地上霜。 举头望明月, 低头思故乡。 7 小小的船 弯弯的月儿小小的船。 小小的船儿两头尖。 我在小小的船里坐, 只看见闪闪的星星蓝蓝的天。 8 阳光 阳光像金子,洒遍田野、高山和小河。 田里的禾苗,因为有了阳光,更绿了。山上的小树,因为有了阳光,更高了。河面闪着阳光,小河就像长长的锦缎了。 早晨,我拉开窗帘,阳光就跳进了我的家。 谁也捉不住阳光,阳光是大家的

阳光像金子,阳光比金子更宝贵。 9 影子 影子在前, 影子在后, 影子常常跟着我, 就像一条小黑狗。 影子在左, 影子在右, 影子常常陪着我, 它是我的好朋友。 10 比尾巴 谁的尾巴长 谁的尾巴短 谁的尾巴好像一把伞? 猴子的尾巴长。 兔子的尾巴短。 松鼠的尾巴好像一把伞。 谁的尾巴弯? 谁的尾巴扁? 谁的尾巴最好看? 公鸡的尾巴弯。 鸭子的尾巴扁。 孔雀的尾巴最好看。 11 我多想去看看 妈妈告诉我, 沿着弯弯的小路, 就能走出大山。 遥远的北京城, 有一座天安门,

人教版小学语文一年级上册复韵母ai ei ui 详细教案

ɑi、ei、ui教学设计案例 第一课时 教学目标: 1、学会复韵母ɑi、ei、ui及其四声,读准音,记清形,正确书写。 2、学习声母与ɑi、ei、ui组成的音节,能准确拼读音节,正确书写音节。 3、知道ɑi、ei、ui的标调位置。 4、能够看图说话,根据音节拼读句子。 5、能够自己拼读儿歌,做到词语连读。 二、教学重点: 学会复韵母ɑi、ei、ui,明确单韵母与复韵母之间的不同之处。 三、教学难点: 复韵母既不能读成两个音,也不能不表示口型变化的过程。 教学过程: 一、创设情境,激趣导入 1、复习单韵母 这是谁啊?对了,喜洋洋在跟你们打招呼呢?你们也跟喜洋洋问声好吧!(出示课件:喜洋洋) 看到你们这么聪明,喜洋洋要带我们去拼音乐园玩哦,拼音乐园有好多好玩的字母朋友哦,想不想去?生:想。(出示拼音乐园)欢迎小朋友来到拼音乐园,单韵母已经等了好久了,我们一起把这六个单韵母朋友读出来。(出示六个单韵母) 2、复习单韵母四声 同学们,这六位朋友来的时候,还戴了四顶小帽子呢?还记得四

声歌谣吗?生:记得。一起把四声歌谣朗读出来。一声平,二声扬,三声拐弯,四声降。这些单韵母朋友已戴上帽子,一起来边读边做动作。(出示ɑ、o、e、i、u、ü的四声)(用亲切有趣的导语,使枯燥的复习趣味盎然,同时利用创设的情境调动学生学习新课的积极性。) 二、熟读儿歌,引入新知 (一)读儿歌引出要学习的韵母。 1.多种形式读儿歌。如,老师大点儿声,学生小点儿声;老师小点儿声,学生大点儿声;谁能自己读一读等。 2、小朋友快看看,喜洋洋要带我们去学习3个复韵母和它们的拼音。单韵母ɑ、e、u最喜欢和i做朋友了。你看,它们在一起就成了ei ui,它们都是由两个单韵母合起来的,我们给它们取个名字叫复韵母ɑi。这节课我们就一起来学习复韵母ɑi ei ui(板书ɑi ei ui) 3.仔细观察一下,这3个韵母和我们以前学过的单韵母有什么不一样?你发现了吗?对呀!两个单韵母合在一起就组成了新的韵母,这样由几个字母组成的韵母就叫作复韵母。 (运用儿歌引出音节,引导学生去发现复韵母这个新知识。这样,可初步培养学生自主探究的学习能力。) (二)学习复韵母ɑi。 ɑ学习ɑi 1、看插图说话,引出ɑi:图上画了什么?(一个姐姐和一个弟弟)谁个儿高?谁个儿矮?(姐姐高,弟弟矮。) 2、ǎi是第几声?第一声该怎么念?板书:ɑi 3、教学ɑi的发音,认清字形。 ɑi 就是我们今天要学的第一个复韵母,“复韵母”念两遍。复韵母ɑi 是哪两个单韵母组成的?怎么把ɑ和i合

蛋白质的降解

第六章蛋白质的降解及其生物学意义 ?第一节蛋白质降解的概述 ?第二节参与蛋白质降解的酶类 ?第三节蛋白酶体-泛素系统及其功能 ?第四节蛋白质降解的生物学意义 蛋白质降解是生命的重要过程 ?维持细胞的稳态。 ?清除因突变、热或氧化胁迫造成的错误折叠的蛋白质,防止形成细胞内凝集。 ?及时终止不同生命时期调节蛋白的生物活性。 ?蛋白质的过度降解也是有害的,蛋白质的降解必须受到空间和时间上 蛋白质降解的体系 ?蛋白质消化分解为被机体吸收的营养物质。 ?研究蛋白质结构时,用蛋白酶降解肽链。 ?蛋白质新生肽链生物合成以及新生肽链折叠的过程中,质量的控制都与“次品”的降解有关。 ?蛋白质在行使功能时,很多调节控制都与肽键的断裂有关,如前肽的切除、无活性的前体蛋白质的激活等。 第一节蛋白质降解的概述 蛋白质的寿命 ?细胞内绝大多数蛋白质的降解是服从一级反应动力学。半衰期介于几十秒到百余天,大多数是70~80d。 ?哺乳动物细胞内各种蛋白质的平均周转率为1 ~2d。代谢过程中的关键酶以及处于分支点的酶寿命仅几分钟,有利于体内稳态在情况改变后快速建立。 –大鼠肝脏的鸟氨酸脱羧酶半衰期仅11min,是大鼠肝脏中降解最快的蛋白质。 –肌肉肌动蛋白和肌球蛋白的寿命约l~2w。 –血红蛋白的寿命超过一个月。 ?蛋白质的半衰期并不恒定,与细胞的生理状态密切相关。 蛋白质寿命的N端规则 ?N端规则:细胞质中蛋白质的寿命与肽链的N端氨基酸残基的性质有一定的关系。 ?N端的氨基酸残基为D、R、L、K和F的蛋白质,其半衰期只有2~3min。 ?N端的氨基酸残基为A、G、M和V的蛋白质,它们在原核细胞中的半衰期可超过10h,而在真核细胞中甚至可超过20h。 酿酒酵母蛋白质代谢特点 ?酿酒酵母中不稳定蛋白的N端氨基酸残基有12个:Asn(B)、Asp(D)、Glu(E)、Phe(F)、His(H)、Ile(I)、Leu(L)、Lys(K)、Arg(R)、Trp(W)、Tyr(Y)和Gln(Z)。 ?酵母中存在切除N端甲硫氨酸的氨肽酶,它作用的蛋白质底物的N端第二个氨基酸一定是N端规则中的氨基酸残基。 PEST假设 ?PEST(Pro-Glu-Ser-Thr)假设:认为含有序列为PEST肽段的蛋白质,在细胞质中很快被降解,在这个亲水的区域附近常有碱性残基。 ?PEST肽段的缺失,可以延长此突变蛋白质的寿命。 ?在22个快速降解的蛋白质中有20个是含有PEST序列。 ?在35个慢速降解的蛋白质中有32个不含PEST序列。 分泌到细胞外蛋白质的寿命 ?分泌到细胞外的蛋白质,它们的寿命都比较长,如胶原蛋白、眼睛中的晶体蛋白。

一年级上册语文课文背诵

第一单元 一二三四五,金木水火土,天地分上下,日月照今古 云对雨,雪对风。花对树,鸟对虫。山清对水秀,柳绿对桃红。(《对韵歌》) 一片两片三四片,五片六片七八片。九片十片无数片,飞入水中都不见。 鹅鹅鹅,曲项向天歌。白毛浮绿水,红掌拨清波。(《咏鹅》骆宾王唐代) 第四单元 天气凉了,树叶黄了,一片片叶子从树上落下来。天空那么蓝,那么高。一群大雁往南飞,一会排成个“人”字,一会排成个“一”字。啊!秋天来了!(《秋天》) 弯弯的月儿小小的船。小小的船儿两头尖。我在小小的船里坐,只看见闪闪的星星蓝蓝的天。(《小小的船》) 江南可采莲,莲叶何田田。鱼戏莲叶间,鱼戏莲叶东,鱼戏莲叶西,鱼戏莲叶南,鱼戏莲叶北。(《江南》) 草芽尖尖,他对小鸟说:“我是春天。” 荷叶圆圆,他对青蛙说:“我是夏天。” 谷穗弯弯,他鞠着躬说:“我是秋天。” 雪人大肚子一挺,他顽皮地说:“我就是冬天。”(《四季》) 一年之计在于春,一日之计在于晨。 一寸光阴一寸金,寸金难买寸光阴。 第五单元 远看山有色,近听水无声。春去花还在,人来鸟不惊。(《画》【唐】王维) 一个大,一个小,一只黄牛一只猫。一边多,一边少,一群鸭子一只鸟。一个大,一个小,一个苹果一颗枣。一边多,一边少,一堆杏子一个桃。(《大小多少》) 五星红旗,我们的国旗。国歌声中,徐徐升起。迎风飘扬,多么美丽。向着国旗,我们立正;望着国旗,我们敬礼。(《升国旗》) 锄禾日当午,汗滴禾下土。谁念盘中餐,粒粒皆辛苦。(《悯农诗》其二唐李绅)第六单元

谁的尾巴长?谁的尾巴短?谁的尾巴好象一把伞?猴子的尾巴长。兔子的尾巴短。松鼠的尾巴好象一把伞。谁的谁的尾巴弯?谁的尾扁?谁的尾巴最好看?公鸡的尾巴弯。鸭子的尾巴扁。孔雀的尾巴最好看。(《比尾巴》) 早晨起来,面向太阳。前面是东,后面是西。左面是北,右面是南。 小时不识月,呼作白玉盘。又疑瑶台镜,飞在青云端。(《古朗月行》〔唐〕李白)第七单元 种瓜得瓜,种豆得豆。 前人栽树,后人乘凉。 千里之行,始于足下。 百尺竿头,更进一步。 第八单元 下雪啦,下雪啦!雪地里来了一群小画家。小鸡画竹叶,小狗画梅花,小鸭画枫叶,小马画月牙。不用颜料不用笔,几步就成一幅画。青蛙为什么没参加?他在洞里睡着啦。(《雪地里的小画家》) 解落三秋叶,能开二月花。过江千尺浪,入竹万竿斜。(《风》唐·李峤) 日积月累 一片两片三四片,五片六片七八片。九片十片无数片,飞入水中都不见。 鹅鹅鹅,曲项向天歌。白毛浮绿水,红掌拨清波。(《咏鹅》骆宾王 (唐代)) 一年之计在于春,一日之计在于晨。一寸光阴一寸金,寸金难买寸光阴。 锄禾日当午,汗滴禾下土。谁念盘中餐,粒粒皆辛苦。(《悯农诗》其二唐李绅)早晨起来,面向太阳。前面是东,后面是西。左面是北,右面是南。 小时不识月,呼作白玉盘。又疑瑶台镜,飞在青云端。(《古朗月行》〔唐〕李白)种瓜得瓜,种豆得豆。前人栽树,后人乘凉。千里之行,始于足下。百尺竿头,更进一步。 解落三秋叶,能开二月花。过江千尺浪,入竹万竿斜。(《风》唐·李峤)

人教版一年级语文上册复韵母aieiui教学

教学目标: 1学会3个复韵母ai ei ui和它们的四声,能够读准音,认清形,并能准确书写。 2、能够认读声母与ai ei ui 组成的10个音节,会拼读本课的复韵母音节,会读拼音词。 教学过程 第一课时教学要求:学会复韵母ai ei ui 的四声与书写。教学过程: 一、复习检查。 1、抽读字母卡片:a o e i u u。 2、复习单韵母的四声 (2)单韵母发音嘴巴不动,复韵母发音嘴巴要滑动:发第一个字母音后马 上要发下一个字母的音,中间不能停,要一口气完成? (3) ai怎样发音呢?它与单韵母的口形有什么联系?教师再示范并边讲边提问:嘴巴先怎么样?(先张大)为什么?(因为有个a)发a音后嘴巴马上滑动,滑动到怎样为止,为什么?(滑动到上下牙齿对齐,因为a后面有个i。) (4) 师生有节奏地双边活动: 师:ai ai怎样发? 生:ai ai这样发,因为有个a,嘴巴先张大,因为有个i,牙齿再对齐,ai ai ai 。 师:口形很重要。 生:一定要记牢。 (5) 复韵母的标调规则

学习标调歌:有a不放过,没a找o e, iu 都有标在后。 (6)对照标调歌,仔细看认真想,复韵母ai怎样标调?同桌讨论讨论。 指名学生板书调号。 小结标调方法:按单韵母排列顺序标调。 (7)练读ai的四声 (二)学习复韵母ei (1)出示ei ,说说组成,想想我们应该怎样发音。(先读e,然后向i 滑行) (2)生自由练习试读,明确ei也由两个单韵母组成,因此,也叫复韵母。 (3)复习标调歌,指名说说调号应标在谁的头上 (4)练读四声 (三)学习复韵母ui (1)根据ai ei的发音方法,谁来说说我们应该怎样发ui? (2)学生自由试读 (3)学习ui的四声,强调调号标在i上,但上面的点要去掉。 (4)练读四声。 四、学习ai ei ui 的书写 1、指导观察,写的时候注意什么?(两个字母靠近) 2、练习描红 五、巩固练习。 1、抽读韵母卡片。 2、比较3个复韵母的异同。 3、读顺口溜。 四、作业] 1、练读复韵母。 2、抄写ai ei ui 各两遍。 第二课时 教学要求:学习声母与复韵母的拼读,练读音节词。 教学过程: 一、复习检查 1、什么叫复韵母?读好复韵母要注意什么? 2、复习复韵母ai ei ui 和它们的四声。 二、学习复韵母ai ei ui 的拼读。 1、复习声母。 2、复习拼音节的方法。 3、出示:

一年级语文上册课文内容

人教版语文一年级上册课文 识字一 1、《一去二三里》 一去二三里 一去二三里, 烟村四五家。 亭台六七座, 八九十枝花。 2、《口耳目》 口耳目 口耳目羊鸟兔 日月火木禾竹 3、《在家里》 沙发茶几报纸书架 台灯挂钟电视电话 晚上,爸爸在看报,妈妈在看电视。我给他们送上水果。爸爸妈妈笑了,我也笑了。 4、《操场上》 打球拔河拍皮球 跳高跑步踢足球 铃声响,下课了, 操场上,真热闹。 跳高拔河拍皮球, 天天锻炼身体好。 课文1、一去二三里 一去二三里, 烟村四五家。 亭台六七座, 八九十枝花。 课文2、四季 草芽尖尖, 他对小鸟说: “我是春天。” 荷叶圆圆, 他对青蛙说: “我是夏天。” 谷穗弯弯, 他鞠着躬说: “我是秋天。” 雪人大肚子一挺, 他顽皮地说:

“我就是冬天。” 课文3 小小竹排画中游 小竹排,顺水流, 鸟儿唱,鱼儿游。 两岸树木密, 禾苗绿油油。 江南鱼米乡, 小小竹排画中游。 课文4、《哪座房子最漂亮》 一座房,两座房, 青青的瓦,白白的墙, 宽宽的门,大大的窗。 三座房,四座房, 房前花果香, 屋后树成行。 哪座房子最漂亮? 要数我们的小学堂。 课文5、《爷爷和小树》 我家门口有一棵小树。 冬天到了,爷爷给小树穿上暖和的衣裳。小树不冷了。 夏天到了,小树给爷爷撑开绿色的小伞。爷爷不热了。 课文6、《静夜思》 床前明月光, 疑是地上霜。 举头望明月, 低头思故乡。 课文7、《小小的船》 弯弯的月儿小小的船。 小小的船儿两头尖。 我在小小的船里坐, 只看见闪闪的星星蓝蓝的天。 课文8、《阳光》 阳光像金子,洒遍田野、高山和小河。 田里的禾苗,因为有了阳光,更绿了。山上的小树,因为有了阳光,更高了。河面闪着阳光,小河就像长长的锦缎了。 早晨,我拉开窗帘,阳光就跳进了我的家。 谁也捉不住阳光,阳光是大家的。

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四、把下列韵母表补充完整。 ɑ ( ) e i u ( )( ) ei ( ) ɑo ( ) ( )( ) üe er ɑn en ( ) ( ) ( )( ) enɡ ( ) ( ) 五、写出下面音节的韵母。 kāi ( ) xuě ( ) jú ( ) mǐn ( ) què ( ) jīnɡ ( ) hǔ ( ) jùn ( ) kǒu ( ) zhēnɡ( ) qǔ ( ) lǜ ( ) 六、把下面音节的声母写在()里。 cǎo( ) hiú ( ) zhuō ( ) ruì( ) xiónɡ( ) yǎnɡ ( ) 七、连线,挑选两种你喜欢的动物,把拼音抄在四线格上 fánɡ zi hú dié xiǎo niǎo qīnɡ wā

八、连线。 là zhú tài yánɡ qiān bǐ qì qiú九、请你把下面音节补充完整。 十、连一连. fēi jī xué xiào xiǎo hé yuè er 月儿小河飞机学校十一、知道这些动物爱吃什么吗?找一找连一连。

c ǎo y ú lu ó bo ɡǔ tou 十二、你能根据下面的图画写出复韵母吗? 十三、根据汉字提示,给音节标声调。 轮 船 写 作 业 小 牛 排 队 lun chu ɑn xie zuo ye xi ɑo niu p ɑi dui you yon ɡ zhe zhi

一年级上册语文课本

小学教育资料 姓名:__________________ 班级:__________________

汉语拼音: 1. ɑāáǎà,o ōóǒò,e ēéěè. 2. i īíǐì,u ūúǔù,üǖǘǚǜ. Y W V 3. b p m f :b-ɑ-bɑ b-ɑ b-o b-i b-u p-ɑ p-o p-i p-u m-ɑ m-o m-I m-u f-ɑ f-o f-u b-ā-bā b-á-bá b-ǎ-bǎ b-à-bà bà bɑ mā mɑ wǒ 4.d:d-e-de dɑ di du t: t-e-te tɑ tit u n: nü-u-nu n-ü-nü nɑ ne ni l:l-u-lu l-ü-lü lɑ le li —————

儿歌:作者郑春华 ————— qnīɡ qīnɡde 轻轻地 xiǎo tùxiǎo tù qīnɡ qīnɡ tiào 小兔小兔轻轻跳, xiǎo ɡǒu xiǎo ɡǒu màn màn pǎo 小狗小狗慢慢跑, Yào shì cǎi ténɡle xiǎo cǎo 要是踩疼了小草, wǒ jiù bùɡēn nǐ mén hǎo 我就不跟你们好。 生字:dà mǐ tǔ de mǎ ——————— 大米土地马

——————— 复习一 我会读:ɑ o e i u ü b p m f d t n l y w 我会写:b-d f-t n-m u-ü 看看读读:lǎ bɑ mù tī yī fu pù bù 我会连:yāé tù mǎ lù lǘ 鸭鹅兔马鹿驴 我会认: 爸爸妈妈大土米我马地ɡ: ɡ-ɑ-ɡɑɡe ɡu k: k-ɑ-kɑ ke ku h: h-ɑ-hɑ he hu ɡ-u-ā-ɡuā ɡ-u-ɑ-ɡuɑɡ-u-o-ɡuo kuɑ huɑ kuo huo

小学一年级上册复韵母练习题

复韵母练习题 一、读一读,抄一抄。 ao ou iu 二、请你帮助小兔把音节完整的写下来。 三、读一读 1. hu ü er z ǎo z ǎo de k üi le 。 2. ni ú ni ú p üi p í qi ú。 3. b ǎo b ǎo z ài h y shu ǐ。 ao b m z

四、读读这首古诗,然后,背一背,做一做。 长cháng 歌g y 行xíng 百bǎi 川chuün 东dōng 到dào 海hǎi ,何h ? 时shí复f ù 西x ī 归guī 。 少shào 壮zhuàng 不b ù 努n ǔ 力l ì,老lǎo 大d à 徒t ú 伤shüng 悲byi 。 找出学过的复韵母,用红笔圈出来。 ie ?e er 五、你能根据下面的图画写出复韵母 吗? 六、请你把下面音节补充完整, 七、连一连? f yi j ī xu ? xi ào xi ǎo h ? yu a er 月儿 小河 飞机 学校 ?e j q x ( ) ( ) ( ) ie j q x ( ) ( ) ( )

八、把音节补充完整 y m ? h j 要门爷回家 你栽树,他培土, 我去提水。 九、图画音节连一连。 wū guī cì wei xǐ qua bái cài 十、知道这些动物爱吃什么吗?找一找连一连。 cǎo yú luó bo gǔ tou

十一、对号入座,读准音节选一选。 hu ǒ ni ú y óu xu y bi ǎo p ǎo ( ) ( ) ( ) ( ) ( ) ( ) 十二、读一读,想一想,做一做。 看月亮kànyualiàng 初一看chūyīkàn ,一条线yītiáoxiàn ;初二三chūarsün ,眉毛弯m?imáowün ; 初五六chūwǔliù,挂银镰guàyínlián ;初七八c h ūq īb ü,像小船xiàngxiǎochuán ; 初九十chūjiǔshí,切半圆qiybànyuán ;十五六shíwǔliù,像玉盘xiàngyùpán 。 1.照样子,填一填。 弯弯的月亮像小船,圆圆的月亮像 。 2.你喜欢圆圆的月亮还是弯弯的月亮?能给它画张像吗? 动动脑 筋啊!

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