Results 251 to 260 of about 151,281 (298)
Some of the next articles are maybe not open access.
Quantitative Structure–Property Relationships for Vapor Pressure of PCDD/Fs
Bulletin of Environmental Contamination and Toxicology, 2001GSF, Natl Res Ctr Environm & Hlth, Inst Ecol Chem, D-85764 Munich, Germany; State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China; Dalian Univ Technol, Sch Environm Sci & Technol, Dalian 116012, Peoples R ...
J W, Chen +4 more
openaire +2 more sources
Building a Quantitative Structure-Property Relationship (QSPR) Model
2019Knowing the physicochemical and general biochemical properties of a compound is critical to understanding how it behaves in different biological environments and to anticipating what is likely to happen in situations where that behavior cannot be measured directly.
Robert D, Clark, Pankaj R, Daga
openaire +2 more sources
Quantitative structure–property relationship of distribution coefficients of organic compounds
SAR and QSAR in Environmental Research, 2020The n-octanol/buffer solution distribution coefficient (or n-octanol/water partition coefficient) is of critical importance for measuring lipophilicity of drug candidates. After 4885 molecular descriptor generation, 15 molecular descriptors were selected to develop quantitative structure-property relationship (QSPR) models for distribution coefficients
Y. Liu, X. Yu, J. Chen
openaire +2 more sources
Quantitative structure–property relationships in pharmaceutical research – Part 2
Pharmaceutical Science & Technology Today, 2000Part one of this two-part review described the advantages and limitations of quantitative structure-property relationships (QSPR), and offered an overview of the components involved in the development of correlations1. Part two provides a discussion of a few notable examples of relationships with organoleptic, physicochemical and pharmaceutical ...
Manish Grover +3 more
openaire +2 more sources
Quantitative Structure–Property Relationship Approach in Formulation Development: an Overview
AAPS PharmSciTech, 2019Chemoinformatics is emerging as a new trend to set drug discovery which correlates the relationship between structure and biological functions. The main aim of chemoinformatics refers to analyzing the similarity among molecules, searching the molecules in the structural database, finding potential drug molecule and their property. One of the key fields
Ajit S, Kulkarni +4 more
openaire +2 more sources
Journal of Chromatography A, 2006
The retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides was studied by quantitative structure-property relationships (QSPR) method. Heuristic method (HM) and support vector machine (SVM) method were used to build linear and nonlinear models, respectively. Compared the results of these two methods,
Weiping, Ma +6 more
openaire +2 more sources
The retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides was studied by quantitative structure-property relationships (QSPR) method. Heuristic method (HM) and support vector machine (SVM) method were used to build linear and nonlinear models, respectively. Compared the results of these two methods,
Weiping, Ma +6 more
openaire +2 more sources
Quantitative structure–property relationships on photodegradation of polybrominated diphenyl ethers
Chemosphere, 2006By partial least squares (PLS) regression, quantitative structure-property relationship (QSPR) models were developed for photodegradation rates (k(p)) and quantum yields (Phi) of polybrominated diphenyl ethers (PBDEs) in methanol/water (8:2), and photodegradation rates in pure methanol by UV light in the sunlight region, respectively.
Junfeng, Niu +4 more
openaire +2 more sources
Quantitative structure–property relationships (QSPRs) on direct photolysis of PCDDs
Chemosphere, 2001By the use of partial least squares (PLS) method and 27 quantum chemical descriptors computed by PM3 Hamiltonian, a statistically significant QSPR were obtained for direct photolysis quantum yields (Y) of selected Polychlorinated dibenzo-p-dioxins (PCDDs). The QSPR can be used for prediction.
J, Chen +4 more
openaire +2 more sources
Applications of quantitative structure—property relationships to pharmaceutics
Chemometrics and Intelligent Laboratory Systems, 1994Abstract Most correlation analysis studies of drugs are concerned with the correlation of in-vivo or in-vitro biological activity with physicochemical or structural molecular parameters. However, it is also important to be able to predict such properties as solubility, melting and boiling points, adsorption behaviour, stability to degradation ...
openaire +1 more source
The Journal of Physical Chemistry B, 2005
The results of a qualitative and quantitative structure-property relationships analysis of multicomponent potential bioglasses of composition (2 - y) SiO2 x 1 Na2O x 1.1 CaO x y P2O5 x x ZnO (x = 0, 0.16, 0.35, 0.78 and y = 0.10, 0.20, 0.36) are presented. Quantitative models are obtained by means of structural descriptors derived by molecular dynamics
L. LINATI +6 more
openaire +5 more sources
The results of a qualitative and quantitative structure-property relationships analysis of multicomponent potential bioglasses of composition (2 - y) SiO2 x 1 Na2O x 1.1 CaO x y P2O5 x x ZnO (x = 0, 0.16, 0.35, 0.78 and y = 0.10, 0.20, 0.36) are presented. Quantitative models are obtained by means of structural descriptors derived by molecular dynamics
L. LINATI +6 more
openaire +5 more sources