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In Silico and In Vitro Considerations of Keratinocyte Nuclear Receptor Protein Structural Order for Improving Experimental Analysis

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Epidermal Cells

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2109))

Abstract

Nuclear receptors (NR) regulate gene expression critical in keratinocyte replication and differentiation. In addition to a ligand-binding domain, NR like other transcription factor families have a DNA-binding domain that must attain a particular conformation for effective interaction with the three-dimensional structure in promoters of target genes for control of their expression. Such protein-DNA assemblies extend the classic “lock and key” idea typified by protein-protein interactions. However, it is becoming increasingly clear that multi-subdomain transcription factors like NR frequently range along the length of the protein from structured, ordered regions expected for interaction with a preset partner to more flexible, intrinsically disordered regions which are more available for diverse posttranslational modifications and/or interaction with differing partners. The extended amino terminus of NR (the A/B subdomain) is one such intrinsically disordered region. Here we provide a primer on in silico-based recognition of amino acid composition and order associated with such conformational flexibility along with adaptations of readily accessible laboratory techniques (e.g., considerations for recombinant expression, sensitivity to protease and proteasome digestion) to facilitate initial prediction and testing for intrinsic disorder in various proteins of interest to keratinocyte biologists, like NR and other transcription factors.

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References

  1. Weikum ER, Liu X, Ortlund EA (2018) The nuclear receptor superfamily: a structural perspective. Protein Sci 27(11):1876–1892. https://doi.org/10.1002/pro.3496

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Sevilla LM, Perez P (2018) Roles of the glucocorticoid and mineralocorticoid receptors in skin pathophysiology. Int J Mol Sci 19(7):E1906. https://doi.org/10.3390/ijms19071906

    Article  CAS  PubMed  Google Scholar 

  3. Montagner A, Wahli W, Tan NS (2015) Nuclear receptor peroxisome proliferator activated receptor (PPAR) beta/delta in skin wound healing and cancer. Eur J Dermatol 25(Suppl 1):4–11

    CAS  PubMed  Google Scholar 

  4. Hyter S, Indra AK (2013) Nuclear hormone receptor functions in keratinocyte and melanocyte homeostasis, epidermal carcinogenesis and melanomagenesis. FEBS Lett 587(6):529–541. https://doi.org/10.1016/j.febslet.2013.01.041

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kretzschmar K, Cottle DL, Schweiger PJ, Watt FM (2015) The androgen receptor antagonizes Wnt/beta-catenin signaling in epidermal stem cells. J Invest Dermatol 135(11):2753–2763. https://doi.org/10.1038/jid.2015.242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Zhang C, Gurevich I, Aneskievich BJ (2012) Organotypic modeling of human keratinocyte response to peroxisome proliferators. Cells Tissues Organs 196(5):431–441. https://doi.org/10.1159/000336268

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Xu D, Cai L, Guo S, Xie L, Yin M, Chen Z, Zhou H, Su Y, Zeng Z, Zhang X (2017) Virtual screening and experimental validation identify novel modulators of nuclear receptor RXRalpha from Drugbank database. Bioorg Med Chem Lett 27(4):1055–1061. https://doi.org/10.1016/j.bmcl.2016.12.058

    Article  CAS  PubMed  Google Scholar 

  8. Khorasanizadeh S, Rastinejad F (2016) Visualizing the architectures and interactions of nuclear receptors. Endocrinology 157(11):4212–4221. https://doi.org/10.1210/en.2016-1559

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Mazaira GI, Zgajnar NR, Lotufo CM, Daneri-Becerra C, Sivils JC, Soto OB, Cox MB, Galigniana MD (2018) The nuclear receptor field: a historical overview and future challenges. Nucl Receptor Res 5:101320. https://doi.org/10.11131/2018/101320

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Rastinejad F, Ollendorff V, Polikarpov I (2015) Nuclear receptor full-length architectures: confronting myth and illusion with high resolution. Trends Biochem Sci 40(1):16–24. https://doi.org/10.1016/j.tibs.2014.10.011

    Article  CAS  PubMed  Google Scholar 

  11. Chrisman IM, Nemetchek MD, de Vera IMS, Shang J, Heidari Z, Long Y, Reyes-Caballero H, Galindo-Murillo R, Cheatham TE 3rd, Blayo AL, Shin Y, Fuhrmann J, Griffin PR, Kamenecka TM, Kojetin DJ, Hughes TS (2018) Defining a conformational ensemble that directs activation of PPARgamma. Nat Commun 9(1):1794. https://doi.org/10.1038/s41467-018-04176-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kojetin DJ, Matta-Camacho E, Hughes TS, Srinivasan S, Nwachukwu JC, Cavett V, Nowak J, Chalmers MJ, Marciano DP, Kamenecka TM, Shulman AI, Rance M, Griffin PR, Bruning JB, Nettles KW (2015) Structural mechanism for signal transduction in RXR nuclear receptor heterodimers. Nat Commun 6:8013. https://doi.org/10.1038/ncomms9013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Goswami D, Callaway C, Pascal BD, Kumar R, Edwards DP, Griffin PR (2014) Influence of domain interactions on conformational mobility of the progesterone receptor detected by hydrogen/deuterium exchange mass spectrometry. Structure 22(7):961–973. https://doi.org/10.1016/j.str.2014.04.013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Khan SH, Jasuja R, Kumar R (2017) Trehalose induces functionally active conformation in the intrinsically disordered N-terminal domain of glucocorticoid receptor. J Biomol Struct Dyn 35(10):2248–2256. https://doi.org/10.1080/07391102.2016.1214086

    Article  CAS  PubMed  Google Scholar 

  15. Khan SH, McLaughlin WA, Kumar R (2017) Site-specific phosphorylation regulates the structure and function of an intrinsically disordered domain of the glucocorticoid receptor. Sci Rep 7(1):15440. https://doi.org/10.1038/s41598-017-15549-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chandra V, Huang P, Hamuro Y, Raghuram S, Wang Y, Burris TP, Rastinejad F (2008) Structure of the intact PPAR-gamma-RXR-nuclear receptor complex on DNA. Nature 456(7220):350–356. https://doi.org/10.1038/nature07413

    Article  PubMed  PubMed Central  Google Scholar 

  17. Chandra V, Huang P, Potluri N, Wu D, Kim Y, Rastinejad F (2013) Multidomain integration in the structure of the HNF-4alpha nuclear receptor complex. Nature 495(7441):394–398. https://doi.org/10.1038/nature11966

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Laptenko O, Tong DR, Manfredi J, Prives C (2016) The tail that wags the dog: how the disordered c-terminal domain controls the transcriptional activities of the p53 tumor-suppressor protein. Trends Biochem Sci 41(12):1022–1034. https://doi.org/10.1016/j.tibs.2016.08.011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Follis AV, Galea CA, Kriwacki RW (2012) Intrinsic protein flexibility in regulation of cell proliferation: advantages for signaling and opportunities for novel therapeutics. Adv Exp Med Biol 725:27–49. https://doi.org/10.1007/978-1-4614-0659-4_3

    Article  CAS  PubMed  Google Scholar 

  20. Atkins JD, Boateng SY, Sorensen T, McGuffin LJ (2015) Disorder prediction methods, their applicability to different protein targets and their usefulness for guiding experimental studies. Int J Mol Sci 16(8):19040–19054. https://doi.org/10.3390/ijms160819040

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dyson HJ, Wright PE (2016) Role of intrinsic protein disorder in the function and interactions of the transcriptional coactivators CREB-binding protein (CBP) and p300. J Biol Chem 291(13):6714–6722. https://doi.org/10.1074/jbc.R115.692020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wright PE, Dyson HJ (2015) Intrinsically disordered proteins in cellular signalling and regulation. Nat Rev Mol Cell Biol 16(1):18–29. https://doi.org/10.1038/nrm3920

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Dyson HJ (2012) Roles of intrinsic disorder in protein-nucleic acid interactions. Mol BioSyst 8(1):97–104. https://doi.org/10.1039/c1mb05258f

    Article  CAS  PubMed  Google Scholar 

  24. Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT (2004) Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J Mol Biol 337(3):635–645. https://doi.org/10.1016/j.jmb.2004.02.002

    Article  CAS  PubMed  Google Scholar 

  25. Uversky VN, Oldfield CJ, Dunker AK (2008) Intrinsically disordered proteins in human diseases: introducing the D2 concept. Annu Rev Biophys 37:215–246. https://doi.org/10.1146/annurev.biophys.37.032807.125924

    Article  CAS  PubMed  Google Scholar 

  26. Darling AL, Uversky VN (2018) Intrinsic disorder and posttranslational modifications: the darker side of the biological dark matter. Front Genet 9:158. https://doi.org/10.3389/fgene.2018.00158

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Uversky VN (2013) Unusual biophysics of intrinsically disordered proteins. Biochim Biophys Acta 1834(5):932–951. https://doi.org/10.1016/j.bbapap.2012.12.008

    Article  CAS  PubMed  Google Scholar 

  28. Dunker AK, Cortese MS, Romero P, Iakoucheva LM, Uversky VN (2005) Flexible nets. The roles of intrinsic disorder in protein interaction networks. FEBS J 272(20):5129–5148

    Article  CAS  Google Scholar 

  29. Oldfield CJ, Cheng Y, Cortese MS, Romero P, Uversky VN, Dunker AK (2005) Coupled folding and binding with alpha-helix-forming molecular recognition elements. Biochemistry 44(37):12454–12470. https://doi.org/10.1021/bi050736e

    Article  CAS  PubMed  Google Scholar 

  30. Wright PE, Dyson HJ (2009) Linking folding and binding. Curr Opin Struct Biol 19(1):31–38. https://doi.org/10.1016/j.sbi.2008.12.003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Iakoucheva LM, Radivojac P, Brown CJ, O’Connor TR, Sikes JG, Obradovic Z, Dunker AK (2004) The importance of intrinsic disorder for protein phosphorylation. Nucleic Acids Res 32(3):1037–1049. https://doi.org/10.1093/nar/gkh253

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Wycisk K, Tarczewska A, Kaus-Drobek M, Dadlez M, Holubowicz R, Pietras Z, Dziembowski A, Taube M, Kozak M, Orlowski M, Ozyhar A (2018) Intrinsically disordered N-terminal domain of the Helicoverpa armigera Ultraspiracle stabilizes the dimeric form via a scorpion-like structure. J Steroid Biochem Mol Biol 183:167–183

    Article  CAS  Google Scholar 

  33. Pieprzyk J, Zbela A, Jakob M, Ozyhar A, Orlowski M (2014) Homodimerization propensity of the intrinsically disordered N-terminal domain of Ultraspiracle from Aedes aegypti. Biochim Biophys Acta 1844(6):1153–1166. https://doi.org/10.1016/j.bbapap.2014.03.010

    Article  CAS  PubMed  Google Scholar 

  34. Rochette-Egly C, Germain P (2009) Dynamic and combinatorial control of gene expression by nuclear retinoic acid receptors (RARs). Nucl Recept Signal 7:e005. https://doi.org/10.1621/nrs.07005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Simons SS Jr, Edwards DP, Kumar R (2014) Minireview: dynamic structures of nuclear hormone receptors: new promises and challenges. Mol Endocrinol 28(2):173–182. https://doi.org/10.1210/me.2013-1334

    Article  CAS  PubMed  Google Scholar 

  36. Willison KR (2018) The substrate specificity of eukaryotic cytosolic chaperonin CCT. Philos Trans R Soc Lond Ser B Biol Sci 373(1749):20170192. https://doi.org/10.1098/rstb.2017.0192

    Article  CAS  Google Scholar 

  37. Tsvetkov P, Myers N, Moscovitz O, Sharon M, Prilusky J, Shaul Y (2012) Thermo-resistant intrinsically disordered proteins are efficient 20S proteasome substrates. Mol Biosyst 8(1):368–373. https://doi.org/10.1039/c1mb05283g

    Article  CAS  PubMed  Google Scholar 

  38. Sickmeier M, Hamilton JA, LeGall T, Vacic V, Cortese MS, Tantos A, Szabo B, Tompa P, Chen J, Uversky VN, Obradovic Z, Dunker AK (2007) DisProt: the database of disordered proteins. Nucleic Acids Res 35(Database issue):D786–D793. https://doi.org/10.1093/nar/gkl893

    Article  CAS  PubMed  Google Scholar 

  39. Fukuchi S, Sakamoto S, Nobe Y, Murakami SD, Amemiya T, Hosoda K, Koike R, Hiroaki H, Ota M (2012) IDEAL: intrinsically disordered proteins with extensive annotations and literature. Nucleic Acids Res 40(Database issue):D507–D511. https://doi.org/10.1093/nar/gkr884

    Article  CAS  PubMed  Google Scholar 

  40. Theillet FX, Kalmar L, Tompa P, Han KH, Selenko P, Dunker AK, Daughdrill GW, Uversky VN (2013) The alphabet of intrinsic disorder: I. Act like a pro: on the abundance and roles of proline residues in intrinsically disordered proteins. Intrinsically Disord Proteins 1(1):e24360

    Article  Google Scholar 

  41. Vacic V, Uversky VN, Dunker AK, Lonardi S (2007) Composition profiler: a tool for discovery and visualization of amino acid composition differences. BMC Bioinformatics 8:211

    Article  Google Scholar 

  42. Bairoch A, Apweiler R (2000) The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res 28(1):45–48

    Article  CAS  Google Scholar 

  43. Lebendiker M, Danieli T (2014) Production of prone-to-aggregate proteins. FEBS Lett 588(2):236–246. https://doi.org/10.1016/j.febslet.2013.10.044

    Article  CAS  PubMed  Google Scholar 

  44. Suskiewicz MJ, Sussman JL, Silman I, Shaul Y (2011) Context-dependent resistance to proteolysis of intrinsically disordered proteins. Protein Sci 20(8):1285–1297. https://doi.org/10.1002/pro.657

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Uversky VN (2017) Paradoxes and wonders of intrinsic disorder: stability of instability. Intrinsically Disord Proteins 5(1):e1327757. https://doi.org/10.1080/21690707.2017.1327757

    Article  PubMed  PubMed Central  Google Scholar 

  46. Kalthoff C (2003) A novel strategy for the purification of recombinantly expressed unstructured protein domains. J Chromatogr B Analyt Technol Biomed Life Sci 786(1–2):247–254

    Article  CAS  Google Scholar 

  47. Livernois AM, Hnatchuk DJ, Findlater EE, Graether SP (2009) Obtaining highly purified intrinsically disordered protein by boiling lysis and single step ion exchange. Anal Biochem 392(1):70–76. https://doi.org/10.1016/j.ab.2009.05.023

    Article  CAS  PubMed  Google Scholar 

  48. Babu MM, van der Lee R, de Groot NS, Gsponer J (2011) Intrinsically disordered proteins: regulation and disease. Curr Opin Struct Biol 21(3):432–440. https://doi.org/10.1016/j.sbi.2011.03.011

    Article  CAS  PubMed  Google Scholar 

  49. McEwan IJ, Lavery D, Fischer K, Watt K (2007) Natural disordered sequences in the amino terminal domain of nuclear receptors: lessons from the androgen and glucocorticoid receptors. Nucl Recept Signal 5:e001

    Article  Google Scholar 

  50. Davies P, Watt K, Kelly SM, Clark C, Price NC, McEwan IJ (2008) Consequences of poly-glutamine repeat length for the conformation and folding of the androgen receptor amino-terminal domain. J Mol Endocrinol 41(5):301–314. https://doi.org/10.1677/JME-08-0042

    Article  CAS  PubMed  Google Scholar 

  51. Swatek KN, Komander D (2016) Ubiquitin modifications. Cell Res 26(4):399–422. https://doi.org/10.1038/cr.2016.39

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ben-Nissan G, Sharon M (2014) Regulating the 20S proteasome ubiquitin-independent degradation pathway. Biomol Ther 4(3):862–884. https://doi.org/10.3390/biom4030862

    Article  CAS  Google Scholar 

  53. Erales J, Coffino P (2014) Ubiquitin-independent proteasomal degradation. Biochim Biophys Acta 1843(1):216–221. https://doi.org/10.1016/j.bbamcr.2013.05.008

    Article  CAS  PubMed  Google Scholar 

  54. Tsvetkov P, Asher G, Paz A, Reuven N, Sussman JL, Silman I, Shaul Y (2008) Operational definition of intrinsically unstructured protein sequences based on susceptibility to the 20S proteasome. Proteins 70(4):1357–1366. https://doi.org/10.1002/prot.21614

    Article  CAS  PubMed  Google Scholar 

  55. Ngoc LV, Wauquier C, Soin R, Bousbata S, Twyffels L, Kruys V, Gueydan C (2014) Rapid proteasomal degradation of posttranscriptional regulators of the TIS11/tristetraprolin family is induced by an intrinsically unstructured region independently of ubiquitination. Mol Cell Biol 34(23):4315–4328. https://doi.org/10.1128/MCB.00643-14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Wiggins CM, Tsvetkov P, Johnson M, Joyce CL, Lamb CA, Bryant NJ, Komander D, Shaul Y, Cook SJ (2011) BIM(EL), an intrinsically disordered protein, is degraded by 20S proteasomes in the absence of poly-ubiquitylation. J Cell Sci 124(Pt 6):969–977. https://doi.org/10.1242/jcs.058438

    Article  CAS  PubMed  Google Scholar 

  57. UniProt Consortium T (2018) UniProt: the universal protein knowledgebase. Nucleic Acids Res 46(5):2699. https://doi.org/10.1093/nar/gky092

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Sigrist CJ, de Castro E, Cerutti L, Cuche BA, Hulo N, Bridge A, Bougueleret L, Xenarios I (2013) New and continuing developments at PROSITE. Nucleic Acids Res 41(Database issue):D344–D347. https://doi.org/10.1093/nar/gks1067

    Article  CAS  PubMed  Google Scholar 

  59. Obradovic Z, Peng K, Vucetic S, Radivojac P, Brown CJ, Dunker AK (2003) Predicting intrinsic disorder from amino acid sequence. Proteins 53(Suppl 6):566–572. https://doi.org/10.1002/prot.10532

    Article  CAS  PubMed  Google Scholar 

  60. Romero P, Obradovic Z, Li X, Garner EC, Brown CJ, Dunker AK (2001) Sequence complexity of disordered protein. Proteins 42(1):38–48. https://doi.org/10.1002/1097-0134(20010101)42:1<38::AID-PROT50>3.0.CO;2-3

    Article  CAS  Google Scholar 

  61. Peng K, Vucetic S, Radivojac P, Brown CJ, Dunker AK, Obradovic Z (2005) Optimizing long intrinsic disorder predictors with protein evolutionary information. J Bioinforma Comput Biol 3(1):35–60

    Article  CAS  Google Scholar 

  62. Peng K, Radivojac P, Vucetic S, Dunker AK, Obradovic Z (2006) Length-dependent prediction of protein intrinsic disorder. BMC Bioinformatics 7:208

    Article  Google Scholar 

  63. Varadi M, Kosol S, Lebrun P, Valentini E, Blackledge M, Dunker AK, Felli IC, Forman-Kay JD, Kriwacki RW, Pierattelli R, Sussman J, Svergun DI, Uversky VN, Vendruscolo M, Wishart D, Wright PE, Tompa P (2014) pE-DB: a database of structural ensembles of intrinsically disordered and of unfolded proteins. Nucleic Acids Res 42(Database issue):D326–D335. https://doi.org/10.1093/nar/gkt960

    Article  CAS  PubMed  Google Scholar 

  64. Murray B, Zhang B, Skrzypek E, Kornhauser JM, Latham V, Nandhikonda V, Gnad F, Hornbeck PV, Nord A, Wheeler T (2018) 15 years of PhosphoSitePlus®: integrating post-translationally modified sites, disease variants and isoforms. Nucleic Acids Res 47(D1):D433–D441. https://doi.org/10.1093/nar/gky1159

    Article  CAS  PubMed Central  Google Scholar 

  65. Meszaros B, Erdos G, Dosztanyi Z (2018) IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic Acids Res 46(W1):W329–W337. https://doi.org/10.1093/nar/gky384

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Dosztanyi Z, Csizmok V, Tompa P, Simon I (2005) IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 21(16):3433–3434

    Article  CAS  Google Scholar 

  67. Lieutaud P, Ferron F, Uversky AV, Kurgan L, Uversky VN, Longhi S (2016) How disordered is my protein and what is its disorder for? A guide through the “dark side” of the protein universe. Intrinsically Disord Proteins 4(1):e1259708. https://doi.org/10.1080/21690707.2016.1259708

    Article  PubMed  PubMed Central  Google Scholar 

  68. Uversky VN, Dunker AK (2010) Understanding protein non-folding. Biochim Biophys Acta 1804(6):1231–1264. https://doi.org/10.1016/j.bbapap.2010.01.017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Wilkins MR, Gasteiger E, Bairoch A, Sanchez JC, Williams KL, Appel RD, Hochstrasser DF (1999) Protein identification and analysis tools in the ExPASy server. Methods Mol Biol 112:531–552

    CAS  PubMed  Google Scholar 

  70. Tsvetkov P, Shaul Y (2012) Determination of IUP based on susceptibility for degradation by default. Methods Mol Biol 895:3–18. https://doi.org/10.1007/978-1-61779-927-3_1

    Article  CAS  PubMed  Google Scholar 

  71. Piovesan D, Tabaro F, Mičetić I, Necci M, Quaglia F, Oldfield CJ, Aspromonte MC, Davey NE, Davidović R, Dosztányi Z, Elofsson A, Gasparini A, Hatos A, Kajava AV, Kalmar L, Leonardi E, Lazar T, Macedo-Ribeiro S, Macossay-Castillo M, Meszaros A, Minervini G, Murvai N, Pujols J, Roche DB, Salladini E, Schad E, Schramm A, Szabo B, Tantos A, Tonello F, Tsirigos KD, Veljković N, Ventura S, Vranken W, Warholm P, Uversky VN, Dunker AK, Longhi S, Tompa P, Tosatto SC (2017) DisProt 7.0: a major update of the database of disordered proteins. Nucleic Acids Res 45(D1):D1123–D1124. https://doi.org/10.1093/nar/gkw1056

    Article  CAS  PubMed  Google Scholar 

  72. Receveur-Brechot V, Bourhis JM, Uversky VN, Canard B, Longhi S (2006) Assessing protein disorder and induced folding. Proteins 62(1):24–45. https://doi.org/10.1002/prot.20750

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

Earlier work from our group referenced here was supported in part by a USPHS/NIH grant to BJA (AR048660) from NIAMS. RS was supported by an assistantship from the Department of Pharmaceutical Sciences.

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Authors and Affiliations

  1. School of Pharmacy, University of Connecticut, Storrs, CT, USA

    Rambon Shamilov

  2. School of Pharmacy, University of Connecticut, Storrs, CT, USA

    Matthew J. Staid

  3. Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, CT, USA

    Brian J. Aneskievich

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  1. Rambon Shamilov
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Correspondence to Brian J. Aneskievich .

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  1. Ottawa, ON, Canada

    Kursad Turksen

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Shamilov, R., Staid, M.J., Aneskievich, B.J. (2019). In Silico and In Vitro Considerations of Keratinocyte Nuclear Receptor Protein Structural Order for Improving Experimental Analysis. In: Turksen, K. (eds) Epidermal Cells. Methods in Molecular Biology, vol 2109. Humana, New York, NY. https://doi.org/10.1007/7651_2019_240

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  • DOI: https://doi.org/10.1007/7651_2019_240

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