16 Molecular Modeling Method Applications …
331
32. ´
Sled´ z P, Caflisch A2 (2018) Protein structure-based drug design: from docking to molecular
dynamics. Curr Opin Struct Biol 48:93–102
33. Hong H, Tong W, Fang H, Shi L, Xie Q, Wu J, Perkins R, Walker JD, Branham W, Sheehan
DM (2002) Prediction of estrogen receptor binding for 58,000 chemicals using an integrated
system of a tree-based model with structural alerts. Environ Health Perspect 110(1):29–36
34. Li JZ, Gramatica P (2010) Classification and virtual screening of androgen receptor antagonists. J Chem Inf Model 50(5):861–874
35. Li F, Chen JW, Wang ZJ, Li J, Qiao XL (2009) Determination and prediction of xenoestrogens
by recombinant yeast-based assay and QSAR. Chemosphere 74(9):1152–1157
36. Yu H, Wondrousch D, Li F, Chen J, Lin H, Ji L (2015) In silico investigation of the thyroid hormone activity of hydroxylated polybrominated diphenyl ethers. Chem Res Toxicol
28(8):1538–1545
37. Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov
A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E,
Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko
IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti
O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg
SA, Slavov S, Hu X, Judson RS (2016) CERAPP: collaborative estrogen receptor activity
prediction project. Environ Health Perspect 124(7):1023–1033
38. Kleinstreuer NC, Ceger P, Watt ED, Martin M, Houck K, Browne P, Thomas RS, Casey WM,
Dix DJ, Allen D, Sakamuru S, Xia M, Huang R, Judson R (2017) Development and validation
of a computational model for androgen receptor activity. Chem Res Toxicol 30(4):946–964
39. Yin C, Yang X, Wei M, Liu H (2017) Predictive models for identifying the binding activity
of structurally diverse chemicals to human pregnane X receptor. Environ Sci Pollut Res
24(24):20063–20071
40. Papa E, Kovarich S, Gramatica P (2013) QSAR prediction of the competitive interaction
of emerging halogenated pollutants with human transthyretin. SAR QSAR Environ Res
24(4):333–349
41. Liu H, Yang X, Lu R (2016) Development of classification model and QSAR model for
predicting binding affinity of endocrine disrupting chemicals to human sex hormone-binding
globulin. Chemosphere 156:1–7
42. Liu H, Yang X, Yin C, Wei M, He X (2017) Development of predictive models for predicting
binding affinity of endocrine disrupting chemicals to fish sex hormone-binding globulin.
Ecotoxicol Environ Saf 136:46–54
43. Breen MS, Breen M, Terasaki N, Yamazaki M, Conolly RB (2010) Computational model of
steroidogenesis in human H295R cells to predict biochemical response to endocrine-active
chemicals: model development for metyrapone. Environ Health Perspect 118(2):265–272
44. Coady KK, Biever RC, Denslow ND, Gross M, Guiney PD, Holbech H, Karouna-Renier
NK, Katsiadaki I, Krueger H, Levine SL, Maack G, Williams M, Wolf JC, Ankley GT (2017)
Current limitations and recommendations to improve testing for the environmental assessment
of endocrine active substances. Integr Environ Assess Manag 13(2):302–316
45. Shen J, Xu L, Fang H, Richard AM, Bray JD, Judson RS, Zhou G, Colatsky TJ, Aungst JL,
Teng C, Harris SC, Ge W, Dai SY, Su Z, Jacobs AC, Harrouk W, Perkins R, Tong W, Hong
H (2013) EADB: an estrogenic activity database for assessing potential endocrine activity.
Toxicol Sci 135(2):277–291
46. Montes-Grajales D, Olivero-Verbel J (2015) EDCs DataBank: 3D-structure database of
endocrine disrupting chemicals. Toxicology 327:87–94
47. Rabinowitz JR, Goldsmith MR, Little SB, Pasquinelli MA (2008) Computational molecular modeling for evaluating the toxicity of environmental chemicals: prioritizing bioassay
requirements. Environ Health Perspect 116(5):573–577
48. Chen QC, Tan H, Yu H, Shi W (2018) Activation of steroid hormone receptors: shed light on
the in silico evaluation of endocrine disrupting chemicals. Sci Total Environ 631–632:27–39
49. Burley SK, Berman HM, Christie C, Duarte JM, Feng Z, Westbrook J, Young J, Zardecki
C (2018) RCSB protein data bank: sustaining a living digital data resource that enables
breakthroughs in scientific research and biomedical education. Protein Sci 27(1):316–330
331
32. ´
Sled´ z P, Caflisch A2 (2018) Protein structure-based drug design: from docking to molecular
dynamics. Curr Opin Struct Biol 48:93–102
33. Hong H, Tong W, Fang H, Shi L, Xie Q, Wu J, Perkins R, Walker JD, Branham W, Sheehan
DM (2002) Prediction of estrogen receptor binding for 58,000 chemicals using an integrated
system of a tree-based model with structural alerts. Environ Health Perspect 110(1):29–36
34. Li JZ, Gramatica P (2010) Classification and virtual screening of androgen receptor antagonists. J Chem Inf Model 50(5):861–874
35. Li F, Chen JW, Wang ZJ, Li J, Qiao XL (2009) Determination and prediction of xenoestrogens
by recombinant yeast-based assay and QSAR. Chemosphere 74(9):1152–1157
36. Yu H, Wondrousch D, Li F, Chen J, Lin H, Ji L (2015) In silico investigation of the thyroid hormone activity of hydroxylated polybrominated diphenyl ethers. Chem Res Toxicol
28(8):1538–1545
37. Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov
A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E,
Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko
IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti
O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg
SA, Slavov S, Hu X, Judson RS (2016) CERAPP: collaborative estrogen receptor activity
prediction project. Environ Health Perspect 124(7):1023–1033
38. Kleinstreuer NC, Ceger P, Watt ED, Martin M, Houck K, Browne P, Thomas RS, Casey WM,
Dix DJ, Allen D, Sakamuru S, Xia M, Huang R, Judson R (2017) Development and validation
of a computational model for androgen receptor activity. Chem Res Toxicol 30(4):946–964
39. Yin C, Yang X, Wei M, Liu H (2017) Predictive models for identifying the binding activity
of structurally diverse chemicals to human pregnane X receptor. Environ Sci Pollut Res
24(24):20063–20071
40. Papa E, Kovarich S, Gramatica P (2013) QSAR prediction of the competitive interaction
of emerging halogenated pollutants with human transthyretin. SAR QSAR Environ Res
24(4):333–349
41. Liu H, Yang X, Lu R (2016) Development of classification model and QSAR model for
predicting binding affinity of endocrine disrupting chemicals to human sex hormone-binding
globulin. Chemosphere 156:1–7
42. Liu H, Yang X, Yin C, Wei M, He X (2017) Development of predictive models for predicting
binding affinity of endocrine disrupting chemicals to fish sex hormone-binding globulin.
Ecotoxicol Environ Saf 136:46–54
43. Breen MS, Breen M, Terasaki N, Yamazaki M, Conolly RB (2010) Computational model of
steroidogenesis in human H295R cells to predict biochemical response to endocrine-active
chemicals: model development for metyrapone. Environ Health Perspect 118(2):265–272
44. Coady KK, Biever RC, Denslow ND, Gross M, Guiney PD, Holbech H, Karouna-Renier
NK, Katsiadaki I, Krueger H, Levine SL, Maack G, Williams M, Wolf JC, Ankley GT (2017)
Current limitations and recommendations to improve testing for the environmental assessment
of endocrine active substances. Integr Environ Assess Manag 13(2):302–316
45. Shen J, Xu L, Fang H, Richard AM, Bray JD, Judson RS, Zhou G, Colatsky TJ, Aungst JL,
Teng C, Harris SC, Ge W, Dai SY, Su Z, Jacobs AC, Harrouk W, Perkins R, Tong W, Hong
H (2013) EADB: an estrogenic activity database for assessing potential endocrine activity.
Toxicol Sci 135(2):277–291
46. Montes-Grajales D, Olivero-Verbel J (2015) EDCs DataBank: 3D-structure database of
endocrine disrupting chemicals. Toxicology 327:87–94
47. Rabinowitz JR, Goldsmith MR, Little SB, Pasquinelli MA (2008) Computational molecular modeling for evaluating the toxicity of environmental chemicals: prioritizing bioassay
requirements. Environ Health Perspect 116(5):573–577
48. Chen QC, Tan H, Yu H, Shi W (2018) Activation of steroid hormone receptors: shed light on
the in silico evaluation of endocrine disrupting chemicals. Sci Total Environ 631–632:27–39
49. Burley SK, Berman HM, Christie C, Duarte JM, Feng Z, Westbrook J, Young J, Zardecki
C (2018) RCSB protein data bank: sustaining a living digital data resource that enables
breakthroughs in scientific research and biomedical education. Protein Sci 27(1):316–330