- Open Access
Suggestion of suitable animal models for in vivo studies of protein tyrosine phosphatase 1b (PTP1B) inhibitors using computational approaches
© Nguyen and Le; licensee Springer. 2014
Received: 13 May 2014
Accepted: 16 July 2014
Published: 28 July 2014
PTP1B is a prototypic enzyme of the superfamily protein tyrosine phosphatases (PTPs) which are critical regulators of tyrosine phosphorylation-dependent signaling events. It is a highly plausible candidate for designing therapeutic inhibitors of obesity and type 2 diabetes (T2D). In this study, a detailed comparative analysis to reveal the evolutionary relationship of human PTP1B among related vertebrates has been addressed.
The phylogenetic trees were constructed with maximum likelihood algorithm by PhyML package on the basis of multiple sequence alignment (MSA) by ClustalΩ and T-coffee. Mutational variability of the sequences corresponding to the 3D structure (pdb: 2vev) was analyzed with Consurf software. The comparative analysis by inhibitor docking to different models was made to confirm the suitability of models.
As a result, the PTP1B or PTP non-receptor type 1 homologies show high conservativity where about 70% positions on primary structures are conserved. Within PTP domain (3–277), the most variable positions are 12, 13, 19 and 24 which is a part of the second aryl binding site. Moreover, there are important evolutional mutations that can change the conformation of the proteins, for instance, hydrophilic N139 changed to hydrophobic Gly (mPTP1B); E132 to proline in the hydrophobic core structure or Y46 to cystein in pTyr recognition loop. These variations/differences should be taken into account for rational inhibitor design and in choosing suitable animal models for drug testing and evaluation. Moreover, our study suggests critically potential models which are Heterocephalus glaber, Tupaia chinensis, Sus scrofa, and Rattus norvegicus in addition to the best one Macaca fascicularis. Among these models, the H.glaber and R.norvegicus are preferable over M.musculus thanks to their similarity in binding affinity and binding modes to investigated PTP1B inhibitors.
Among the PTPs superfamily, PTP1B has become prominent for its down regulation of both insulin and leptin signaling and control of glucose homeostasis and energy expenditure (Tsou and Bence 2012). It terminates the signaling cascade by dephosphorylating the tyrosine residues on its substrates, the phosphotyrosine kinases (PTKs). As a major negative regulator of Janus kinase in JAK-STAT signaling, moreover, PTP1B is recognized to be a key link between metabolic diseases (Tonks 2003), inflammation (Pike et al. 2014) and cancer (Feldhammer et al. 2013).
In insulin signaling, PTP1B acts to dephosphorylate the insulin receptor (IR) at tandem Y1162/Y1163 (Tsou and Bence 2012; Galic et al. 2005) and possibly the insulin receptor substrate 1 (IRS-1) (Galic et al. 2005). Increasing expressed PTP1B and its activity result in over dephosphorylation of IR and kinases leading to interruption of insulin cascades and hence insulin resistance in target tissues.
On the other approach, PTP1B antagonizes leptin signaling via direct dephosphorylation of the active site of the leptin receptor-associated tyrosine kinase JAK2 (Tsou and Bence 2012; Zabolotny et al. 2002; Cheng et al. 2002; Myers et al. 2001). In common obesity, there’s a phenomenon called leptin resistance reflecting the failure of leptin to inhibit energy intake and to increase energy expenditure (Enriori et al. 2006). Since its impact on terminating the leptin signaling, PTP1B is a highly plausible candidate for therapeutic inhibitors to restore leptin sensitivity and prevent disease in the non-adipose tissues (Cook and Unger 2002).
Interestingly, PTP1B-deficient mice were shown to increase insulin sensitivity and resistance to diet-induced obesity (Kahn and Flier 2000; Elchebly et al. 1999; Klaman et al. 2000). Since the discovery of PTP1B in 1988, it has become an important target for treatment of diabetes mellitus and obesity. As over 80% of individuals with T2D are obese (Nadler et al. 2000), PTP1B inhibition may be a potential strategy for a therapeutic target of type 2 diabetes through its links with obesity.
This protein has been well-studied in structure and substrate binding (Tonks 2003). There are four important loops in the catalytic site which are PTP, pTyr, WPD and Q loops. PTP loops contain the signature motif [I/V]HCXXGXXR [S/T] which is highly conserved among classical PTP sub-family. The pTyr loop plays a role in recognition of Tyr tandem in the substrate and contains Tyr46 which defines the depth of the binding site and contributes to absolute substrate specificity of PTP1B to phosphotyrosine-containing substrates. The Cys215 in PTP loop, Asp181 in WPD loop and Gln262 in Q loop are reactive residues essential for catalysis. The second aryl binding site was characterized by Arg24, Arg254 and Gly259 (Andersen et al. 2001). This finding has been supporting variety of PTP1B inhibitor studies (Zhang and Lee 2003).
However, none of potential inhibitors could pass clinical trials which lead to the need of thorough investigating on both functional and evolutionary relationships of PTP1B to other PTPs and among species to avoid inhibitor side effects and to increase suitability of animal in vivo test prior to clinical trials. Although the intra-relation among PTP domains of human and vertebrates was reviewed with sequence and partially structure analysis (Andersen et al. 2001), a detailed comparative study to reveal the inter-relation specifically of human PTP1B among related species has not been addressed yet. Hence, the final objective of this study is to propose potentially suitable animal models for in vivo drug testing and strategies for further rational inhibitor designs against PTP1B, particularly as treatment for obesity-associated diabetes.
Results and discussion
Phylogenetic study of PTP1B protein
Essentially, hPTP1B (P18031), in this study, acts as indicator for choosing suitable animal models for in vivo tests due to its relevance to clinical studies for drug targeting (Sobhia et al. 2012). For this reason, group 1 was not chosen for further analysis because of distant evolution from hPTP1B. Furthermore, ptp1b sequences from these species reveal critical variations/mutations in PTP domains (Figure 3). Arg45 and Tyr46 in pTyr recognition loop are mutated to Lys and Cys respectively in Clonorchis. Within the Q loop (262–269), there are variations observed in Pediculus (I-V; A-P; D-G), Culex (A-F; R-Y), Lepeophtheirus (A-W; R-K). Among those, the mutations from Asp265 (negatively charged) to Gly (hydrophobic) in Pediculus may affect the conformation of the loop. Looking into the second aryl binding site of the protein (Andersen et al. 2001), Arg24 is quite varied in group 1 sequences. Point mutations from R (positively charged) to E (negatively charged), to L (hydrophobic) or even deleted (gapped) may cause significant differences in substrate trapping/interaction of the PTP1B in these species from that of hPTP1B.
Analysis on evolutionary conservation
The PTP1B homologous sequences of group 2 among 18 selected species including human were analyzed thoroughly by Consurf server. This test not only helped resolve which are the most variable/conserved regions on the protein but also contributed to the selection of proper animal models.
Ranking the candidates based on variation/conservativity level within PTP domains (275 residues)
1.1.Macaca fascicularis (long-tailed macaque)
1.2.Macaca mulatta (rhesus monkey)
Bos taurus (domestic cow)
Sus scrofa (wild pig)
Heterocephalus glaber (naked mole rat)
Tupaia chinensis (tree shrew)
6.1.Pteropus alecto (black flying-fox)
6.2.Myotis brandtii (brandt’s bat)
Bos grunniensmutus (wild yak)
Rattus norvegicus (rat)
Mus musculus (mouse)
Gallus gallus (chicken)
Chelonia mydas (green turtle)
Anas platyrhynchos (wild duck)
Xenopus (Silurana) tropicalis (tropical clawed frog)
Xenopus laevis (African clawed frog)
Danio rerio (zebrafish)
Inhibitor docking into models’ PTP1B 3D structures
Seven candidates, Sus scrofa, Tupaia chinensis, Heterocephalus glaber, Myotis brantdii, Pteropus alecto, Rattus norvegicus and Mus musculus, which are available and have high potential were chosen for further analysis on structures and ligand interactions. The PTP1B proteins of these animals have no experimental structures yet; hence they are modeled as homologs from the template 2VEV of human PTP1B catalytic domain with 299 residues. The sequence identity of models to human template is over 80% and the overall pattern of the structure of PTP1B catalytic domain is conserved (Additional file 1).
These models, along with hPTP1B (pdb: 2vev), were investigated as to their ligand interaction by inhibitor docking with Ertiprotafib (Ki 1500 nM) and five other small molecules published as potential PTP1B antagonists denoted as compounds 1 to 5 (Zhang and Lee 2003). Compound 1 (affinity 220 nM) is peptidomimetics of 3-carboxy-4-(O-carboxymethyl) tyrosine core that could augment insulin action in the cell (Larsen et al. 2003). Compound 2 (Ki 2 μM) is the ortho tetrazole analogue in which tetrazole moiety is well-accommodated in the active site (Liljebris et al. 2002). Compound 3 (Ki 0.6 μM) was developed by Novo Nordisk group to address the second aryl phosphate-binding pocket of PTP1B (Iversen et al. 2001). Abbott group investigated about compound 4 (Ki 77 nM) for interacting with both binding sites on the PTP1B enzyme (Liu and Trevillyan 2002). The non-hydrolyzable analog, compound 5 (Ki 2.4 nM), was the most potent inhibitor for being capable of occupying both active site and a unique peripheral site (Shen et al. 2001).
Calculated binding energies ΔG inter (kcal/mol) of six PTP1B inhibitors to protein models with hPTP1B as standard
P.alecto had strong affinity to compound 2, just as hPTP1B does but it had weak affinity to compound 4 and 5. Most models had relatively good binding affinity to compound 3, particularly the S.scrofa and H.glaber models responsed the same as hPTP1B. However, in this study, the hPTP1B binding site for compound 3 showed slight differences to the experimental report (Iversen et al. 2001). We could not observe the salt bridge between the molecule and Asp48 because, in our study, there was no water molecule introduced during the conventional docking procedure.
This study intensively analyzes the phylogenetic relationship between hPTP1B and other common vertebrates. Important mutations/variations in second-aryl binding sites, adjacent regions of Q loop and hydrophobic core structure should be noticeable as protein conformational differences which are likely to lead to disagreement between in silico design and in vivo testing. Rats, as a common model, are more preferable for having higher similarity with hPTP1B than mice while Heterocephalus glaber emerges as new model due to better suitability and agreement in the target PTP1B sequences.
Among all, H.glaber and R.norvegicus are preferred over M.musculus thanks to their similarity in binding affinity and binding modes to investigated PTP1B inhibitors. They are also more common and available than other animals as models for in vivo tests.
It is recommended that the study can be scaled up for investigating more variety of potential PTP1B inhibitors in these animal models. It is also necessary to study whether functions of PTP1B homologs in these animals are similar in human or not. In order to ensure the success of drug development as well as to reduce time and cost, the suitability of animal tests is very critical to prevent false positive results.
Multiple sequence alignment and phylogenetic tree construction
Full-length sequence of hPTP1B with 435 amino acids (Swiss-Prot: P18031) collected from the UniProtKB database (http://www.uniprot.org/) was the query sequence for a Blastp (Altschul et al. 1990) search from the non-redundant protein database with default parameters (BLOSUM 62 matrix (Henikoff and Henikoff 1992)). From a maximum 250 homologies, qualified sequences which could represent the PTP1B homologs in different vertebrates were the materials for multiple sequence alignment (MSA) using Clustal Omega (Sievers et al. 2011) with input ordered and Phylip output format (http://www.ebi.ac.uk/Tools/msa/clustalo/). The result of MSA was also compared and verified by T-Coffee method (Notredame et al. 2000) and the algorithm of genetic semihomology (Leluk 1998; Leluk et al. 2001) respectively. The consensus sequence of aligned PTP-non receptor type 1 sequences was then constructed with the aid of Consensus constructor (Fogtman and Lesyng 2005). The parameters used were: identity 91.67%, significance 29.17%, gaps 50%. The refined MSA was then used as input for the construction of a phylogenetic tree by the PHYML approach (Guindon and Gascuel 2003) which implements the maximum likelihood method. The options were adjusted for amino acid data type, Jones, Taylor, and Thornton (JTT) substitution model and tree topology best searching of NNI (Nearest Neighbor Interchange) and SPR (Subtree Prune and Regraft) search.
Analysis of evolutionary conservativity
The evolutionary conservativity/variability of aligned protein homologies was calculated with the help of Consurf (Glaser et al. 2003; Landau et al. 2005; Ashkenazy et al. 2010) (http://consurf.tau.ac.il/). The conservativity scores were calculated by Bayesian method. JTT was the evolutionary substitution model applied. Evolutionarily functional positions and regions were also analyzed on the basis of the hPTP1B structure [PDB: 2VEV] and visualized by Chimera (Meng et al. 2006) version 1.8 (http://www.cgl.ucsf.edu/chimera/).
Inhibitor docking into PTP1B models
The 3D structures of PTP1B of most potential animal candidate were constructed by homology modeling on the Swiss-Model server (http://swissmodel.expasy.org) from the template hPTP1B catalytic domain structure (residues 1–321) on Protein Data Bank (PDB: 2VEV). The model quality was mainly evaluated based on the QMEAN4 score which is a composite score consisting of a linear combination of 4 statistical potential terms (estimated model reliability between 0–1) and RMSD values.
Six PTP1B inhibitors reviewed (Zhang and Lee 2003) were prepared in 3D structures. The docking step between newly modeled protein structures and these inhibitors was undergone by AutoDock Vina package (Trott and Olson 2010). The ligands were prepared by the graphical user interface AutoDockTools (http://mgltools.scripps.edu/downloads). The input ligands were added Gasteiger charged if missing, merged non-polar H, detected rotatable bonds and then set Torsion degree of freedom (TORSDOF). The receptors were also prepared as pdbqt file with the grid map information. The center of the grid box was (17, 18, 77) and applied to all the receptor structures as they are written in the same pattern of coordinates. This box has the size of 30Ǻ at each square face and cover both known binding pockets of PTP1B. The docking step was run with two CPU, exhaustiveness 10 and only the binding mode with the lowest free binding energy was recorded. The resulting docking scores were the predicted free binding energies (Gibbs, ΔG) with the intramolecular contributions taken into account (c = cinter + cintra). The predicted docking scores in this study were then re-calculated into the interaction energies that avoid the interferences caused by high torsion numbers of the inhibitors (with more than 10 rotatable bonds). The following formula helped compute the final binding energies:
ΔGinter = ΔGpred *(1 + 0.05846 Nrot) (Trott and Olson 2010)
Binding modes were further analyzed in the context with protein binding sites by LigPlot+ v.1.4 (Laskowski and Swindells 2011).
This research was funded by the Ho Chi Minh International University-Vietnam National University. The computing resources and support by the Institute for Computer Science and Technology (ICST) at the Ho Chi Minh City are gracefully acknowledged. We highly appreciate Mr. Hieu Nguyen and Mr. Vuong Van Quan who are researchers of Life Science Lab of ICST for their valuable help with docking techniques.
- Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. J Mol Biol 1990, 215(3):403-410. http://dx.doi.org/10.1016/S0022-2836(05)80360-2View ArticleGoogle Scholar
- Andersen JN, Mortensen OH, Peters GH, Drake PG, Iversen LF, Olsen OH, Jansen PG, Andersen HS, Tonks NK, Møller NPH: Structural and evolutionary relationships among protein tyrosine phosphatase domains. Mol Cell Biol 2001, 21(21):7117-7136. doi:10.1128/mcb.21.21.7117-7136.2001View ArticleGoogle Scholar
- Ashkenazy H, Erez E, Martz E, Pupko T, Ben-Tal N: ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res 2010, 38(suppl 2):W529-W533. doi:10.1093/nar/gkq399View ArticleGoogle Scholar
- Cheng A, Uetani N, Simoncic PD, Chaubey VP, Lee-Loy A, McGlade CJ, Kennedy BP, Tremblay ML: Attenuation of leptin action and regulation of obesity by protein tyrosine phosphatase 1B. Dev Cell 2002, 2(4):497-503. doi:S1534580702001491View ArticleGoogle Scholar
- Cook WS, Unger RH: Protein tyrosine phosphatase 1B: a potential leptin resistance factor of obesity. Dev Cell 2002, 2(4):385-387. doi:S1534580702001582View ArticleGoogle Scholar
- Elchebly M, Payette P, Michaliszyn E, Cromlish W, Collins S, Loy AL, Normandin D, Cheng A, Himms-Hagen J, Chan C-C, Ramachandran C, Gresser MJ, Tremblay ML, Kennedy BP: Increased insulin sensitivity and obesity resistance in mice lacking the protein tyrosine phosphatase-1B gene. Science 1999, 283(5407):1544-1548. doi:10.1126/science.283.5407.1544View ArticleGoogle Scholar
- Enriori PJ, Evans AE, Sinnayah P, Cowley MA: Leptin resistance and obesity. Obesity 2006, 14(S8):254S-258S. doi:10.1038/oby.2006.319View ArticleGoogle Scholar
- Feldhammer M, Uetani N, Miranda-Saavedra D, Tremblay ML: PTP1B: a simple enzyme for a complex world. Crit Rev Biochem Mol Biol 2013, 48(5):430-445. doi:10.3109/10409238.2013.819830View ArticleGoogle Scholar
- Fogtman ALJ, Lesyng B: Beta-spectrin consensus sequence construction with variable threshold parameters; verification of usefulness. Bio-Algorithms Med-Syst 2005, 1: 117-120.Google Scholar
- Galic S, Hauser C, Kahn BB, Haj FG, Neel BG, Tonks NK, Tiganis T: Coordinated regulation of insulin signaling by the protein tyrosine phosphatases PTP1B and TCPTP. Mol Cell Biol 2005, 25(2):819-829. doi:10.1128/mcb.25.2.819-829.2005View ArticleGoogle Scholar
- Glaser F, Pupko T, Paz I, Bell RE, Bechor-Shental D, Martz E, Ben-Tal N: ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information. Bioinformatics 2003, 19(1):163-164. doi:10.1093/bioinformatics/19.1.163View ArticleGoogle Scholar
- Guindon S, Gascuel O: A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 2003, 52(5):696-704. doi:10.1080/10635150390235520View ArticleGoogle Scholar
- Henikoff S, Henikoff JG: Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci 1992, 89(22):10915-10919.View ArticleGoogle Scholar
- Iversen LF, Andersen HS, Moller KB, Olsen OH, Peters GH, Branner S, Mortensen SB, Hansen TK, Lau J, Ge Y, Holsworth DD, Newman MJ, Hundahl Moller NP: Steric hindrance as a basis for structure-based design of selective inhibitors of protein-tyrosine phosphatases. Biochemistry 2001, 40(49):14812-14820. doi:bi011389lView ArticleGoogle Scholar
- Kahn BB, Flier JS: Obesity and insulin resistance. J Clin Invest 2000, 106(4):473-481. doi:10.1172/jci10842View ArticleGoogle Scholar
- Klaman LD, Boss O, Peroni OD, Kim JK, Martino JL, Zabolotny JM, Moghal N, Lubkin M, Kim Y-B, Sharpe AH, Stricker-Krongrad A, Shulman GI, Neel BG, Kahn BB: Increased energy expenditure, decreased adiposity, and tissue-specific insulin sensitivity in protein-tyrosine phosphatase 1B-deficient mice. Mol Cell Biol 2000, 20(15):5479-5489. doi:10.1128/mcb.20.15.5479-5489.2000View ArticleGoogle Scholar
- Landau M, Mayrose I, Rosenberg Y, Glaser F, Martz E, Pupko T, Ben-Tal N: ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures. Nucleic Acids Res 2005, 33(suppl 2):W299-W302. doi:10.1093/nar/gki370View ArticleGoogle Scholar
- Larsen SD, Stevens FC, Lindberg TJ, Bodnar PM, O’Sullivan TJ, Schostarez HJ, Palazuk BJ, Bleasdale JE: Modification of the N-terminus of peptidomimetic protein tyrosine phosphatase 1B (PTP1B) inhibitors: identification of analogues with cellular activity. Bioorg Med Chem Lett 2003, 13(5):971-975. http://dx.doi.org/10.1016/S0960-894X(02)01065-XView ArticleGoogle Scholar
- Laskowski RA, Swindells MB: LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. J Chem Inf Model 2011, 51(10):2778-2786. doi:10.1021/ci200227uView ArticleGoogle Scholar
- Leluk J: A new algorithm for analysis of the homology in protein primary structure. Comput Chem 1998, 22(1):123-131. doi:S0097-8485(97)00035-1View ArticleGoogle Scholar
- Leluk J, Hanus-Lorenz B, Sikorski AF: Application of genetic semihomology algorithm to theoretical studies on various protein families. Acta Biochim Pol 2001, 48(1):21-33.Google Scholar
- Liljebris C, Larsen SD, Ogg D, Palazuk BJ, Bleasdale JE: Investigation of potential bioisosteric replacements for the carboxyl groups of peptidomimetic inhibitors of protein tyrosine phosphatase 1B: identification of a tetrazole-containing inhibitor with cellular activity. J Med Chem 2002, 45(9):1785-1798. doi:jm011100yView ArticleGoogle Scholar
- Liu G, Trevillyan JM: Protein tyrosine phosphatase 1B as a target for the treatment of impaired glucose tolerance and type II diabetes. Curr Opin Investig Drugs 2002, 3(11):1608-1616.Google Scholar
- Meng E, Pettersen E, Couch G, Huang C, Ferrin T: Tools for integrated sequence-structure analysis with UCSF Chimera. BMC Bioinformatics 2006, 7(1):339.View ArticleGoogle Scholar
- Myers MP, Andersen JN, Cheng A, Tremblay ML, Horvath CM, Parisien JP, Salmeen A, Barford D, Tonks NK: TYK2 and JAK2 are substrates of protein-tyrosine phosphatase 1B. J Biol Chem 2001, 276(51):47771-47774. doi:10.1074/jbc.C100583200 [doi] C100583200Google Scholar
- Nadler ST, Stoehr JP, Schueler KL, Tanimoto G, Yandell BS, Attie AD: The expression of adipogenic genes is decreased in obesity and diabetes mellitus. PNAS 2000, 97(21):11371-11376.View ArticleGoogle Scholar
- Notredame C, Higgins DG, Heringa J: T-Coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 2000, 302(1):205-217. doi:10.1006/jmbi.2000.4042 [doi] S0022-2836(00)94042-7View ArticleGoogle Scholar
- Pike KA, Hutchins AP, Vinette V, Theberge J-F, Sabbagh L, Tremblay ML, Miranda-Saavedra D: Protein Tyrosine Phosphatase 1B Is a Regulator of the Interleukin-10-Induced Transcriptional Program in Macrophages. Sci Signal 2014, 7(324):ra43. doi:10.1126/scisignal.2005020View ArticleGoogle Scholar
- Shen K, Keng YF, Wu L, Guo XL, Lawrence DS, Zhang ZY: Acquisition of a specific and potent PTP1B inhibitor from a novel combinatorial library and screening procedure. J Biol Chem 2001, 276(50):47311-47319. doi:10.1074/jbc.M106568200 [doi] M106568200View ArticleGoogle Scholar
- Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Soding J, Thompson JD, Higgins DG: Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 2011., 7: doi.org/10.1038/msb.2011.75Google Scholar
- Sobhia ME, Paul S, Shinde R, Potluri M, Gundam V, Kaur A, Haokip T: Protein tyrosine phosphatase inhibitors: a patent review (2002 – 2011). Expert Opin Ther Pat 2012, 22(2):125-153. doi:10.1517/13543776.2012.661414View ArticleGoogle Scholar
- Tonks NK: PTP1B: from the sidelines to the front lines! FEBS Lett 2003, 546(1):140-148. http://dx.doi.org/10.1016/S0014-5793(03)00603-3View ArticleGoogle Scholar
- Trott O, Olson AJ: AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 2010, 31(2):455-461. doi:10.1002/jcc.21334 [doi]Google Scholar
- Tsou RC, Bence KK: The genetics of PTPN1 and obesity: insights from mouse models of tissue-specific PTP1B deficiency. J Obes 2012, 2012: 8. doi:10.1155/2012/926857View ArticleGoogle Scholar
- Zabolotny JM, Bence-Hanulec KK, Stricker-Krongrad A, Haj F, Wang Y, Minokoshi Y, Kim YB, Elmquist JK, Tartaglia LA, Kahn BB, Neel BG: PTP1B regulates leptin signal transduction in vivo. Dev Cell 2002, 2(4):489-495. doi:S153458070200148XView ArticleGoogle Scholar
- Zhang ZY, Lee SY: PTP1B inhibitors as potential therapeutics in the treatment of type 2 diabetes and obesity. Expert Opin Investig Drugs 2003, 12(2):223-233. doi:10.1517/135437220.127.116.11 [doi]View ArticleGoogle Scholar
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