The Experts below are selected from a list of 966 Experts worldwide ranked by ideXlab platform
J. Steadman - One of the best experts on this subject based on the ideXlab platform.
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Picosecond measurements of phenol excited‐state proton transfer in clusters. I. Solvent basicity and cluster size effects
The Journal of Chemical Physics, 1991Co-Authors: J. A. Syage, J. SteadmanAbstract:Excited‐state proton transfer (ESPT) rates in molecular clusters were measured as a function of cluster size using picosecond spectroscopy in a molecular beam mass spectrometer. ESPT from the S1 state of phenol to base solvent clusters (NH3)n occurs for a critical solvent cluster size n≥5, with a rate constant of k=(60±10 ps)−1 for n=5–7. ESPT showing critical cluster‐size dependencies was also observed in the basic solvent N(CH3)3(n≂3). Proton transfer was not observed in the less‐basic solvent clusters (CH3OH)n and (H2O)n. Mixed‐solvent studies indicate that the addition of a Dissimilar Molecule to an otherwise neat solvent cluster impedes ESPT, presumably due to a disruption of the hydrogen bonding network. Evidence is also presented for the direct measure of solvent reorganization following ESPT. For (NH3)n solvation, the solvent reorganization appears as a long‐time‐scale component (0.3 ns) on the protonated solvent formation traces.
J. A. Syage - One of the best experts on this subject based on the ideXlab platform.
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Picosecond measurements of phenol excited‐state proton transfer in clusters. I. Solvent basicity and cluster size effects
The Journal of Chemical Physics, 1991Co-Authors: J. A. Syage, J. SteadmanAbstract:Excited‐state proton transfer (ESPT) rates in molecular clusters were measured as a function of cluster size using picosecond spectroscopy in a molecular beam mass spectrometer. ESPT from the S1 state of phenol to base solvent clusters (NH3)n occurs for a critical solvent cluster size n≥5, with a rate constant of k=(60±10 ps)−1 for n=5–7. ESPT showing critical cluster‐size dependencies was also observed in the basic solvent N(CH3)3(n≂3). Proton transfer was not observed in the less‐basic solvent clusters (CH3OH)n and (H2O)n. Mixed‐solvent studies indicate that the addition of a Dissimilar Molecule to an otherwise neat solvent cluster impedes ESPT, presumably due to a disruption of the hydrogen bonding network. Evidence is also presented for the direct measure of solvent reorganization following ESPT. For (NH3)n solvation, the solvent reorganization appears as a long‐time‐scale component (0.3 ns) on the protonated solvent formation traces.
Alexandre Varnek - One of the best experts on this subject based on the ideXlab platform.
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A unified approach to the applicability domain problem of QSAR models
Journal of Cheminformatics, 2010Co-Authors: Dragos Horvath, Gilles Marcou, Alexandre VarnekAbstract:The present work proposes a unified conceptual framework to describe and quantify the important issue of the Applicability Domains (AD) of Quantitative Structure-Activity Relationships (QSARs). AD models are conceived as meta-models designed to associate an untrustworthiness score to any Molecule M subject to property prediction by a QSAR model. Untrustworthiness scores or "AD metrics" are an expression of the relationship between M (represented by its descriptors in chemical space) and the space zones populated by the training Molecules at the basis of model μ. Scores integrating some of the classical AD criteria (similarity-based, box-based) were considered in addition to newly invented terms, such as the Dissimilarity to outlier-free training sets and the correlation breakdown count. A loose correlation is expected to exist between this untrustworthiness and the error affecting the predicted property. While high untrustworthiness does not preclude correct predictions, inaccurate predictions at low untrustworthiness must be imperatively avoided. This kind of relationship is characteristic for the Neighborhood Behavior (NB) problem: Dissimilar Molecule pairs may or may not display similar properties, but similar Molecule pairs with different properties are explicitly "forbidden". Therefore, statistical tools developed to tackle this latter aspect were applied, and lead to a unified AD metric benchmarking scheme. A first use of untrustworthiness scores resides in prioritization of predictions, without need to specify a hard AD border. Moreover, if a significant set of external compounds is available, the formalism allows optimal AD borderlines to be fitted. Eventually, consensus AD definitions were built by means of a nonparametric mixing scheme of two AD metrics of comparable quality, and shown to outperform their respective parents.
Dragos Horvath - One of the best experts on this subject based on the ideXlab platform.
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A unified approach to the applicability domain problem of QSAR models
Journal of Cheminformatics, 2010Co-Authors: Dragos Horvath, Gilles Marcou, Alexandre VarnekAbstract:The present work proposes a unified conceptual framework to describe and quantify the important issue of the Applicability Domains (AD) of Quantitative Structure-Activity Relationships (QSARs). AD models are conceived as meta-models designed to associate an untrustworthiness score to any Molecule M subject to property prediction by a QSAR model. Untrustworthiness scores or "AD metrics" are an expression of the relationship between M (represented by its descriptors in chemical space) and the space zones populated by the training Molecules at the basis of model μ. Scores integrating some of the classical AD criteria (similarity-based, box-based) were considered in addition to newly invented terms, such as the Dissimilarity to outlier-free training sets and the correlation breakdown count. A loose correlation is expected to exist between this untrustworthiness and the error affecting the predicted property. While high untrustworthiness does not preclude correct predictions, inaccurate predictions at low untrustworthiness must be imperatively avoided. This kind of relationship is characteristic for the Neighborhood Behavior (NB) problem: Dissimilar Molecule pairs may or may not display similar properties, but similar Molecule pairs with different properties are explicitly "forbidden". Therefore, statistical tools developed to tackle this latter aspect were applied, and lead to a unified AD metric benchmarking scheme. A first use of untrustworthiness scores resides in prioritization of predictions, without need to specify a hard AD border. Moreover, if a significant set of external compounds is available, the formalism allows optimal AD borderlines to be fitted. Eventually, consensus AD definitions were built by means of a nonparametric mixing scheme of two AD metrics of comparable quality, and shown to outperform their respective parents.
Gilles Marcou - One of the best experts on this subject based on the ideXlab platform.
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A unified approach to the applicability domain problem of QSAR models
Journal of Cheminformatics, 2010Co-Authors: Dragos Horvath, Gilles Marcou, Alexandre VarnekAbstract:The present work proposes a unified conceptual framework to describe and quantify the important issue of the Applicability Domains (AD) of Quantitative Structure-Activity Relationships (QSARs). AD models are conceived as meta-models designed to associate an untrustworthiness score to any Molecule M subject to property prediction by a QSAR model. Untrustworthiness scores or "AD metrics" are an expression of the relationship between M (represented by its descriptors in chemical space) and the space zones populated by the training Molecules at the basis of model μ. Scores integrating some of the classical AD criteria (similarity-based, box-based) were considered in addition to newly invented terms, such as the Dissimilarity to outlier-free training sets and the correlation breakdown count. A loose correlation is expected to exist between this untrustworthiness and the error affecting the predicted property. While high untrustworthiness does not preclude correct predictions, inaccurate predictions at low untrustworthiness must be imperatively avoided. This kind of relationship is characteristic for the Neighborhood Behavior (NB) problem: Dissimilar Molecule pairs may or may not display similar properties, but similar Molecule pairs with different properties are explicitly "forbidden". Therefore, statistical tools developed to tackle this latter aspect were applied, and lead to a unified AD metric benchmarking scheme. A first use of untrustworthiness scores resides in prioritization of predictions, without need to specify a hard AD border. Moreover, if a significant set of external compounds is available, the formalism allows optimal AD borderlines to be fitted. Eventually, consensus AD definitions were built by means of a nonparametric mixing scheme of two AD metrics of comparable quality, and shown to outperform their respective parents.