Differential transport of cytosine-containing nucleosides by recombinant human concentrative nucleoside transporter protein hCNT1

The transportability of cytosine-containing nucleosides by recombinant hCNT1 was investigated in transfected mammalian cells. Apparent K(m) values for hCNT1-mediated transport of uridine, cytidine and deoxycytidine were, respectively, 59, 140 and 150 microM. Uridine transport was inhibited 89, 32 and 11%, respectively, by 500 microM gemcitabine, cytarabine and lamivudine, demonstrating that, unlike gemcitabine (a high-affinity hCNT1 permeant), cytarabine and lamivudine are poor hCNT1 permeants.     

Involvement of the concentrative nucleoside transporter 3 and equilibrative nucleoside transporter 2 in the resistance of T-lymphoblastic cell lines to thiopurines

Mechanisms of resistance to thiopurines, 6-mercaptopurine (6-MP) and 6-thioguanine (6-TG) were investigated in human leukemia cell lines. We developed two 6-MP- and 6-TG-resistant cell lines from the human T-lymphoblastic cell line (MOLT-4) by prolonged exposure to these drugs. The resistant cells were highly cross resistant to 6-MP and 6-TG, and exhibited marked reduction in cellular uptake of 6-MP (70% and 80%, respectively). No significant modification of the activities of hypoxanthine-guanine phosphoribosyl transferase, thiopurine methyltransferase or inosine monophosphate dehydrogenase was observed. Real-time PCR of concentrative nucleoside transporter 3 (CNT3) and equilibrative nucleoside transporter 2 (ENT2) of resistant cells showed substantial reductions in expression of messenger RNAs. Small interfering RNA designed to silence the CNT3 and ENT2 genes down-regulated the expression of these genes in leukemia cells. These decreases were accompanied by reduction of transport of 6-MP (47% and 21%, respectively) as well as its cytocidal effect (30% and 21%, respectively). Taken together these results show that CNT3 and ENT2 play a key role in the transport of 6-MP and 6-TG by leukemia cells. From a clinical point of view determination of CNT3 and ENT2 levels in leukemia cells may be useful in predicting the efficacy of thiopurine treatment.     

Systematic evaluation of CS‐Rosetta for membrane protein structure prediction with sparse NOE restraints

We critically test and validate the CS‐Rosetta methodology for de novo structure prediction of ‐helical membrane proteins (MPs) from NMR data, such as chemical shifts and NOE distance restraints. By systematically reducing the number and types of NOE restraints, we focus on determining the regime in which MP structures can be reliably predicted and pinpoint the boundaries of the approach. Five MPs of known structure were used as test systems, phototaxis sensory rhodopsin II (pSRII), a subdomain of pSRII, disulfide binding protein B (DsbB), microsomal prostaglandin E2 synthase‐1 (mPGES‐1), and translocator protein (TSPO). For pSRII and DsbB, where NMR and X‐ray structures are available, resolution‐adapted structural recombination (RASREC) CS‐Rosetta yields structures that are as close to the X‐ray structure as the published NMR structures if all available NMR data are used to guide structure prediction. For mPGES‐1 and Bacillus cereus TSPO, where only X‐ray crystal structures are available, highly accurate structures are obtained using simulated NMR data. One main advantage of RASREC CS‐Rosetta is its robustness with respect to even a drastic reduction of the number of NOEs. Close‐to‐native structures were obtained with one randomly picked long‐range NOEs for every 14, 31, 38, and 8 residues for full‐length pSRII, the pSRII subdomain, TSPO, and DsbB, respectively, in addition to using chemical shifts. For mPGES‐1, atomically accurate structures could be predicted even from chemical shifts alone. Our results show that atomic level accuracy for helical membrane proteins is achievable with CS‐Rosetta using very sparse NOE restraint sets to guide structure prediction. Proteins 2017; 85:812–826. © 2016 Wiley Periodicals, Inc.     

SimFold energy function for de novo protein structure prediction: consensus with Rosetta

Predicting protein tertiary structures by in silico folding is still very difficult for proteins that have new folds. Here, we developed a coarse-grained energy function, SimFold, for de novo structure prediction, performed a benchmark test of prediction with fragment assembly simulations for 38 test proteins, and proposed consensus prediction with Rosetta. The SimFold energy consists of many terms that take into account solvent-induced effects on the basis of physicochemical consideration. In the benchmark test, SimFold succeeded in predicting native structures within 6.5 A for 12 of 38 proteins; this success rate was the same as that by the publicly available version of Rosetta (ab initio version 1.2) run with default parameters. We investigated which energy terms in SimFold contribute to structure prediction performance, finding that the hydrophobic interaction is the most crucial for the prediction, whereas other sequence-specific terms have weak but positive roles. In the benchmark, well-predicted proteins by SimFold and by Rosetta were not the same for 5 of 12 proteins, which led us to introduce consensus prediction. With combined decoys, we succeeded in prediction for 16 proteins, four more than SimFold or Rosetta separately. For each of 38 proteins, structural ensembles generated by SimFold and by Rosetta were qualitatively compared by mapping sampled structural space onto two dimensions. For proteins of which one of the two methods succeeded and the other failed in prediction, the former had a less scattered ensemble located around the native. For proteins of which both methods succeeded in prediction, often two ensembles were mixed up.     

Synthesis and biological evaluation of phloridzin analogs as human concentrative nucleoside transporter 3 (hCNT3) inhibitors

Nucleoside transporter inhibitors have potential therapeutic applications as anticancer, antiviral, cardioprotective and neuroprotective agents. Although quite a few potent inhibitors of the equilibrative nucleoside transporters are known, largely missing are the concentrative nucleoside transporter inhibitors. Phloridzin (3, K_i = 16.00 μM) is a known moderate inhibitor of the concentrative nucleoside transporters. We have synthesized and evaluated analogs of phloridzin at the hCNT3 nucleoside transporter. Within the series of synthesized analogs compound 16 (K_i = 2.88 μM), possessing a ribofuranose sugar unit instead of a glucopyranose as present in phloridzin, exhibited the highest binding affinity at the hCNT3 transporter. Phloridzin and compound 16 have also been shown to be selective for the hCNT3 transporter as compared with the hENT1 transporter. Compound 16 can serve as a new lead which after further modifications could yield selective and potent hCNT3 inhibitors.     

Conserved residues F316 and G476 in the concentrative nucleoside transporter 1 (hCNT1) affect guanosine sensitivity and membrane expression, respectively

The functional significance of two highly conserved amino acid residues, F316 [putative transmembrane domain (TM)7] and G476 (putative TM11), in the concentrative nucleoside transporter hCNT1 (SLC28A1) was examined by performing site-directed mutagenesis. Conservative mutations at these positions (F316A, F316Y, G476A, and G476L) were generated and expressed in Madin-Darby canine kidney (MDCK) cells as fusion polypeptides with green fluorescent protein (GFP). Unlike wild-type hCNT1, G476A-GFP and G476L-GFP were not expressed in the plasma membrane in undifferentiated or differentiated MDCK cells and had no functional activity. Like wild-type hCNT1, F316A-GFP and F316Y-GFP were expressed in the plasma membrane of undifferentiated MDCK cells and in the apical membrane of differentiated MDCK cells. Remarkably, transport of [³H]uridine by F316Y-GFP or F316A-GFP was highly sensitive to inhibition by guanosine. Furthermore, genotyping of exon 11 of hCNT1 (TM7) in a panel of 260 anonymous human DNA samples revealed a novel F316H variant (TT>CA; 1/260). When expressed in MDCK cells, [³H]uridine transport by F316H was also found to be sensitive to inhibition by guanosine (IC₅₀ = 148 µM). The effect of the F316H mutation resembles the N4 type nucleoside transporter phenotype previously reported to be present in human kidneys. We suggest that the N4 transport system is a naturally occurring variant of hCNT1, perhaps at the F316 position. Collectively, our data show that G476 is important for correct membrane targeting, folding, and/or intracellular processing of hCNT1. In addition, we have discovered that hCNT1 displays natural variation at position F316 and that the variant F316H confers on the transporter an unusual sensitivity to inhibition by guanosine. localization; inhibition; polymorphism     

Inward- and outward-facing homology modeling of human concentrative nucleoside transporter 3 (hCNT3) predicts an elevator-type transport mechanism

The human SLC28 family of concentrative (Na⁺-dependent) nucleoside transporters has three members, hCNT1, hCNT2 and hCNT3. Previously, we have used heterologous expression in Xenopus laevis oocytes in combination with an engineered cysteine-less hCNT3 protein hCNT3(C-) to undertake systematic substituted cysteine accessibility method (SCAM) analysis of the transporter using the membrane-impermeant thiol reactive reagent p-chloromercuribenzene sulfonate (PCMBS). A continuous sequence of more than 300 individual amino acid residue positions were investigated, including the entire transport domain of the protein, as well as important elements of the corresponding hCNT3 structural domain. We have now constructed 3D structural homology models of hCNT3 based upon inward-facing, intermediates and outward-facing crystal structures of the bacterial CNT Neisseria wadsworthii CNT_NW to show that all previously identified PCMBS-sensitive residues in hCNT3 are located above (ie on the extracellular side of) the key diagonal barrier scaffold domain TM9 in the transporter’s outward-facing conformation. In addition, both the Na⁺ and permeant binding sites of the mobile transport domain of hCNT3 are elevated from below the scaffold domain TM9 in the inward-facing conformation to above TM9 in the outward-facing conformation. The hCNT3 homology models generated in the present study validate our previously published PCMBS SCAM data, and confirm an elevator-type mechanism of membrane transport.     

Scoring function accuracy for membrane protein structure prediction

We perform a systematic examination of the ability of several different high-resolution, atomic-detail scoring functions to discriminate native conformations of loops in membrane proteins from non-native but physically reasonable, or "decoy," conformations. Decoys constructed from changing a loop conformation while keeping the remainder of the protein fixed are a challenging test of energy function accuracy. Nevertheless, the best of the energy functions we examined recognized the native structure as lowest in energy around half the time, and consistently chose it as a low-energy structure. This suggests that the best of present energy functions, even without a representation of the lipid bilayer, are of sufficient accuracy to give reasonable confidence in predictions of membrane protein structure. We also constructed homology models for each structure, using other known structures in the same protein family as templates. Homology models were constructed using several scoring functions and modeling programs, but with a comparable sampling effort for each procedure. Our results indicate that the quality of sequence alignment is probably the most important factor in model accuracy for sequence identity from 20-40%; one can expect a reasonably accurate model for membrane proteins when sequence identity is greater than 30%, in agreement with previous studies. Most errors are localized in loop regions, which tend to be found outside the lipid bilayer. For the most discriminative energy functions, it appears that errors are most likely due to lack of sufficient sampling, although it should be stressed that present energy functions are still far from perfectly reliable.     

Monkey corticotropin-releasing factor1 receptor: Complementary DNA cloning and pharmacological characterization

The full-length complementary DNA (cDNA) of monkey corticotropin-releasing factor type 1 (CRF1) receptor was isolated from a rhesus monkey (Macaca mulatta) amygdala cDNA library. The cloned monkey CRF1 receptor cDNA has 2,374 bp with an open reading frame encoding a 415-amino acid protein. The sequence of the monkey CRF1 receptor cDNA showed a high degree of sequence identity with other species of CRF1 receptors, and being 99.5% identical to human CRF1 receptors. When monkey CRF1 was expressed into COS-7 cells, high specific binding of [125I]-ovine CRF was observed. CRF and CRF-related peptides inhibited [125I]-ovine CRF binding in a concentration-dependent manner. IC50 values of ovine CRF, human/rat CRF, sauvagine and urotensin I were 23.5 +/- 7.4, 22.7 +/- 10.8, 27.5 +/- 12.3 and 14.2 +/- 7.0 nM, respectively. CRF1 receptor specific antagonists, such as CP-154,526, SC241 and CRA1000, also inhibited the [125I]-ovine CRF binding, with IC50 values of 3.9 +/- 0.4, 43.5 +/- 8.0 and 19.8 +/- 2.0 nM, respectively. GTP and its nonhydrolyzed analogue, GTPgammaS, reduced [125I]-ovine CRF binding, while ATP had a negligible effect, thereby indicating that the monkey CRF1 receptor belongs to a family of G-protein coupled receptors. CRF and its related peptides increased cyclic AMP formation concentration-dependently in COS-7 cells transiently expressing the monkey CRF1 receptor. Monkey CRF1 was expressed abundantly in the pituitary, cerebral cortex, hippocampus, amygdala and cerebellum. Thus the monkey CRF1 receptor and the human CRF1 receptor have similar molecular and pharmacological characteristics.     

Cation coupling properties of human concentrative nucleoside transporters hCNT1, hCNT2 and hCNT3

The SLC28 family of concentrative nucleoside transporter (CNT) proteins in mammalian cells contains members of two distinct phylogenic subfamilies. In humans, hCNT1 and hCNT2 belong to one subfamily, and hCNT3 to the other. All three CNTs mediate inwardly-directed Na(+)/nucleoside cotransport, and are either pyrimidine nucleoside-selective (hCNT1), purine nucleoside-selective (hCNT2), or broadly selective for both pyrimidine and purine nucleosides (hCNT3). While previous studies have characterized cation interactions with both hCNT1 and hCNT3, little is known about the corresponding properties of hCNT2. In the present study, heterologous expression in Xenopus oocytes in combination with radioisotope flux and electrophysiological techniques has allowed us to undertake a side-by-side comparison of hCNT2 with other hCNT family members. Apparent K (50) values for Na(+) activation were voltage-dependent, and similar in magnitude for all three transporters. Only hCNT3 was also able to couple transport of uridine to uptake of H(+). The Na(+)/nucleoside stoichiometry of hCNT2, as determined from both Hill coefficients and direct charge/flux measurements, was 1:1. This result was the same as for hCNT1, but different from that of hCNT3 (2:1). The charge-to-(22)Na(+) uptake stoichiometry was 1:1 for all three hCNTs. In parallel with their division into two separate CNT subfamilies, hCNT2 shares common cation specificity and coupling characteristics with hCNT1, which differ markedly from those of hCNT3.     

Functional and protein chemical characterization of the N-terminal domain of the rat corticotropin-releasing factor receptor 1

Rat corticotropin-releasing factor receptor 1 (rCRFR1) was produced either in transfected HEK 293 cells as a complex glycosylated protein or in the presence of the mannosidase I inhibitor kifunensine as a high mannose glycosylated protein. The altered glycosylation did not influence the biological function of rCRFR1 as demonstrated by competitive binding of rat urocortin (rUcn) or human/rat corticotropin-releasing factor (h/rCRF) and agonist-induced cAMP accumulation. The low production rate of the N-terminal domain of rCRFR1 (rCRFR1-NT) by transfected HEK 293 cells, was increased by a factor of 100 in the presence of kifunensine. The product, rCRFR1-NT-Kif, bound rUcn specifically (K(D) = 27 nM) and astressin (K(I) = 60 nM). This affinity was 10-fold lower than the affinity of full length rCRFR1. However, it was sufficiently high for rCRFR1-NT-Kif to serve as a model for the N-terminal domain of rCRFR1. With protein fragmentation, Edman degradation, and mass spectrometric analysis, evidence was found for the signal peptide cleavage site C-terminally to Thr(23) and three disulfide bridges between precursor residues 30 and 54, 44 and 87, and 68 and 102. Of all putative N-glycosylation sites in positions 32, 38, 45, 78, 90, and 98, all Asn residues except for Asn(32) were glycosylated to a significant extent. No O-glycosylation was observed.     

Synthesis and evaluation of 2-anilino-3-phenylsulfonyl-6-methylpyridines as corticotropin-releasing factor1 receptor ligands

A novel series of 2-anilino-3-phenylsulfonyl-6-methylpyridines was synthesized and evaluated as corticotropin-releasing factor receptor ligands. Structure-activity relationship studies focused primarily on optimization of the 3-phenylsulfonyl group. Compounds within this series were identified which showed potent binding affinity for the CRF1 receptor. Selected compounds were examined in a rat pharmacokinetic study and were found to have oral bioavailabilities ranging from 16 to 35%.     

I-TASSER server for protein 3D structure prediction

Background  

Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions.     

TransportTP: A two-phase classification approach for membrane transporter prediction and characterization

Background  

Membrane transporters play crucial roles in living cells. Experimental characterization of transporters is costly and time-consuming. Current computational methods for transporter characterization still require extensive curation efforts, especially for eukaryotic organisms. We developed a novel genome-scale transporter prediction and characterization system called TransportTP that combined homology-based and machine learning methods in a two-phase classification approach. First, traditional homology methods were employed to predict novel transporters based on sequence similarity to known classified proteins in the Transporter Classification Database (TCDB). Second, machine learning methods were used to integrate a variety of features to refine the initial predictions. A set of rules based on transporter features was developed by machine learning using well-curated proteomes as guides.     

Optimal mutation sites for PRE data collection and membrane protein structure prediction

Nuclear magnetic resonance paramagnetic relaxation enhancement (PRE) measures long-range distances to isotopically labeled residues, providing useful constraints for protein structure prediction. The method usually requires labor-intensive conjugation of nitroxide labels to multiple locations on the protein, one at a time. Here a computational procedure, based on protein sequence and simple secondary structure models, is presented to facilitate optimal placement of a minimum number of labels needed to determine the correct topology of?a helical transmembrane protein. Tests on DsbB (four helices) using just one label lead to correct topology predictions in four of five cases, with the predicted structures <6 ? to the native structure. Benchmark results using simulated PRE data show that we can generally predict the correct topology for five and six to seven helices using two and three labels, respectively, with an average success rate of 76% and structures of similar precision. The results show promise in facilitating experimentally constrained structure prediction of membrane proteins.     

A method for α-helical integral membrane protein fold prediction

Integral membrane proteins (of the α-helical class) are of central importance in a wide variety of vital cellular functions. Despite considerable effort on methods to predict the location of the helices, little attention has been directed toward developing an automatic method to pack the helices together. In principle, the prediction of membrane proteins should be easier than the prediction of globular proteins: there is only one type of secondary structure and all helices pack with a common alignment across the membrane. This allows all possible structures to be represented on a simple lattice and exhaustively enumerated. Prediction success lies not in generating many possible folds but in recognizing which corresponds to the native. Our evaluation of each fold is based on how well the exposed surface predicted from a multiple sequence alignment fits its allocated position. Just as exposure to solvent in globular proteins can be predicted from sequence variation, so exposure to lipid can be recognized by variable-hydrophobic (variphobic) positions. Application to both bacteriorhodopsin and the eukaryotic rhodopsin/opsin families revealed that the angular size of the lipid-exposed faces must be predicted accurately to allow selection of the correct fold. With the inherent uncertainties in helix prediction and parameter choice, this accuracy could not be guaranteed but the correct fold was typically found in the top six candidates. Our method provides the first completely automatic method that can proceed from a scan of the protein sequence databanks to a predicted three-dimensional structure with no intervention required from the investigator. Within the limited domain of the seven helix bundle proteins, a good chance can be given of selecting the correct structure. However, the limited number of sequences available with a corresponding known structure makes further characterization of the method difficult. © 1994 John Wiley & Sons, Inc.     

MUFOLD: A new solution for protein 3D structure prediction

There have been steady improvements in protein structure prediction during the past 2 decades. However, current methods are still far from consistently predicting structural models accurately with computing power accessible to common users. Toward achieving more accurate and efficient structure prediction, we developed a number of novel methods and integrated them into a software package, MUFOLD. First, a systematic protocol was developed to identify useful templates and fragments from Protein Data Bank for a given target protein. Then, an efficient process was applied for iterative coarse‐grain model generation and evaluation at the Cα or backbone level. In this process, we construct models using interresidue spatial restraints derived from alignments by multidimensional scaling, evaluate and select models through clustering and static scoring functions, and iteratively improve the selected models by integrating spatial restraints and previous models. Finally, the full‐atom models were evaluated using molecular dynamics simulations based on structural changes under simulated heating. We have continuously improved the performance of MUFOLD by using a benchmark of 200 proteins from the Astral database, where no template with >25% sequence identity to any target protein is included. The average root‐mean‐square deviation of the best models from the native structures is 4.28 Å, which shows significant and systematic improvement over our previous methods. The computing time of MUFOLD is much shorter than many other tools, such as Rosetta. MUFOLD demonstrated some success in the 2008 community‐wide experiment for protein structure prediction CASP8. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

The prediction of membrane protein structure and genome structural annotation

New methods, essentially based on hidden Markov models (HMM) and neural networks (NN), can predict the topography of both beta-barrel and all-alpha membrane proteins with high accuracy and a low rate of false positives and false negatives. These methods have been integrated in a suite of programs to filter proteomes of Gram-negative bacteria, searching for new membrane proteins.     

基于蛋白质结构预测的胰岛素样生长因子-1的制备及活性分析北大核心CSCD

为了更经济高效地制备胰岛素样生长因子-1 (insulin-like growth factor-1, IGF-1),本研究采用计算机模拟技术对3种IGF-1融合蛋白进行蛋白质结构预测与分子对接,筛选出酶切最适配的IGF-1融合蛋白表达形式。利用基因工程技术构建并鉴定了IGF-1融合蛋白原核表达载体,并转化大肠杆菌Origami B(DE3)菌株,获得重组子;经异丙基-β-D-硫代吡喃半乳糖苷(isopropyl-β-D-1-thiogalactopyranoside, IPTG)诱导表达后,对菌体的破菌上清进行亲和层析、脱盐、凝血酶酶切及酶切产物亲和层析纯化得到目的蛋白;通过3T3细胞增殖法建立活性评价体系并对获得的IGF-1进行活性测定。结果显示,构建的IGF-1融合蛋白原核表达载体序列正确,获得的重组子在25℃、0.05 mmol/L IPTG诱导16 h时融合蛋白为可溶性表达,经初步纯化、凝血酶酶切、再次纯化后可获得纯度大于90%的IGF-1目的蛋白,在建立的活性评价体系下测得制备的IGF-1比活为2.47×10^(5)U/mg,与市售标准品接近。本研究建立了一条用于制备IGF-1的完整工艺路线,为IGF-1药物的研制及工业化生产奠定基础。