메뉴 건너뛰기




Volumn 929, Issue , 2012, Pages 93-138

Prediction of physicochemical properties

Author keywords

Aqueous solubility; Boiling point; Henry's law constant; Melting point; Partition coefficient; Physicochemical properties; pKa; Prediction; Prediction software; QSPR; QSPR guidelines; Quantitative structure property relationships; Vapor pressure

Indexed keywords

ARTICLE; COMPUTER PROGRAM; MELTING POINT; PHYSICAL CHEMISTRY; PRACTICE GUIDELINE; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; SOLUBILITY; VAPOR PRESSURE;

EID: 84934435781     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-62703-50-2_6     Document Type: Article
Times cited : (11)

References (247)
  • 1
    • 72449198009 scopus 로고    scopus 로고
    • Improving compound quality through in vitro and in silico profiling
    • van de Waterbeemd H (2009) Improving compound quality through in vitro and in silico profiling. Chem Biodivers 6:1760-1766
    • (2009) Chem Biodivers , vol.6 , pp. 1760-1766
    • Van De Waterbeemd, H.1
  • 2
    • 8344262895 scopus 로고    scopus 로고
    • Calculation of physicochemical properties
    • Cronin MTD, Livingstone DJ (eds) CRC, Boca Raton, FL
    • Cronin MTD, Livingstone DJ (2004) Calculation of physicochemical properties. In: Cronin MTD, Livingstone DJ (eds) Predicting chemical toxicity and fate. CRC, Boca Raton, FL, pp 31-40
    • (2004) Predicting Chemical Toxicity and Fate , pp. 31-40
    • Cronin, M.T.D.1    Livingstone, D.J.2
  • 3
    • 33845961644 scopus 로고    scopus 로고
    • Good practice in physicochemical property prediction
    • Cronin MTD, Livingstone DJ (eds) CRC, Boca Raton, FL
    • Fisk PR, McLaughlin L, Wildey RJ (2004) Good practice in physicochemical property prediction. In: Cronin MTD, Livingstone DJ (eds) Predicting chemical toxicity and fate. CRC, Boca Raton, FL, pp 41-59
    • (2004) Predicting Chemical Toxicity and Fate , pp. 41-59
    • Fisk, P.R.1    McLaughlin, L.2    Wildey, R.J.3
  • 4
    • 84897548839 scopus 로고    scopus 로고
    • Calculation of physic-chemical and environmental fate properties
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Webb TH, Morlacci LA (2010) Calculation of physic-chemical and environmental fate properties. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 118-147
    • (2010) Silico Toxicology: Principles and Applications , pp. 118-147
    • Webb, T.H.1    Morlacci, L.A.2
  • 5
    • 8344268393 scopus 로고    scopus 로고
    • QSAR modeling of bioaccumulation
    • Cronin MTD, Livingstone DJ (eds) CRC, Boca Raton, FL
    • Dearden JC (2004) QSAR modeling of bioaccumulation. In: Cronin MTD, Livingstone DJ (eds) Predicting chemical toxicity and fate. CRC, Boca Raton, FL, pp 333-355
    • (2004) Predicting Chemical Toxicity and Fate , pp. 333-355
    • Dearden, J.C.1
  • 6
    • 34147177383 scopus 로고    scopus 로고
    • QSAR modeling of soil sorption
    • Cronin MTD, Livingstone DJ (eds) CRC, Boca Raton, FL
    • Dearden JC (2004) QSAR modeling of soil sorption. In: Cronin MTD, Livingstone DJ (eds) Predicting chemical toxicity and fate. CRC, Boca Raton, FL, pp 357-371
    • (2004) Predicting Chemical Toxicity and Fate , pp. 357-371
    • Dearden, J.C.1
  • 7
    • 57049085196 scopus 로고    scopus 로고
    • Predicting fate-related physicochemical properties
    • van Leeuwen CJ, Vermeire TG (eds) 2nd edn. Springer, Dordrecht
    • Schuurmann G, Ebert R-U, Nendza M et al (2007) Predicting fate-related physicochemical properties. In: van Leeuwen CJ, Vermeire TG (eds) Risk assessment of chemicals: an introduction, 2nd edn. Springer, Dordrecht, pp 375-426
    • (2007) Risk Assessment of Chemicals: An Introduction , pp. 375-426
    • Schuurmann, G.1    Ebert, R.-U.2    Nendza, M.3
  • 8
    • 0027982335 scopus 로고
    • Hydrogen bonding. 32. An analysis of water-octanol and water-cyclohexane partitioning and the Dlog P parameter of Seiler
    • Abraham MH, Chadha HS, Mitchell RC (1994) Hydrogen bonding. 32. An analysis of water-octanol and water-cyclohexane partitioning and the Dlog P parameter of Seiler. J Pharm Sci 83:1085-1100
    • (1994) J Pharm Sci , vol.83 , pp. 1085-1100
    • Abraham, M.H.1    Chadha, H.S.2    Mitchell, R.C.3
  • 9
    • 62849112750 scopus 로고    scopus 로고
    • Calculation of molecular lipophilicity: State-of-the-art and comparison of log P methods on more than 96,000 compounds
    • Mannhold R, Poda GI, Ostermann C et al (2009) Calculation of molecular lipophilicity: state-of-the-art and comparison of log P methods on more than 96,000 compounds. J Pharm Sci 98:861-893
    • (2009) J Pharm Sci , vol.98 , pp. 861-893
    • Mannhold, R.1    Poda, G.I.2    Ostermann, C.3
  • 10
    • 33846891907 scopus 로고    scopus 로고
    • In silico prediction of aqueous solubility
    • Dearden JC (2006) In silico prediction of aqueous solubility. Exp Opin Drug Discov 1:31-52
    • (2006) Exp Opin Drug Discov , vol.1 , pp. 31-52
    • Dearden, J.C.1
  • 11
    • 8344277344 scopus 로고    scopus 로고
    • Building QSAR models: A practical guide
    • Cronin MTD, Livingstone DJ (eds) CRC, Boca Raton, FL
    • Livingstone DJ (2004) Building QSAR models: a practical guide. In: Cronin MTD, Livingstone DJ (eds) Predicting chemical toxicity and fate. CRC, Boca Raton, FL, pp 151-170
    • (2004) Predicting Chemical Toxicity and Fate , pp. 151-170
    • Livingstone, D.J.1
  • 12
    • 84934444533 scopus 로고    scopus 로고
    • SMILES: www.daylight.com/dayhtml-tutorials/languages/smiles/index.html
    • SMILES
  • 13
    • 84862697374 scopus 로고    scopus 로고
    • Data quality assessment for in silico methods: A survey of approaches and needs
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Nendza M, Aldenberg T, Benfenati E et al (2010) Data quality assessment for in silico methods: a survey of approaches and needs. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 59-117
    • (2010) Silico Toxicology: Principles and Applications , pp. 59-117
    • Nendza, M.1    Aldenberg, T.2    Benfenati, E.3
  • 14
    • 33645028278 scopus 로고    scopus 로고
    • On selection of training and test sets for the development of predictive QSAR models
    • Leonard JT, Roy K (2006) On selection of training and test sets for the development of predictive QSAR models. QSAR Comb Sci 25:235-251
    • (2006) QSAR Comb Sci , vol.25 , pp. 235-251
    • Leonard, J.T.1    Roy, K.2
  • 15
    • 0042355453 scopus 로고    scopus 로고
    • Rational selection of training and test sets for the development of validated QSAR models
    • Golbraikh A, Shen M, Xiao Z et al (2003) Rational selection of training and test sets for the development of validated QSAR models. J Comput Aided Mol Des 17:241-253
    • (2003) J Comput Aided Mol des , vol.17 , pp. 241-253
    • Golbraikh, A.1    Shen, M.2    Xiao, Z.3
  • 16
    • 84880543050 scopus 로고    scopus 로고
    • Aquasol
    • Aquasol: www.pharmacy.arizona.edu/outreach/aquasol/
  • 17
    • 84880562651 scopus 로고    scopus 로고
    • Tripos
    • Tripos: www.tripos.com
  • 18
    • 84880567689 scopus 로고    scopus 로고
    • Chemical & Physical Properties Database
    • Chemical & Physical Properties Database. www.dep.state.pa.us/ physicalproperties/CPP- search.htm
  • 19
    • 84880529768 scopus 로고    scopus 로고
    • Chemical Database Service: cds.dl.ac.uk
    • Chemical Database Service: cds.dl.ac.uk
  • 20
    • 84880544691 scopus 로고    scopus 로고
    • ChemSpider
    • ChemSpider: www.chemspider.com
  • 21
    • 84880520380 scopus 로고    scopus 로고
    • Crossfire: info.crossfiredatabases.com
    • Crossfire: info.crossfiredatabases.com
  • 22
    • 84880541716 scopus 로고    scopus 로고
    • OCHEM
    • OCHEM: www.ochem.eu
  • 23
    • 84880527226 scopus 로고    scopus 로고
    • OECD eChemPortal
    • OECD eChemPortal: www.echemportal.org
  • 24
    • 84880542832 scopus 로고    scopus 로고
    • OECD QSAR Toolbox
    • OECD QSAR Toolbox: www.qsartoolbox. org
  • 25
    • 84880568056 scopus 로고    scopus 로고
    • OSHA
    • OSHA: www.osha.gov/web/dep/chemicaldata/
  • 26
    • 84880551264 scopus 로고    scopus 로고
    • PhysProp
    • PhysProp: www.syrres.com/what-we-d0/product.aspx?id?133
  • 27
    • 0242526954 scopus 로고    scopus 로고
    • Finding physical properties of chemicals: A practical guide for scientists, engineers, and librarians
    • Wagner AB (2001) Finding physical properties of chemicals: a practical guide for scientists, engineers, and librarians. Sci Technol Lib 21(3/4):27-45
    • (2001) Sci Technol Lib , vol.21 , Issue.3-4 , pp. 27-45
    • Wagner, A.B.1
  • 28
    • 73349120606 scopus 로고    scopus 로고
    • Optimizing the performance of in silico ADMET general models according to local requirements: MARS approach. Solubility estimations as case study
    • Oyarzabal J, Pastor J, Howe TJ (2009) Optimizing the performance of in silico ADMET general models according to local requirements: MARS approach. Solubility estimations as case study. J ChemInfModel 49:2837-2850
    • (2009) J ChemInfModel , vol.49 , pp. 2837-2850
    • Oyarzabal, J.1    Pastor, J.2    Howe, T.J.3
  • 30
    • 84897549384 scopus 로고    scopus 로고
    • Molecular descriptors from two-dimensional chemical structure
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Maran U, Sild S, Tulp I et al (2010) Molecular descriptors from two-dimensional chemical structure. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 148-192
    • (2010) In Silico Toxicology: Principles and Applications , pp. 148-192
    • Maran, U.1    Sild, S.2    Tulp, I.3
  • 31
    • 0035470283 scopus 로고    scopus 로고
    • Prediction of aqueous solubility of organic compounds by the general solubility equation (GSE
    • Ran YQ, Jain N, Yalkowsky SH (2001) Prediction of aqueous solubility of organic compounds by the general solubility equation (GSE). J Chem Inf Comput Sci 41: 1208-1217
    • (2001) J Chem Inf Comput Sci , vol.41 , pp. 1208-1217
    • Ran, Y.Q.1    Jain, N.2    Yalkowsky, S.H.3
  • 32
    • 84880531596 scopus 로고    scopus 로고
    • ADAPT: research.chem.psu.edu/pcjgroup/adapt.html
    • ADAPT: research.chem.psu.edu/pcjgroup/adapt.html
  • 33
    • 84880548846 scopus 로고    scopus 로고
    • Molecular Discovery
    • Molecular Discovery: www.moldiscovery.com
  • 34
    • 84880564581 scopus 로고    scopus 로고
    • SemiChem
    • SemiChem: www.semichem.com
  • 35
    • 84880521021 scopus 로고    scopus 로고
    • Biobyte
    • Biobyte: www.biobyte.com
  • 36
    • 84880547961 scopus 로고    scopus 로고
    • Accelrys
    • Accelrys: www.accelrys.com
  • 37
    • 84880525108 scopus 로고    scopus 로고
    • Dragon
    • Dragon: www.talete.mi.it/products/dragon- description.htm
  • 38
    • 84880521837 scopus 로고    scopus 로고
    • eDragon
    • eDragon: www.vcclab.org/lab/edragon/
  • 39
    • 84880559101 scopus 로고    scopus 로고
    • ChemComp
    • ChemComp: www.chemcomp.com
  • 40
    • 84880516894 scopus 로고    scopus 로고
    • EduSoft
    • EduSoft: www.edusoft-lc.com/molconn/
  • 41
    • 84880528431 scopus 로고    scopus 로고
    • vLifeSciences
    • vLifeSciences: www.vlifesciences.com
  • 43
    • 84897526793 scopus 로고    scopus 로고
    • Statistical methods for continuous measured endpoints in in silico toxicology
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Rowe PH (2010) Statistical methods for continuous measured endpoints in in silico toxicology. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 228-251
    • (2010) In Silico Toxicology: Principles and Applications , pp. 228-251
    • Rowe, P.H.1
  • 44
    • 84880522908 scopus 로고    scopus 로고
    • SimulationsPlus
    • SimulationsPlus: www.simulations-plus.com
  • 45
    • 84880519796 scopus 로고    scopus 로고
    • FQS Poland
    • FQS Poland: www.fqs.pl
  • 46
    • 84880546001 scopus 로고    scopus 로고
    • VCCLAB
    • VCCLAB: www.vcclab.org
  • 47
    • 84880535567 scopus 로고    scopus 로고
    • MSI
    • MSI: www.msi.umn.edu/sw/cerius2
  • 48
    • 84880515854 scopus 로고    scopus 로고
    • VSN International
    • VSN International: www.vsni.co.uk/software/genstat/
  • 49
    • 84880536698 scopus 로고    scopus 로고
    • MathWorks
    • MathWorks: www.mathworks.com
  • 50
    • 84880546598 scopus 로고    scopus 로고
    • Minitab
    • Minitab: www.minitab.com
  • 51
    • 84880524329 scopus 로고    scopus 로고
    • NCSS
    • NCSS: www.ncss.com
  • 52
    • 84880553867 scopus 로고    scopus 로고
    • IDBS
    • IDBS: www.idbs.com
  • 53
    • 84880536610 scopus 로고    scopus 로고
    • ProChemist: pro.chemist.online.fr
    • ProChemist: pro.chemist.online.fr
  • 54
    • 84880515617 scopus 로고    scopus 로고
    • GNU
    • GNU: www.gnu.org/software/pspp/
  • 55
    • 84880527930 scopus 로고    scopus 로고
    • SAS
    • SAS: www.sas.com
  • 56
    • 84880545660 scopus 로고    scopus 로고
    • Scigress Explorer
    • Scigress Explorer: www.scigress-explorer.software. informer.com
  • 57
    • 84880526004 scopus 로고    scopus 로고
    • SPSS
    • SPSS: www.spss.com
  • 58
    • 84880515379 scopus 로고    scopus 로고
    • StatSoft
    • StatSoft: www.statsoft.com
  • 59
    • 84880545187 scopus 로고    scopus 로고
    • Schrodinger
    • Schrodinger: www.schrodinger.com
  • 60
    • 33745821727 scopus 로고    scopus 로고
    • Can we estimate the accuracy of ADME-Tox predictions?
    • Tetko IV, Bruneau P, Mewes H-W et al (2006) Can we estimate the accuracy of ADME-Tox predictions? Drug Disc Today 11:700-707
    • (2006) Drug Disc Today , vol.11 , pp. 700-707
    • Tetko, I.V.1    Bruneau, P.2    Mewes, H.-W.3
  • 62
    • 0043132440 scopus 로고    scopus 로고
    • Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs
    • Eriksson L, Jaworska J,Worth AP et al (2003) Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ Health Perspect 111:1361-1375
    • (2003) Environ Health Perspect , vol.111 , pp. 1361-1375
    • Eriksson, L.1    Jaworska Jworth, A.P.2
  • 63
    • 0142057987 scopus 로고    scopus 로고
    • Quantitative structure-property relationships for prediction of boiling point, vapor pressure, and melting point
    • Dearden JC (2003) Quantitative structure-property relationships for prediction of boiling point, vapor pressure, and melting point. Environ Toxicol Chem 22:1696-1709
    • (2003) Environ Toxicol Chem , vol.22 , pp. 1696-1709
    • Dearden, J.C.1
  • 64
    • 0141969350 scopus 로고    scopus 로고
    • Quantitative structure-property relationships for predicting Henry?s law constant from molecular structure
    • Dearden JC, Schuurmann G (2003) Quantitative structure-property relationships for predicting Henry?s law constant from molecular structure. Environ Toxicol Chem 22:1755-1770
    • (2003) Environ Toxicol Chem , vol.22 , pp. 1755-1770
    • Dearden, J.C.1    Schuurmann, G.2
  • 65
    • 84880527514 scopus 로고    scopus 로고
    • QMRF Database: qsardb.jrc.it/qmrf/
    • QMRF Database: qsardb.jrc.it/qmrf/
  • 66
    • 84880541004 scopus 로고    scopus 로고
    • Danish QSAR Database
    • Danish QSAR Database: www.130.226.165. 14/index.html
  • 67
    • 84880561860 scopus 로고    scopus 로고
    • ACD/Labs
    • ACD/Labs: www.acdlabs.com
  • 68
    • 84880527349 scopus 로고    scopus 로고
    • ChemAxon
    • ChemAxon: www.chemaxon.com
  • 69
    • 84880561258 scopus 로고    scopus 로고
    • CambridgeSoft
    • CambridgeSoft: www.cambridgesoft.com
  • 70
    • 84880530997 scopus 로고    scopus 로고
    • UFZ
    • UFZ: www.ufz.de/index.php?en=6738
  • 71
    • 84880565484 scopus 로고    scopus 로고
    • ChemSilico
    • ChemSilico: www.chemsilico.com
  • 72
    • 84880528088 scopus 로고    scopus 로고
    • Daylight
    • Daylight: www.daylight.com
  • 73
    • 84880547113 scopus 로고    scopus 로고
    • Episuite
    • Episuite: www.epa.gov/opptintr/exposure/pubs/episuite.htm
  • 74
    • 84880563216 scopus 로고    scopus 로고
    • ChemSW
    • ChemSW: www.chemsw.com
  • 75
    • 84880557434 scopus 로고    scopus 로고
    • Molinspiration
    • Molinspiration: www.molinspiration.com
  • 76
    • 84880529652 scopus 로고    scopus 로고
    • Chemistry Database Software
    • Chemistry Database Software: www.chemdbsoft. com
  • 77
    • 84880566973 scopus 로고    scopus 로고
    • CompuDrug
    • CompuDrug: www.compudrug.com
  • 78
    • 84880542617 scopus 로고    scopus 로고
    • G & P Engineering Software
    • G & P Engineering Software. www.gpengineeringsoft.com
  • 79
    • 84880530431 scopus 로고    scopus 로고
    • MW Software
    • MW Software: www.mwsoftware.com/dragon
  • 80
    • 84880544468 scopus 로고    scopus 로고
    • ProPred
    • ProPred: www.capec.kt.dtu.dk
  • 81
    • 84880528496 scopus 로고    scopus 로고
    • SPARC: ibmlc2.chem.uga.edu/sparc
    • SPARC: ibmlc2.chem.uga.edu/sparc
  • 82
    • 84880567648 scopus 로고    scopus 로고
    • TerraBase
    • TerraBase: www.terrabase-inc.com
  • 83
    • 84880518908 scopus 로고    scopus 로고
    • Optibrium
    • Optibrium: www.optibrium.com
  • 84
    • 0022272070 scopus 로고
    • Partitioning and lipophilicity in quantitative structure-activity relationships
    • Dearden JC (1985) Partitioning and lipophilicity in quantitative structure-activity relationships. Environ Health Perspect 61:203-228
    • (1985) Environ Health Perspect , vol.61 , pp. 203-228
    • Dearden, J.C.1
  • 85
    • 34447521097 scopus 로고
    • Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients
    • Hansch C, Maloney PP, Fujita T et al (1962) Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 194:178-180
    • (1962) Nature , vol.194 , pp. 178-180
    • Hansch, C.1    Maloney, P.P.2    Fujita, T.3
  • 88
    • 85056344778 scopus 로고    scopus 로고
    • Octanol/water partition coefficients
    • Boethling RS, Mackay D (eds) Lewis, Boca Raton, FL
    • Leo A (2000) Octanol/water partition coefficients. In: Boethling RS, Mackay D (eds) Handbook of property estimation methods for chemicals. Lewis, Boca Raton, FL, pp 89-114
    • (2000) Handbook of Property Estimation Methods for Chemicals , pp. 89-114
    • Leo, A.1
  • 89
    • 0035055492 scopus 로고    scopus 로고
    • Substructure and whole molecule approaches for calculating log P
    • Mannhold R, van de Waterbeemd H (2001) Substructure and whole molecule approaches for calculating log P. Comput Aided Mol Des 15:337-354
    • (2001) Comput Aided Mol des , vol.15 , pp. 337-354
    • Mannhold, R.1    Van De Waterbeemd, H.2
  • 90
    • 0038282314 scopus 로고    scopus 로고
    • Theoretical property predictions
    • Livingstone DJ (2003) Theoretical property predictions. Curr Top Med Chem 3: 1171-1192
    • (2003) Curr Top Med Chem , vol.3 , pp. 1171-1192
    • Livingstone, D.J.1
  • 91
    • 14544278461 scopus 로고    scopus 로고
    • Recent methodologies for the estimation of n-octanol/water partition coefficients and their use in the prediction of membrane transport properties of drugs
    • Klopman G, Zhu H (2005) Recent methodologies for the estimation of n-octanol/water partition coefficients and their use in the prediction of membrane transport properties of drugs. Mini Rev Med Chem 5:127-133
    • (2005) Mini Rev Med Chem , vol.5 , pp. 127-133
    • Klopman, G.1    Zhu, H.2
  • 92
    • 33749000228 scopus 로고
    • A new substituent constant, p, derived from partition coefficients
    • Fujita T, Iwasa J, Hansch C (1964) A new substituent constant, p, derived from partition coefficients. J Am Chem Soc 86:5175-5180
    • (1964) J Am Chem Soc , vol.86 , pp. 5175-5180
    • Fujita, T.1    Iwasa, J.2    Hansch, C.3
  • 93
    • 0015755443 scopus 로고
    • Statistical analysis of a series of partition coefficients with special reference to the predictability of folding of drug molecules. Introduction of hydrophobic fragmental constants (f values)
    • Nys GG, Rekker RF (1973) Statistical analysis of a series of partition coefficients with special reference to the predictability of folding of drug molecules. Introduction of hydrophobic fragmental constants (f values). Chim Ther 8:521-535
    • (1973) Chim Ther , vol.8 , pp. 521-535
    • Nys, G.G.1    Rekker, R.F.2
  • 95
    • 0016721416 scopus 로고
    • Calculation of hydrophobic constant (log P) from p and f values
    • Leo A, Jow PYC, Silipo C et al (1975) Calculation of hydrophobic constant (log P) from p and f values. J Med Chem 18:865-868
    • (1975) J Med Chem , vol.18 , pp. 865-868
    • Leo, A.1    Jow, P.Y.C.2    Silipo, C.3
  • 96
    • 0024656378 scopus 로고
    • A new method for the estimation of partition coefficient
    • Bodor N, Gabanyi NZ, Wong C-K (1989) A new method for the estimation of partition coefficient. J Am Chem Soc 111:3783-3786
    • (1989) J Am Chem Soc , vol.111 , pp. 3783-3786
    • Bodor, N.1    Gabanyi, N.Z.2    Wong, C.-K.3
  • 97
    • 84986520724 scopus 로고
    • A computer automated structure evaluation (CASE) approach to calculation of partition coefficient
    • Klopman G, Wang S (1991) A computer automated structure evaluation (CASE) approach to calculation of partition coefficient. J Comput Chem 12:1025-1032
    • (1991) J Comput Chem , vol.12 , pp. 1025-1032
    • Klopman, G.1    Wang, S.2
  • 98
    • 84911792416 scopus 로고
    • Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships: III. Modeling hydrophobic interactions
    • Ghose AK, Pritchett A, Crippen GM (1988) Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships: III. Modeling hydrophobic interactions. J Comput Chem 9:80-90
    • (1988) J Comput Chem , vol.9 , pp. 80-90
    • Ghose, A.K.1    Pritchett, A.2    Crippen, G.M.3
  • 99
    • 42149111018 scopus 로고    scopus 로고
    • Using molecular fingerprint as descriptors in the QSPR study of lipophilicity
    • Liu R, Zhou D (2008) Using molecular fingerprint as descriptors in the QSPR study of lipophilicity. J Chem Inf Model 48:542-549
    • (2008) J Chem Inf Model , vol.48 , pp. 542-549
    • Liu, R.1    Zhou, D.2
  • 100
    • 67651249916 scopus 로고    scopus 로고
    • In silico log P prediction for a large data set with support vector machines, radial basis neural networks and multiple linear regression
    • Chen H-F (2009) In silico log P prediction for a large data set with support vector machines, radial basis neural networks and multiple linear regression. Chem Biol Drug Des 74:142-147
    • (2009) Chem Biol Drug des , vol.74 , pp. 142-147
    • Chen, H.-F.1
  • 101
    • 0035470269 scopus 로고    scopus 로고
    • Prediction of n-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indices
    • Tetko IV, Tanchuk VYu, Villa AEP (2001) Prediction of n-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indices. J Chem Inf Comput Sci 41:1407-1421
    • (2001) J Chem Inf Comput Sci , vol.41 , pp. 1407-1421
    • Tetko, I.V.1    Tanchuk, V.Yu.2    Villa, A.E.P.3
  • 103
    • 40049106872 scopus 로고    scopus 로고
    • A comparison of commercially available software for the prediction of partition coefficient
    • Ford M, Livingstone D, Dearden J et al (eds) Blackwell, Oxford
    • Dearden JC, Netzeva TI, Bibby R (2003) A comparison of commercially available software for the prediction of partition coefficient. In: Ford M, Livingstone D, Dearden J et al (eds) Designing drugs and crop protectants: processes, problems and solutions. Blackwell, Oxford, pp 168-169
    • (2003) Designing Drugs and Crop Protectants: Processes, Problems and Solutions , pp. 168-169
    • Dearden, J.C.1    Netzeva, T.I.2    Bibby, R.3
  • 104
    • 33846811529 scopus 로고    scopus 로고
    • Comparison of predictivities of log P calculation models based on experimental data for 134 simple organic compounds
    • Sakuratani Y, Kasai K, Noguchi Y et al (2007) Comparison of predictivities of log P calculation models based on experimental data for 134 simple organic compounds. QSAR Comb Sci 26:109-116
    • (2007) QSAR Comb Sci , vol.26 , pp. 109-116
    • Sakuratani, Y.1    Kasai, K.2    Noguchi, Y.3
  • 105
    • 84934441703 scopus 로고    scopus 로고
    • COSMOlogic: www.cosmologic.de
    • COSMOlogic
  • 106
    • 4043140704 scopus 로고    scopus 로고
    • "In silico" design of new uranyl extractants based on phosphoryl-containing podands: QSPR studies, generation and screening of virtual combinatorial library, and experimental tests
    • Varnek A, Fourches D, Solov?ev VP et al (2004) "In silico" design of new uranyl extractants based on phosphoryl-containing podands: QSPR studies, generation and screening of virtual combinatorial library, and experimental tests. J Chem Inf Comput Sci 44:1365-1382
    • (2004) J Chem Inf Comput Sci , vol.44 , pp. 1365-1382
    • Varnek, A.1    Fourches, D.2    Solovev, V.P.3
  • 107
    • 0029622330 scopus 로고
    • QSAR study of the toxicity of nitrobenzenes to Tetrahymena pyriformis
    • Dearden JC, Cronin MTD, Schultz TW et al (1995) QSAR study of the toxicity of nitrobenzenes to Tetrahymena pyriformis. Quant Struct Act Relat 14:427-432
    • (1995) Quant Struct Act Relat , vol.14 , pp. 427-432
    • Dearden, J.C.1    Cronin, M.T.D.2    Schultz, T.W.3
  • 108
    • 0001011568 scopus 로고    scopus 로고
    • QSPR studies on vapor pressure, aqueous solubility, and the prediction of air-water partition coefficients
    • Katritzky AR, Wang Y, Sild S et al (1998) QSPR studies on vapor pressure, aqueous solubility, and the prediction of air-water partition coefficients. J Chem Inf Comput Sci 38:720-725
    • (1998) J Chem Inf Comput Sci , vol.38 , pp. 720-725
    • Katritzky, A.R.1    Wang, Y.2    Sild, S.3
  • 112
    • 33747183101 scopus 로고    scopus 로고
    • Recent progress in the computational prediction of aqueous solubility and absorption
    • Johnson SR, Zheng W (2006) Recent progress in the computational prediction of aqueous solubility and absorption. AAPS J 8: E27-E40
    • (2006) AAPS J , vol.8
    • Johnson, S.R.1    Zheng, W.2
  • 114
    • 0001085722 scopus 로고
    • The linear free energy relationship between partition coefficients and aqueous solubility of organic liquids
    • Hansch C, Quinlan JE, Lawrence GL (1968) The linear free energy relationship between partition coefficients and aqueous solubility of organic liquids. J Org Chem 33:347-350
    • (1968) J Org Chem , vol.33 , pp. 347-350
    • Hansch, C.1    Quinlan, J.E.2    Lawrence, G.L.3
  • 115
    • 0019166075 scopus 로고
    • Solubility and partitioning I: Solubility of nonelectrolytes in water
    • Yalkowsky SH, Valvani SC (1980) Solubility and partitioning I: solubility of nonelectrolytes in water. J Pharm Sci 69:912-922
    • (1980) J Pharm Sci , vol.69 , pp. 912-922
    • Yalkowsky, S.H.1    Valvani, S.C.2
  • 116
    • 39449138204 scopus 로고    scopus 로고
    • Why are some properties more difficult to predict than others? A study of QSPR models of solubility, melting point, and log P
    • Hughes LD, Palmer DS, Nigsch F et al (2008) Why are some properties more difficult to predict than others? A study of QSPR models of solubility, melting point, and log P. J Chem Inf Model 48:220-232
    • (2008) J Chem Inf Model , vol.48 , pp. 220-232
    • Hughes, L.D.1    Palmer, D.S.2    Nigsch, F.3
  • 117
    • 0038745774 scopus 로고    scopus 로고
    • Estimation of aqueous solubility by the general solubility equation (GSE) the easy way
    • Sanghvi T, Jain N, Yang G et al (2003) Estimation of aqueous solubility by the general solubility equation (GSE) the easy way. QSAR Comb Sci 22:258-262
    • (2003) QSAR Comb Sci , vol.22 , pp. 258-262
    • Sanghvi, T.1    Jain, N.2    Yang, G.3
  • 118
    • 0032841864 scopus 로고    scopus 로고
    • The correlation and prediction of the solubility of compounds in water using an amended solvation energy relationship
    • Abraham MH, Le J (1999) The correlation and prediction of the solubility of compounds in water using an amended solvation energy relationship. J Pharm Sci 88:868-880
    • (1999) J Pharm Sci , vol.88 , pp. 868-880
    • Abraham, M.H.1    Le, J.2
  • 119
    • 6444225736 scopus 로고    scopus 로고
    • Prediction of aqueous solubility based on large datasets using several QSPR models utilizing topological structure representation
    • Votano J.R., Parham M, Hall LH et al (2004) Prediction of aqueous solubility based on large datasets using several QSPR models utilizing topological structure representation. Chem Biodivers 11:1829-1841
    • (2004) Chem Biodivers , vol.11 , pp. 1829-1841
    • Votano, J.R.1    Parham, M.2    Hall, L.H.3
  • 120
    • 8344278626 scopus 로고    scopus 로고
    • Analysis of water solubility data on the basis of HYBOT descriptors. Part 3. Solubility of solid neutral chemicals and drugs
    • Raevsky OA, Raevskaja OE, Schaper K-J (2004) Analysis of water solubility data on the basis of HYBOT descriptors. Part 3. Solubility of solid neutral chemicals and drugs. QSAR Comb Sci 23:327-343
    • (2004) QSAR Comb Sci , vol.23 , pp. 327-343
    • Raevsky, O.A.1    Raevskaja, O.E.2    Schaper, K.-J.3
  • 121
    • 0035273557 scopus 로고    scopus 로고
    • Estimation of the aqueous solubility of organic molecules by the group contribution approach
    • Klopman G, Zhu H (2001) Estimation of the aqueous solubility of organic molecules by the group contribution approach. J Chem Inf Comput Sci 41:439-445
    • (2001) J Chem Inf Comput Sci , vol.41 , pp. 439-445
    • Klopman, G.1    Zhu, H.2
  • 122
    • 33846856225 scopus 로고    scopus 로고
    • Random forest models to predict aqueous solubility
    • Palmer DS, O?Boyle NM, Glen RC et al (2007) Random forest models to predict aqueous solubility. J Chem Inf Model 47: 150-158
    • (2007) J Chem Inf Model , vol.47 , pp. 150-158
    • Palmer, D.S.1    Oboyle, N.M.2    Glen, R.C.3
  • 123
    • 0345548663 scopus 로고    scopus 로고
    • Support vector machines for the estimation of aqueous solubility
    • Lind P, Maltseva T (2003) Support vector machines for the estimation of aqueous solubility. J Chem Inf Comput Sci 43:1855-1859
    • (2003) J Chem Inf Comput Sci , vol.43 , pp. 1855-1859
    • Lind, P.1    Maltseva, T.2
  • 124
    • 50649105956 scopus 로고    scopus 로고
    • New QSPR study for the prediction of aqueous solubility of drug-like compounds
    • Duchowicz PR, Talevi A, Bruno-Blanch LE et al (2008) New QSPR study for the prediction of aqueous solubility of drug-like compounds. Bioorg Med Chem 16:7944-7955
    • (2008) Bioorg Med Chem , vol.16 , pp. 7944-7955
    • Duchowicz, P.R.1    Talevi, A.2    Bruno-Blanch, L.E.3
  • 125
    • 67649663895 scopus 로고    scopus 로고
    • QSPR studies on aqueous solubilities of drug-like compounds
    • Duchowicz PR, Castro EA (2009) QSPR studies on aqueous solubilities of drug-like compounds. Int J Mol Sci 10:2558-2577
    • (2009) Int J Mol Sci , vol.10 , pp. 2558-2577
    • Duchowicz, P.R.1    Castro, E.A.2
  • 126
    • 47349119393 scopus 로고    scopus 로고
    • Prediction of drug solubility from molecular structure using a drug-like training set
    • Huuskonen J, Livingstone DJ, Manallack DT (2008) Prediction of drug solubility from molecular structure using a drug-like training set. SAR QSAR Environ Res 19:191-212
    • (2008) SAR QSAR Environ Res , vol.19 , pp. 191-212
    • Huuskonen, J.1    Livingstone, D.J.2    Manallack, D.T.3
  • 127
    • 34250682678 scopus 로고    scopus 로고
    • QSPR study on the aqueous solubility (lgS(w)) and n-octanol/water partition coefficients (lgK(ow)) of polychlorinated dibenzo-pdioxins (PCDDs)
    • Yang G-Y, Yu J, Wang Z-Y et al (2007) QSPR study on the aqueous solubility (lgS(w)) and n-octanol/water partition coefficients (lgK(ow)) of polychlorinated dibenzo-pdioxins (PCDDs). QSAR Comb Sci 26: 352-357
    • (2007) QSAR Comb Sci , vol.26 , pp. 352-357
    • Yang, G.-Y.1    Yu, J.2    Wang, Z.-Y.3
  • 128
    • 34250631831 scopus 로고    scopus 로고
    • Estimation of aqueous solubility (lgS(w)) of all polychlorinated biphenyl (PCB) congeners by density function theory and position of Cl substitution (N-PCS) method
    • Wei X-Y, Ge Z-G, Wang Z-Y et al (2007) Estimation of aqueous solubility (lgS(w)) of all polychlorinated biphenyl (PCB) congeners by density function theory and position of Cl substitution (N-PCS) method. Chinese J Struct Chem 26:519-528
    • (2007) Chinese J Struct Chem , vol.26 , pp. 519-528
    • Wei, X.-Y.1    Ge, Z.-G.2    Wang, Z.-Y.3
  • 129
    • 40049106872 scopus 로고    scopus 로고
    • A comparison of commercially available software for the prediction of aqueous solubility
    • Ford M, Livingstone D, Dearden J et al (eds) Blackwell, Oxford
    • Dearden JC, Netzeva TI, Bibby R (2003) A comparison of commercially available software for the prediction of aqueous solubility. In: Ford M, Livingstone D, Dearden J et al (eds) Designing drugs and crop protectants: processes, problems and solutions. Blackwell, Oxford, pp 169-171
    • (2003) Designing Drugs and Crop Protectants: Processes, Problems and Solutions , pp. 169-171
    • Dearden, J.C.1    Netzeva, T.I.2    Bibby, R.3
  • 130
    • 84880567999 scopus 로고    scopus 로고
    • Unpublished information
    • Dearden JC. Unpublished information
    • Dearden, J.C.1
  • 131
    • 84965447002 scopus 로고
    • Acid dissociation constant
    • Lyman WJ, Reehl WF, Rosenblatt DH (eds) American Chemical Society, Washington, DC
    • Harris JC, Hayes MJ (1990) Acid dissociation constant. In: Lyman WJ, Reehl WF, Rosenblatt DH (eds) Handbook of chemical property estimation methods. American Chemical Society, Washington, DC, pp 6.1-6.28
    • (1990) Handbook of Chemical Property Estimation Methods , pp. 601-628
    • Harris, J.C.1    Hayes, M.J.2
  • 132
    • 33751259959 scopus 로고    scopus 로고
    • Computational determination of aqueous pKa values of protonated benzimidazoles (Part 2
    • Brown TN, Mora-Diez N (2006) Computational determination of aqueous pKa values of protonated benzimidazoles (Part 2). J Phys Chem B 110:20546-20554
    • (2006) J Phys Chem B , vol.110 , pp. 20546-20554
    • Brown, T.N.1    Mora-Diez, N.2
  • 133
    • 0036681979 scopus 로고    scopus 로고
    • Structure-activity relationships in 4-aminoquinoline antiplasmodials. The role of the group at the 7-position
    • Kaschula CH, Egan TJ, Hunter R et al (2002) Structure-activity relationships in 4- aminoquinoline antiplasmodials. The role of the group at the 7-position. J Med Chem 45:3531-3539
    • (2002) J Med Chem , vol.45 , pp. 3531-3539
    • Kaschula, C.H.1    Egan, T.J.2    Hunter, R.3
  • 134
    • 5444239254 scopus 로고    scopus 로고
    • Computational determination of pK(a) values. A comparison of different theoretical approaches and a novel procedure
    • Soriano E, Cerdan S, Ballesteros P (2004) Computational determination of pK(a) values. A comparison of different theoretical approaches and a novel procedure. J Mol Struct Theochem 684:121-128
    • (2004) J Mol Struct Theochem , vol.684 , pp. 121-128
    • Soriano, E.1    Cerdan, S.2    Ballesteros, P.3
  • 135
    • 84986435688 scopus 로고
    • Application of the multiple computer automated structure evaluation methodology to a quantitative structure-activity relationship study of acidity
    • Klopman G, Fercu D (1994) Application of the multiple computer automated structure evaluation methodology to a quantitative structure-activity relationship study of acidity. J Comput Chem 15:1041-1050
    • (1994) J Comput Chem , vol.15 , pp. 1041-1050
    • Klopman, G.1    Fercu, D.2
  • 136
    • 0242540027 scopus 로고    scopus 로고
    • First principles calculations of aqueous pK(a) values for organic and inorganic acids using COSMO-RS reveal an inconsistency in the slope of the pK(a) scale
    • Klamt A, Eckert F, Diedenhofen M et al (2003) First principles calculations of aqueous pK(a) values for organic and inorganic acids using COSMO-RS reveal an inconsistency in the slope of the pK(a) scale. J Phys Chem A 107:9380-9386
    • (2003) J Phys Chem A , vol.107 , pp. 9380-9386
    • Klamt, A.1    Eckert, F.2    Diedenhofen, M.3
  • 137
    • 33644797789 scopus 로고    scopus 로고
    • Accurate prediction of basicity in aqueous solution with COSMORS
    • Eckert F, Klamt A (2006) Accurate prediction of basicity in aqueous solution with COSMORS. J Comput Chem 27:11-19
    • (2006) J Comput Chem , vol.27 , pp. 11-19
    • Eckert, F.1    Klamt, A.2
  • 138
    • 56449089334 scopus 로고    scopus 로고
    • PKa prediction of monoprotic small molecules the SMARTS way
    • Lee AC, Yu J-Y, Crippen GM (2008) pKa prediction of monoprotic small molecules the SMARTS way. J Chem Inf Model 48:2042-2053
    • (2008) J Chem Inf Model , vol.48 , pp. 2042-2053
    • Lee, A.C.1    Yu, J.-Y.2    Crippen, G.M.3
  • 139
    • 37249023309 scopus 로고    scopus 로고
    • New and original pKa prediction method using GRID molecular interaction fields
    • Milletti F, Storchi L, Sforna G et al (2007) New and original pKa prediction method using GRID molecular interaction fields. J Chem Inf Model 47:2172-2181
    • (2007) J Chem Inf Model , vol.47 , pp. 2172-2181
    • Milletti, F.1    Storchi, L.2    Sforna, G.3
  • 140
    • 72449138105 scopus 로고    scopus 로고
    • In silico prediction and ADME profiling
    • Cruciani G, Milletti F, Storchi L et al (2009) In silico prediction and ADME profiling. Chem Biodivers 6:1812-1821
    • (2009) Chem Biodivers , vol.6 , pp. 1812-1821
    • Cruciani, G.1    Milletti, F.2    Storchi, L.3
  • 142
    • 0030928584 scopus 로고    scopus 로고
    • Prediction of distribution coefficient from structure 2. Validation of PrologD, an expert system
    • Tsantili-Kakoulidou A, Panderi I, Csizmadia F et al (1997) Prediction of distribution coefficient from structure 2. Validation of PrologD, an expert system. J Pharm Sci 86: 1173-1179
    • (1997) J Pharm Sci , vol.86 , pp. 1173-1179
    • Tsantili-Kakoulidou, A.1    Panderi, I.2    Csizmadia, F.3
  • 143
    • 0028889384 scopus 로고
    • A rigorous test for SPARC?s chemical reactivity models: Estimation of more than 4300 ionisation pKa?s
    • Hilal SH, Karickhoff SW, Carreira LA (1995) A rigorous test for SPARC?s chemical reactivity models: estimation of more than 4300 ionisation pKa?s. Quant Struct Act Relat 14: 348-355
    • (1995) Quant Struct Act Relat , vol.14 , pp. 348-355
    • Hilal, S.H.1    Karickhoff, S.W.2    Carreira, L.A.3
  • 144
    • 34548166862 scopus 로고    scopus 로고
    • In silico prediction of ionization constants of drugs
    • Lee PH, Ayyampalayam SN, Carreira LA et al (2007) In silico prediction of ionization constants of drugs. Mol Pharm 4:498-512
    • (2007) Mol Pharm , vol.4 , pp. 498-512
    • Lee, P.H.1    Ayyampalayam, S.N.2    Carreira, L.A.3
  • 145
    • 33646271333 scopus 로고    scopus 로고
    • Model selection based on structural similarity- method description and application to water solubility prediction
    • Kuhne R, Ebert R-U, Schuurmann G (2006) Model selection based on structural similarity- method description and application to water solubility prediction. J Chem Inf Model 46:636-641
    • (2006) J Chem Inf Model , vol.46 , pp. 636-641
    • Kuhne, R.1    Ebert, R.-U.2    Schuurmann, G.3
  • 146
    • 40049107461 scopus 로고    scopus 로고
    • A comparison of commercially available software for the prediction of pKa
    • Dearden JC, Cronin MTD, Lappin DC (2007) A comparison of commercially available software for the prediction of pKa. J Pharm Pharmacol 59(suppl 1):A-7
    • (2007) J Pharm Pharmacol , vol.59 , Issue.SUPPL 1
    • Dearden, J.C.1    Cronin, M.T.D.2    Lappin, D.C.3
  • 147
    • 73349118457 scopus 로고    scopus 로고
    • Comparison of nine programs predicting pKa values of pharmaceutical substances
    • Liao C, Nicklaus MC (2009) Comparison of nine programs predicting pKa values of pharmaceutical substances. J Chem Inf Model 49:2801-2812
    • (2009) J Chem Inf Model , vol.49 , pp. 2801-2812
    • Liao, C.1    Nicklaus, M.C.2
  • 148
    • 34748840224 scopus 로고    scopus 로고
    • Benchmarking and validating algorithms that estimate pKa values of drugs based on their molecular structure
    • MelounM, Bordovska S (2007) Benchmarking and validating algorithms that estimate pKa values of drugs based on their molecular structure. Anal Bioanal Chem 389:1267-1281
    • (2007) Anal Bioanal Chem , vol.389 , pp. 1267-1281
    • Meloun, M.1    Bordovska, S.2
  • 149
    • 75249101196 scopus 로고    scopus 로고
    • Comparative evaluation of in silico pKa prediction tools on the Gold Standard dataset
    • Balogh GT, Gyarmati B, Nagy B et al (2009) Comparative evaluation of in silico pKa prediction tools on the Gold Standard dataset. QSAR Comb Sci 28:1148-1155
    • (2009) QSAR Comb Sci , vol.28 , pp. 1148-1155
    • Balogh, G.T.1    Gyarmati, B.2    Nagy, B.3
  • 150
    • 77951983882 scopus 로고    scopus 로고
    • Evaluation of pKa estimation methods on 211 druglike compounds
    • Manchester J,Walkup G, Rivin O et al (2010) Evaluation of pKa estimation methods on 211 druglike compounds. J Chem Inf Model 50:565-571
    • (2010) J Chem Inf Model , vol.50 , pp. 565-571
    • Manchester, J.1    Walkup, G.2    Rivin, O.3
  • 151
    • 0026356342 scopus 로고
    • The QSAR prediction of melting point, a property of environmental relevance
    • Dearden JC (1991) The QSAR prediction of melting point, a property of environmental relevance. Sci Total Environ 109(110):59-68
    • (1991) Sci Total Environ , vol.109 , Issue.110 , pp. 59-68
    • Dearden, J.C.1
  • 153
    • 0003086204 scopus 로고    scopus 로고
    • The prediction of melting point
    • Charton M, Charton B (eds) JAI Press, Stamford, CT
    • Dearden JC (1999) The prediction of melting point. In: Charton M, Charton B (eds) Advances in quantitative structure-property relationships, vol 2. JAI Press, Stamford, CT, pp 127-175
    • (1999) Advances in Quantitative Structure-property Relationships , vol.2 , pp. 127-175
    • Dearden, J.C.1
  • 155
    • 11644304895 scopus 로고
    • On melting point and boiling point as related to composition
    • Mills EJ (1884) On melting point and boiling point as related to composition. Phil Mag 17:173-187
    • (1884) Phil Mag , vol.17 , pp. 173-187
    • Mills, E.J.1
  • 156
    • 0001700161 scopus 로고    scopus 로고
    • Prediction of melting points for the substituted benzenes
    • Katritzky AR, Maran U, Karelson M et al (1997) Prediction of melting points for the substituted benzenes. J Chem Inf Comput Sci 37:913-919
    • (1997) J Chem Inf Comput Sci , vol.37 , pp. 913-919
    • Katritzky, A.R.1    Maran, U.2    Karelson, M.3
  • 157
    • 0025604899 scopus 로고
    • Estimation of aqueous solubility and melting point of PCB congeners
    • Abramowitz R, Yalkowsky SH (1990) Estimation of aqueous solubility and melting point of PCB congeners. Chemosphere 21:1221-1229
    • (1990) Chemosphere , vol.21 , pp. 1221-1229
    • Abramowitz, R.1    Yalkowsky, S.H.2
  • 158
    • 0002988016 scopus 로고
    • Estimation of melting point of flexible molecules: Aliphatic hydrocarbons
    • Tsakanikas PD, Yalkowsky SH (1988) Estimation of melting point of flexible molecules: aliphatic hydrocarbons. Toxicol Environ Chem 17:19-33
    • (1988) Toxicol Environ Chem , vol.17 , pp. 19-33
    • Tsakanikas, P.D.1    Yalkowsky, S.H.2
  • 159
    • 0025169150 scopus 로고
    • Melting point, boiling point and symmetry
    • Abramowitz R, Yalkowsky SH (1990) Melting point, boiling point and symmetry. Pharm Res 7:942-947
    • (1990) Pharm Res , vol.7 , pp. 942-947
    • Abramowitz, R.1    Yalkowsky, S.H.2
  • 160
    • 0033200852 scopus 로고    scopus 로고
    • A combined group contribution and molecular geometry approach for predicting melting points of aliphatic compounds
    • Zhao L, Yalkowsky SH (1999) A combined group contribution and molecular geometry approach for predicting melting points of aliphatic compounds. Ind Eng Chem Res 38:3581-3584
    • (1999) Ind Eng Chem Res , vol.38 , pp. 3581-3584
    • Zhao, L.1    Yalkowsky, S.H.2
  • 161
    • 0031309190 scopus 로고    scopus 로고
    • 3-D modelling and prediction by WHIM descriptors. Part 8. Toxicity and physicochemical properties of environmental priority chemicals by 2D-TI and 3D-WHIM descriptors
    • Todeschini R, Vighi M, Finizio A et al (1997) 3-D modelling and prediction by WHIM descriptors. Part 8. Toxicity and physicochemical properties of environmental priority chemicals by 2D-TI and 3D-WHIM descriptors. SAR QSAR Environ Res 7:173-193
    • (1997) SAR QSAR Environ Res , vol.7 , pp. 173-193
    • Todeschini, R.1    Vighi, M.2    Finizio, A.3
  • 162
    • 0041698448 scopus 로고    scopus 로고
    • Molecular descriptors influencing melting point and their role in classification of solid drugs
    • Bergstrom CAS, Norinder U, Luthman K et al (2003) Molecular descriptors influencing melting point and their role in classification of solid drugs. J Chem Inf Comput Sci 43: 1177-1185
    • (2003) J Chem Inf Comput Sci , vol.43 , pp. 1177-1185
    • Bergstrom, C.A.S.1    Norinder, U.2    Luthman, K.3
  • 163
    • 33646231725 scopus 로고    scopus 로고
    • QSPR correlation of melting point for drug compounds based on different sources of molecular descriptors
    • Modarresi H, Dearden JC, Modarress H (2006) QSPR correlation of melting point for drug compounds based on different sources of molecular descriptors. J Chem Inf Model 46:930-936
    • (2006) J Chem Inf Model , vol.46 , pp. 930-936
    • Modarresi, H.1    Dearden, J.C.2    Modarress, H.3
  • 164
    • 33746322753 scopus 로고    scopus 로고
    • An improved structure-property model for predicting melting-point temperatures
    • Godavarthy SS, Robinson RL, Gasem KAM (2006) An improved structure-property model for predicting melting-point temperatures. Ind Eng Chem Res 45:5117-5126
    • (2006) Ind Eng Chem Res , vol.45 , pp. 5117-5126
    • Godavarthy, S.S.1    Robinson, R.L.2    Gasem, K.A.M.3
  • 165
    • 20444362720 scopus 로고    scopus 로고
    • General melting point prediction based on a diverse compound data set and artificial neural networks
    • Karthikeyan M, Glen RC, Bender A (2005) General melting point prediction based on a diverse compound data set and artificial neural networks. J Chem Inf Model 45:581-590
    • (2005) J Chem Inf Model , vol.45 , pp. 581-590
    • Karthikeyan, M.1    Glen, R.C.2    Bender, A.3
  • 166
    • 84972939236 scopus 로고
    • Estimation of pure-component properties from group contributions
    • Joback KG, Reid RC (1987) Estimation of pure-component properties from group contributions. Chem Eng Commun 57:233-243
    • (1987) Chem Eng Commun , vol.57 , pp. 233-243
    • Joback, K.G.1    Reid, R.C.2
  • 167
    • 33751158943 scopus 로고
    • Group contribution methods for predicting the melting points and boiling points of aromatic compounds
    • Simamora P, Yalkowsky SH (1994) Group contribution methods for predicting the melting points and boiling points of aromatic compounds. Ind Eng Chem Res 33: 1405-1409
    • (1994) Ind Eng Chem Res , vol.33 , pp. 1405-1409
    • Simamora, P.1    Yalkowsky, S.H.2
  • 168
    • 0028517402 scopus 로고
    • New group contribution method for estimating properties of pure compounds
    • Constantinou L, Gani R (1994) New group contribution method for estimating properties of pure compounds. Am Inst Chem Eng J 40:1697-1710
    • (1994) Am Inst Chem Eng J , vol.40 , pp. 1697-1710
    • Constantinou, L.1    Gani, R.2
  • 169
    • 0035387458 scopus 로고    scopus 로고
    • Group-contribution based estimation of pure component properties
    • Marrero J, Gani R (2001) Group-contribution based estimation of pure component properties. Fluid Phase Equil 183-184:183-208
    • (2001) Fluid Phase Equil , vol.183-184 , pp. 183-208
    • Marrero, J.1    Gani, R.2
  • 170
    • 0030198274 scopus 로고    scopus 로고
    • Group-contribution estimation of normal freezing points of organic compounds
    • Tu C-H, Wu Y-S (1996) Group-contribution estimation of normal freezing points of organic compounds. J Chin Inst Chem Eng 27:323-328
    • (1996) J Chin Inst Chem Eng , vol.27 , pp. 323-328
    • Tu, C.-H.1    Wu, Y.-S.2
  • 171
    • 0242292366 scopus 로고
    • Estimating thermophysical properties of liquids. Part 4-Boiling, freezing and triple-point temperatures
    • Gold PI, Ogle GJ (1969) Estimating thermophysical properties of liquids. Part 4-Boiling, freezing and triple-point temperatures. Chem Eng 76:119-122
    • (1969) Chem Eng , vol.76 , pp. 119-122
    • Gold, P.I.1    Ogle, G.J.2
  • 173
    • 4243284762 scopus 로고
    • Considerations of a vapour pressure-temperature equation, and their relation to Burnop?s boiling point function
    • BanksWH(1939) Considerations of a vapour pressure-temperature equation, and their relation to Burnop?s boiling point function. J Chem Soc 292-295
    • (1939) J Chem Soc , pp. 292-295
    • Banks, W.H.1
  • 174
    • 0344508724 scopus 로고
    • Boiling point
    • Lyman WJ, Reehl WF, Rosenblatt DH (eds) American Chemical Society, Washington, DC
    • Rechsteiner CE (1990) Boiling point. In: Lyman WJ, Reehl WF, Rosenblatt DH (eds) Handbook of chemical property estimations methods. American Chemical Society, Washington, DC, pp 12.1-12.55
    • (1990) Handbook of Chemical Property Estimations Methods , pp. 1201-1255
    • Rechsteiner, C.E.1
  • 175
    • 0011998183 scopus 로고    scopus 로고
    • Evaluation in quantitative structure- property relationship models of structural descriptors derived from information-theory operators
    • Ivanciuc O, Ivanciuc T, Cabrol-Bass D et al (2000) Evaluation in quantitative structure- property relationship models of structural descriptors derived from information-theory operators. J Chem Inf Comput Sci 40: 631-643
    • (2000) J Chem Inf Comput Sci , vol.40 , pp. 631-643
    • Ivanciuc, O.1    Ivanciuc, T.2    Cabrol-Bass, D.3
  • 176
    • 0034092393 scopus 로고    scopus 로고
    • Use of electron-electron repulsion energy as a molecular descriptor in QSAR and QSPR studies
    • Girones X, Amat L, Robert D et al (2000) Use of electron-electron repulsion energy as a molecular descriptor in QSAR and QSPR studies. J Comput Aided Mol Des 14: 477-485
    • (2000) J Comput Aided Mol des , vol.14 , pp. 477-485
    • Girones, X.1    Amat, L.2    Robert, D.3
  • 177
    • 18144404059 scopus 로고    scopus 로고
    • Correlation of boiling points with molecular structure. 1. A training of 298 diverse organics and a test set of 9 simple inorganics
    • Katritzky AR, Mu L, Lobanov VS et al (1996) Correlation of boiling points with molecular structure. 1. A training of 298 diverse organics and a test set of 9 simple inorganics. J Phys Chem 100:10400-10407
    • (1996) J Phys Chem , vol.100 , pp. 10400-10407
    • Katritzky, A.R.1    Mu, L.2    Lobanov, V.S.3
  • 178
    • 36749096308 scopus 로고    scopus 로고
    • QSPR prediction of N-boiling point and critical properties of organic compounds and comparison with a group-contribution method
    • Sola D, Ferri A, Banchero M et al (2008) QSPR prediction of N-boiling point and critical properties of organic compounds and comparison with a group-contribution method. Fluid Phase Equil 263:33-42
    • (2008) Fluid Phase Equil , vol.263 , pp. 33-42
    • Sola, D.1    Ferri, A.2    Banchero, M.3
  • 179
    • 0000118057 scopus 로고
    • Prediction of normal boiling points for a diverse set of industrially important organic compounds from molecular structure
    • Wessel MD, Jurs PC (1995) Prediction of normal boiling points for a diverse set of industrially important organic compounds from molecular structure. J Chem Inf Comput Sci 35:841-850
    • (1995) J Chem Inf Comput Sci , vol.35 , pp. 841-850
    • Wessel, M.D.1    Jurs, P.C.2
  • 180
    • 0035746461 scopus 로고    scopus 로고
    • Use of mathematical structural invariants in the development of QSPR models
    • Basak SC, Mills D (2001) Use of mathematical structural invariants in the development of QSPR models. Commun Math Comput Chem 44:15-30
    • (2001) Commun Math Comput Chem , vol.44 , pp. 15-30
    • Basak, S.C.1    Mills, D.2
  • 181
    • 0000497238 scopus 로고    scopus 로고
    • Boiling point and critical temperature of a heterogeneous data set. QSAR with atom type electrotopological state indices using artificial neural networks
    • Hall LH, Story CT (1996) Boiling point and critical temperature of a heterogeneous data set. QSAR with atom type electrotopological state indices using artificial neural networks. J Chem Inf Comput Sci 36:1004-1014
    • (1996) J Chem Inf Comput Sci , vol.36 , pp. 1004-1014
    • Hall, L.H.1    Story, C.T.2
  • 183
    • 0028427706 scopus 로고
    • Estimation of normal boiling points from group contributions
    • Stein SE, Brown RL (1994) Estimation of normal boiling points from group contributions. J Chem Inf Comput Sci 34:581-587
    • (1994) J Chem Inf Comput Sci , vol.34 , pp. 581-587
    • Stein, S.E.1    Brown, R.L.2
  • 184
    • 0034351504 scopus 로고    scopus 로고
    • A widely applicable set of descriptors
    • Labute P (2000) A widely applicable set of descriptors. J Mol Graph Model 18:464-477
    • (2000) J Mol Graph Model , vol.18 , pp. 464-477
    • Labute, P.1
  • 185
    • 0036708688 scopus 로고    scopus 로고
    • Use of the DIPPR database for development of QSPR correlations: Normal boiling point
    • Ericksen D, Wilding WV, Oscarson JL et al (2002) Use of the DIPPR database for development of QSPR correlations: normal boiling point. J Chem Eng Data 47:1293-1302
    • (2002) J Chem Eng Data , vol.47 , pp. 1293-1302
    • Ericksen, D.1    Wilding, W.V.2    Oscarson, J.L.3
  • 186
    • 0010133234 scopus 로고
    • Vapor pressure
    • Lyman WJ, Reehl WF, Rosenblatt DH (eds) American Chemical Society,Washington, DC
    • Grain CF (1990) Vapor pressure. In: Lyman WJ, Reehl WF, Rosenblatt DH (eds) Handbook of chemical property estimation methods. American Chemical Society,Washington, DC, pp 14.1-14.20
    • (1990) Handbook of Chemical Property Estimation Methods , pp. 1401-1420
    • Grain, C.F.1
  • 187
    • 0004370409 scopus 로고    scopus 로고
    • The vapor pressure of environmentally significant organic chemicals: A review of methods and data at ambient temperature
    • Delle Site A (1996) The vapor pressure of environmentally significant organic chemicals: a review of methods and data at ambient temperature. J Phys Chem Ref Data 26: 157-193
    • (1996) J Phys Chem Ref Data , vol.26 , pp. 157-193
    • Delle Site, A.1
  • 189
    • 34248665536 scopus 로고    scopus 로고
    • Rapid QSPR model development technique for prediction of vapor pressure of organic compounds
    • Katritzky AR, Slavov SH, Dobchev DA et al (2007) Rapid QSPR model development technique for prediction of vapor pressure of organic compounds. Comput Chem Eng 31:1123-1130
    • (2007) Comput Chem Eng , vol.31 , pp. 1123-1130
    • Katritzky, A.R.1    Slavov, S.H.2    Dobchev, D.A.3
  • 190
    • 0000853599 scopus 로고    scopus 로고
    • QSPR prediction of vapor pressure from solely theoretically-derived descriptors
    • Liang CK, Gallagher DA (1998) QSPR prediction of vapor pressure from solely theoretically-derived descriptors. J Chem Inf Comput Sci 38:321-324
    • (1998) J Chem Inf Comput Sci , vol.38 , pp. 321-324
    • Liang, C.K.1    Gallagher, D.A.2
  • 191
    • 0028481624 scopus 로고
    • Group-contribution method for the estimation of vapor pressures
    • Tu C-H (1994) Group-contribution method for the estimation of vapor pressures. Fluid Phase Equil 99:105-120
    • (1994) Fluid Phase Equil , vol.99 , pp. 105-120
    • Tu, C.-H.1
  • 192
    • 54949098504 scopus 로고    scopus 로고
    • Global and local PLS regression models to predict vapor pressure
    • Oberg T, Liu T (2008) Global and local PLS regression models to predict vapor pressure. QSAR Comb Sci 27:273-279
    • (2008) QSAR Comb Sci , vol.27 , pp. 273-279
    • Oberg, T.1    Liu, T.2
  • 193
    • 67650914244 scopus 로고    scopus 로고
    • Predicting the vapour pressure of chemicals from structure: A comparison of graph theoretic versus quantum chemical descriptors
    • Basak SC, Mills D (2009) Predicting the vapour pressure of chemicals from structure: a comparison of graph theoretic versus quantum chemical descriptors. SAR QSAR Environ Res 20:119-132
    • (2009) SAR QSAR Environ Res , vol.20 , pp. 119-132
    • Basak, S.C.1    Mills, D.2
  • 194
    • 0001159624 scopus 로고    scopus 로고
    • Prediction of vapor pressures of hydrocarbons and halohydrocarbons from molecular structure with a computational neural network model
    • Goll ES, Jurs PC (1999) Prediction of vapor pressures of hydrocarbons and halohydrocarbons from molecular structure with a computational neural network model. J Chem Inf Comput Sci 39:1081-1089
    • (1999) J Chem Inf Comput Sci , vol.39 , pp. 1081-1089
    • Goll, E.S.1    Jurs, P.C.2
  • 195
    • 0344413414 scopus 로고    scopus 로고
    • Molecular polarizability as single-parameter predictor of vapor pressures and octanol-air partitioning coefficients of nonpolar compounds: A priori approach and results
    • Staikova M, Wania F, Donaldson DJ (2004) Molecular polarizability as single-parameter predictor of vapor pressures and octanol-air partitioning coefficients of nonpolar compounds: a priori approach and results. Atmos Environ 38:213-225
    • (2004) Atmos Environ , vol.38 , pp. 213-225
    • Staikova, M.1    Wania, F.2    Donaldson, D.J.3
  • 196
    • 4243384281 scopus 로고
    • Prediction of vapour pressure and boiling points of aliphatic compounds
    • Andreev NN, Kuznetsov SE, Storozhenko SY (1994) Prediction of vapour pressure and boiling points of aliphatic compounds. Mendeleev Commun 173-174
    • (1994) Mendeleev Commun , pp. 173-174
    • Andreev, N.N.1    Kuznetsov, S.E.2    Storozhenko, S.Y.3
  • 197
    • 0031079633 scopus 로고    scopus 로고
    • Estimation of vapour pressures for hydrocarbons and halogenated hydrocarbons from chemical structure by a neural network
    • Kuhne R, Ebert R-U, Schuurmann G (1997) Estimation of vapour pressures for hydrocarbons and halogenated hydrocarbons from chemical structure by a neural network. Chemosphere 34:671-686
    • (1997) Chemosphere , vol.34 , pp. 671-686
    • Kuhne, R.1    Ebert, R.-U.2    Schuurmann, G.3
  • 198
    • 0035273271 scopus 로고    scopus 로고
    • Neural network based temperature-dependent quantitative structure property relationships (QSPRs) for predicting vapor pressure of hydrocarbons
    • Yaffe D, Cohen Y (2001) Neural network based temperature-dependent quantitative structure property relationships (QSPRs) for predicting vapor pressure of hydrocarbons. J Chem Inf Comput Sci 41:463-477
    • (2001) J Chem Inf Comput Sci , vol.41 , pp. 463-477
    • Yaffe, D.1    Cohen, Y.2
  • 199
    • 33746070043 scopus 로고    scopus 로고
    • SVRC-QSPR model for predicting saturated vapor pressure of pure fluids
    • Godavarthy SS, Robinson RL, Gasem KAM (2006) SVRC-QSPR model for predicting saturated vapor pressure of pure fluids. Fluid Phase Equil 246:39-51
    • (2006) Fluid Phase Equil , vol.246 , pp. 39-51
    • Godavarthy, S.S.1    Robinson, R.L.2    Gasem, K.A.M.3
  • 200
    • 0009740068 scopus 로고
    • Evaluation of estimation methods for the air-water partition coefficient
    • Schuurmann G, Rothenbacher C (1992) Evaluation of estimation methods for the air-water partition coefficient. Fresenius Environ Bull 1:10-15
    • (1992) Fresenius Environ Bull , vol.1 , pp. 10-15
    • Schuurmann, G.1    Rothenbacher, C.2
  • 202
    • 0242301035 scopus 로고    scopus 로고
    • QSPR prediction of Henry?s law constant: Improved correlation with new parameters
    • Gundertofte K, Jorgensen FS (eds) Kluwer Academic/Plenum, New York, NY
    • Dearden JC, Cronin MTD, Ahmed SA et al (2000) QSPR prediction of Henry?s law constant: improved correlation with new parameters. In: Gundertofte K, Jorgensen FS (eds) Molecular modeling and prediction of bioactivity. Kluwer Academic/Plenum, New York, NY, pp 273-274
    • (2000) Molecular Modeling and Prediction of Bioactivity , pp. 273-274
    • Dearden, J.C.1    Cronin, M.T.D.2    Ahmed, S.A.3
  • 203
    • 0041700890 scopus 로고
    • The intrinsic hydrophilic character of organic compounds. Correlations in terms of structural contributions
    • Hine J, Mookerjee PK (1974) The intrinsic hydrophilic character of organic compounds. Correlations in terms of structural contributions. J Org Chem 40:292-298
    • (1974) J Org Chem , vol.40 , pp. 292-298
    • Hine, J.1    Mookerjee, P.K.2
  • 204
    • 9944232242 scopus 로고
    • Group contributions to the thermodynamic properties of non-ionic organic solutes in dilute aqueous solution
    • Cabani S, Gianni P, Mollica V et al (1981) Group contributions to the thermodynamic properties of non-ionic organic solutes in dilute aqueous solution. J Solut Chem 10:563-595
    • (1981) J Solut Chem , vol.10 , pp. 563-595
    • Cabani, S.1    Gianni, P.2    Mollica, V.3
  • 205
    • 0026004450 scopus 로고
    • Bond contribution method for estimating Henry?s law constants
    • Meylan WM, Howard PH (1991) Bond contribution method for estimating Henry?s law constants. Environ Toxicol Chem 10: 1283-1293
    • (1991) Environ Toxicol Chem , vol.10 , pp. 1283-1293
    • Meylan, W.M.1    Howard, P.H.2
  • 207
    • 0000845639 scopus 로고
    • Computer-assisted study of the relationship between molecular structure and Henry?s law constant
    • Russell CJ, Dixon SL, Jurs PC (1992) Computer-assisted study of the relationship between molecular structure and Henry?s law constant. Anal Chem 64:1350-1355
    • (1992) Anal Chem , vol.64 , pp. 1350-1355
    • Russell, C.J.1    Dixon, S.L.2    Jurs, P.C.3
  • 208
    • 33846096494 scopus 로고    scopus 로고
    • QSPR model of Henry?s law constant for a diverse set of organic chemicals based on genetic algorithm-radial basis function network approach
    • Modarresi H, Modarress H, Dearden JC (2007) QSPR model of Henry?s law constant for a diverse set of organic chemicals based on genetic algorithm-radial basis function network approach. Chemosphere 66:2067-2076
    • (2007) Chemosphere , vol.66 , pp. 2067-2076
    • Modarresi, H.1    Modarress, H.2    Dearden, J.C.3
  • 209
    • 37049071153 scopus 로고
    • Hydrogen bonding. Part 34. The factors that influence the solubility of gases and vapours in water at 298 K, and a new method for its determination
    • Abraham MH, Andonian-Haftvan J, Whiting GS et al (1994) Hydrogen bonding. Part 34. The factors that influence the solubility of gases and vapours in water at 298 K, and a new method for its determination. J Chem Soc Perkin Trans 2:1777-1791
    • (1994) J Chem Soc Perkin Trans , vol.2 , pp. 1777-1791
    • Abraham, M.H.1    Andonian-Haftvan, J.2    Whiting, G.S.3
  • 210
    • 0037266490 scopus 로고    scopus 로고
    • A fuzzy ARTMAP-based quantitative structure- property relationship (QSPR) for the Henry?s law constant of organic compounds
    • Yaffe D, Cohen Y, Espinosa G et al (2003) A fuzzy ARTMAP-based quantitative structure- property relationship (QSPR) for the Henry?s law constant of organic compounds. J Chem Inf Comput Sci 43:85-112
    • (2003) J Chem Inf Comput Sci , vol.43 , pp. 85-112
    • Yaffe, D.1    Cohen, Y.2    Espinosa, G.3
  • 211
    • 77958020996 scopus 로고    scopus 로고
    • Prediction of Henry?s law constant of organic compounds in water from a new group-contribution- based model
    • Gharagheizi F, Abbasi R, Tirandazi B (2010) Prediction of Henry?s law constant of organic compounds in water from a new group-contribution- based model. Ind Eng Chem Res 49:10149-10152
    • (2010) Ind Eng Chem Res , vol.49 , pp. 10149-10152
    • Gharagheizi, F.1    Abbasi, R.2    Tirandazi, B.3
  • 212
    • 0000115399 scopus 로고    scopus 로고
    • A QSPR study of the solubility of gases and vapors in water
    • Katritzky AR, Mu L, Karelson M (1996) A QSPR study of the solubility of gases and vapors in water. J Chem Inf Comput Sci 36: 1162-1168
    • (1996) J Chem Inf Comput Sci , vol.36 , pp. 1162-1168
    • Katritzky, A.R.1    Mu, L.2    Karelson, M.3
  • 213
    • 0142089686 scopus 로고    scopus 로고
    • Guidelines for developing and using quantitative structure-activity relationships
    • Walker JD, Jaworska J, Comber MHI et al (2003) Guidelines for developing and using quantitative structure-activity relationships. Environ Toxicol Chem 22:1653-1665
    • (2003) Environ Toxicol Chem , vol.22 , pp. 1653-1665
    • Walker, J.D.1    Jaworska, J.2    Comber, M.H.I.3
  • 214
    • 57349197941 scopus 로고    scopus 로고
    • Quantitative structure-activity relationships (QSAR) in drug design
    • Smith HJ (ed) 4th edn. Taylor & Francis, Boca Raton, FL
    • Dearden JC, Cronin MTD (2006) Quantitative structure-activity relationships (QSAR) in drug design. In: Smith HJ (ed) Introduction to the principles of drug design and action, 4th edn. Taylor & Francis, Boca Raton, FL, pp 185-209
    • (2006) Introduction to the Principles of Drug Design and Action , pp. 185-209
    • Dearden, J.C.1    Cronin, M.T.D.2
  • 215
    • 84897544576 scopus 로고    scopus 로고
    • Introduction to QSAR and other in silico methods to predict toxicity
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Madden JC (2010) Introduction to QSAR and other in silico methods to predict toxicity. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 11-30
    • (2010) In Silico Toxicology: Principles and Applications , pp. 11-30
    • Madden, J.C.1
  • 216
    • 84880545744 scopus 로고    scopus 로고
    • OECD Principles
    • OECD Principles: www.oecd.org/dataoecd/33/37/37849783.pdf
  • 217
    • 0013393259 scopus 로고    scopus 로고
    • OECD Guidelines: www.olis.oecd.org/olis/2004doc.nsf/LinkTo/NT00009192/ $FILE/JT00176183.PDF
    • OECD Guidelines
  • 218
    • 67949118928 scopus 로고    scopus 로고
    • How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR
    • Dearden JC, Cronin MTD, Kaiser KLE (2009) How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR). SAR QSAR Environ Res 20:241-266
    • (2009) SAR QSAR Environ Res , vol.20 , pp. 241-266
    • Dearden, J.C.1    Cronin, M.T.D.2    Kaiser, K.L.E.3
  • 219
    • 0034051385 scopus 로고    scopus 로고
    • The use of atomic charges and orbital energies as hydrogen- bonding-donor parameters for QSAR studies: Comparison of MNDO, AM1 and PM3 methods
    • Ghafourian T, Dearden JC (2000) The use of atomic charges and orbital energies as hydrogen- bonding-donor parameters for QSAR studies: comparison of MNDO, AM1 and PM3 methods. J Pharm Pharmacol 52: 603-610
    • (2000) J Pharm Pharmacol , vol.52 , pp. 603-610
    • Ghafourian, T.1    Dearden, J.C.2
  • 220
    • 19944430250 scopus 로고    scopus 로고
    • A modular approach to the ECVAM principles on test validity
    • Hartung T, Bremer S, Casati S et al (2004) A modular approach to the ECVAM principles on test validity. ATLA 32:467-472
    • (2004) ATLA , vol.32 , pp. 467-472
    • Hartung, T.1    Bremer, S.2    Casati, S.3
  • 221
    • 27744502880 scopus 로고    scopus 로고
    • Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships
    • Netzeva TI, Worth A, Aldenberg T et al (2005) Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop
    • (2005) The Report and Recommendations of ECVAM Workshop
    • Netzeva, T.I.1    Worth, A.2    Aldenberg, T.3
  • 222
    • 84934439585 scopus 로고    scopus 로고
    • ATLA 33:155-173
    • ATLA , vol.33 , pp. 155-173
  • 223
    • 84897530967 scopus 로고    scopus 로고
    • Developing the applicability domain of in silico models: Relevance, importance and methods
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Hewitt M, Ellison CM (2010) Developing the applicability domain of in silico models: relevance, importance and methods. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 301-333
    • (2010) In Silico Toxicology: Principles and Applications , pp. 301-333
    • Hewitt, M.1    Ellison, C.M.2
  • 224
    • 0002584744 scopus 로고
    • Physicochemical determinants of skin absorption
    • Gerrity TR, Henry CJ (eds) Elsevier, Amsterdam
    • Flynn GL (1990) Physicochemical determinants of skin absorption. In: Gerrity TR, Henry CJ (eds) Principles of route-to-route extrapolation for risk assessment. Elsevier, Amsterdam, pp 93-127
    • (1990) Principles of Route-to-route Extrapolation for Risk Assessment , pp. 93-127
    • Flynn, G.L.1
  • 225
    • 58149136373 scopus 로고    scopus 로고
    • Are the chemical structures in your QSAR correct?
    • Young D, Martin T, Venkatapathy R et al (2008) Are the chemical structures in your QSAR correct? QSAR Comb Sci 27: 1337-1345
    • (2008) QSAR Comb Sci , vol.27 , pp. 1337-1345
    • Young, D.1    Martin, T.2    Venkatapathy, R.3
  • 226
    • 0033038344 scopus 로고    scopus 로고
    • Investigation of the mechanism of flux across human skin in vitro by quantitative structure-permeability relationships
    • Cronin MTD, Dearden JC, Moss GP et al (1999) Investigation of the mechanism of flux across human skin in vitro by quantitative structure-permeability relationships. Eur J Pharm Sci 7:3250330
    • (1999) Eur J Pharm Sci , vol.7 , pp. 3250330
    • Cronin, M.T.D.1    Dearden, J.C.2    Moss, G.P.3
  • 227
    • 33847044104 scopus 로고    scopus 로고
    • Structure-based modelling in reproductive toxicology: (Q)SARs for the placental barrier
    • Hewitt M, Madden JC, Rowe PH, Cronin MTD (2007) Structure-based modelling in reproductive toxicology: (Q)SARs for the placental barrier. SAR QSAR Environ Res 18: 57-76
    • (2007) SAR QSAR Environ Res , vol.18 , pp. 57-76
    • Hewitt, M.1    Madden, J.C.2    Rowe, P.H.3    Cronin, M.T.D.4
  • 228
    • 12244271454 scopus 로고    scopus 로고
    • Predicting CNS permeability of drug molecules: Comparison of neural network and support vector machine algorithms
    • Doniger S, Hofmann T, Yeh J (2002) Predicting CNS permeability of drug molecules: comparison of neural network and support vector machine algorithms. J Comput Biol 9:849-864
    • (2002) J Comput Biol , vol.9 , pp. 849-864
    • Doniger, S.1    Hofmann, T.2    Yeh, J.3
  • 230
    • 33750286241 scopus 로고    scopus 로고
    • QSAR-how good is it in practice? Comparison of descriptor sets on an unbiased cross section of corporate data sets
    • Gedeck P, Rohde B, Bartels C (2006) QSAR-how good is it in practice? Comparison of descriptor sets on an unbiased cross section of corporate data sets. J Chem Inf Model 46:1924-1936
    • (2006) J Chem Inf Model , vol.46 , pp. 1924-1936
    • Gedeck, P.1    Rohde, B.2    Bartels, C.3
  • 231
    • 0015417054 scopus 로고
    • Chance correlations in structure-activity studies using multiple regression analysis
    • Topliss JG, Costello RJ (1972) Chance correlations in structure-activity studies using multiple regression analysis. J Med Chem 15:1066-1068
    • (1972) J Med Chem , vol.15 , pp. 1066-1068
    • Topliss, J.G.1    Costello, R.J.2
  • 233
    • 0035470294 scopus 로고    scopus 로고
    • A fuzzy ARTMAP based on quantitative structure- property relationships (QSPRs) for predicting aqueous solubility of organic compounds
    • Yaffe D, Cohen Y, Espinosa G et al (2001) A fuzzy ARTMAP based on quantitative structure- property relationships (QSPRs) for predicting aqueous solubility of organic compounds. J Chem Inf Comput Sci 41:1177-1207
    • (2001) J Chem Inf Comput Sci , vol.41 , pp. 1177-1207
    • Yaffe, D.1    Cohen, Y.2    Espinosa, G.3
  • 234
    • 18344363227 scopus 로고    scopus 로고
    • The better predictive model: High q2 for the training set or low root mean square error of prediction for the test set?
    • Aptula AO, Jeliazkova NG, Schultz TW et al (2005) The better predictive model: high q2 for the training set or low root mean square error of prediction for the test set? QSAR Comb Sci 24:385-396
    • (2005) QSAR Comb Sci , vol.24 , pp. 385-396
    • Aptula, A.O.1    Jeliazkova, N.G.2    Schultz, T.W.3
  • 235
    • 17044455173 scopus 로고    scopus 로고
    • Comparison of predictive ability of water solubility QSPR models generated by MLR. PLS and ANN methods
    • Eros D, Keri G, Kovesdi I et al (2004) Comparison of predictive ability of water solubility QSPR models generated by MLR, PLS and ANN methods. Mini Rev Med Chem 4:167-177
    • (2004) Mini Rev Med Chem , vol.4 , pp. 167-177
    • Eros, D.1    Keri, G.2    Kovesdi, I.3
  • 236
    • 0036581727 scopus 로고    scopus 로고
    • E-Statistics for deriving QSAR models
    • Devillers J, Dore JC (2002) e-Statistics for deriving QSAR models. SAR QSAR Environ Res 13:409-416
    • (2002) SAR QSAR Environ Res , vol.13 , pp. 409-416
    • Devillers, J.1    Dore, J.C.2
  • 237
    • 84880530943 scopus 로고    scopus 로고
    • Scripps Institute
    • Scripps Institute: www.scripps.edu/rc/softwaredocs/msi/cerius45/qsar/ working-with- stats.html
  • 238
    • 84880541937 scopus 로고    scopus 로고
    • QSAR World
    • QSAR World: www.qsarworld.com/statistics. php
  • 239
    • 0036589313 scopus 로고    scopus 로고
    • Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection
    • Golbraikh A, Tropsha A (2002) Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection. J Comput Aided Mol Des 16:357-369
    • (2002) J Comput Aided Mol des , vol.16 , pp. 357-369
    • Golbraikh, A.1    Tropsha, A.2
  • 240
    • 0033652279 scopus 로고    scopus 로고
    • On the selection of the training set in environmental QSAR analysis when compounds are clustered
    • Eriksson L, Johansson E, Muller M et al (2000) On the selection of the training set in environmental QSAR analysis when compounds are clustered. J Chemom 14: 599-616
    • (2000) J Chemom , vol.14 , pp. 599-616
    • Eriksson, L.1    Johansson, E.2    Muller, M.3
  • 241
    • 34247885823 scopus 로고    scopus 로고
    • Quantitative structure-retention relationship for the Kovats retention indices of a large set of terpenes: A combined data splitting-feature selection strategy
    • Hemmateenajad B, Javadnia K, Elyasi M (2007) Quantitative structure-retention relationship for the Kovats retention indices of a large set of terpenes: a combined data splitting-feature selection strategy. Anal Chim Acta 592:72-81
    • (2007) Anal Chim Acta , vol.592 , pp. 72-81
    • Hemmateenajad, B.1    Javadnia, K.2    Elyasi, M.3
  • 242
    • 84897530372 scopus 로고    scopus 로고
    • Characterisation, evaluation and possible validation of in silico models for toxicity: Determining if a prediction is valid
    • Cronin MTD, Madden JC (eds) RSC Publishing, Cambridge
    • Cronin MTD (2010) Characterisation, evaluation and possible validation of in silico models for toxicity: determining if a prediction is valid. In: Cronin MTD, Madden JC (eds) In silico toxicology: principles and applications. RSC Publishing, Cambridge, pp 275-300
    • (2010) In Silico Toxicology: Principles and Applications , pp. 275-300
    • Cronin, M.T.D.1
  • 243
    • 0038724207 scopus 로고    scopus 로고
    • The importance of being earnest: Validation is the absolute essential for successful application and interpretation of QSPR models
    • Tropsha A, Gramatica P, Gombar VK (2003) The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci 22:69-77
    • (2003) QSAR Comb Sci , vol.22 , pp. 69-77
    • Tropsha, A.1    Gramatica, P.2    Gombar, V.K.3
  • 245
    • 77049106101 scopus 로고    scopus 로고
    • QSAR investigation of new cognition enhancers
    • Dearden JC, Hewitt M, Geronikaki AA et al (2009) QSAR investigation of new cognition enhancers. QSAR Comb Sci 28: 1123-1129
    • (2009) QSAR Comb Sci , vol.28 , pp. 1123-1129
    • Dearden, J.C.1    Hewitt, M.2    Geronikaki, A.A.3
  • 246
    • 39449135396 scopus 로고    scopus 로고
    • The trouble with QSAR (or how i learned to stop worrying and embrace fallacy
    • Johnson SR (2008) The trouble with QSAR (or how I learned to stop worrying and embrace fallacy). J Chem Inf Model 48:25-26
    • (2008) J Chem Inf Model , vol.48 , pp. 25-26
    • Johnson, S.R.1
  • 247
    • 77958029276 scopus 로고    scopus 로고
    • Quantitative correlation of physical and chemical properties with chemical structure: Utility for prediction
    • Katritzky AR, Kuanar M, Slavov S et al (2010) Quantitative correlation of physical and chemical properties with chemical structure: utility for prediction. Chem Rev 110:5714-5789
    • (2010) Chem Rev , vol.110 , pp. 5714-5789
    • Katritzky, A.R.1    Kuanar, M.2    Slavov, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.