The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Lowell L Ashbaugh - One of the best experts on this subject based on the ideXlab platform.
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comparison of the mura and an improved Single Receptor sira trajectory source apportionment tsa method using artificial sources
Atmospheric Environment, 2007Co-Authors: Stephanie Lee, Lowell L AshbaughAbstract:Abstract Two trajectory source apportionment methods were tested using an artificially generated data set to determine their ability to detect the known sources. The forward-looking step from the multi-Receptor trajectory analysis (MURA) method was added to the conditional probability (CP)method of Ashbaugh et al. [1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment 19(8), 1263–1270] to develop the Single-Receptor forward CP (SIRA) method. The multi-Receptor (MURA) and the SIRA methods were tested with three simulations using artificially generated sources. The ability of the methods to detect the sources was quantified for each simulation. The first simulation showed that the SIRA method is an improvement over the original CP method. The MURA trajectory method proved to be superior at identifying sources for the simulation located in the west and comparable to the SIRA method for the two simulations located in the east.
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comparison of multi Receptor and Single Receptor trajectory source apportionment tsa methods using artificial sources
Atmospheric Environment, 2007Co-Authors: Stephanie Lee, Lowell L AshbaughAbstract:Abstract Two trajectory source apportionment methods were tested using an artificially generated data set to determine their ability to detect the known sources. The residence time or conditional probability method developed by Ashbaugh et al. [1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment 19(8), 1263–1270] uses a Single Receptor at a time, whereas the new multi-Receptor (MURA) method developed here uses several Receptors at once in an attempt to detect the sources with higher accuracy. The methods were first tested using a simulation with a Single source and then with another simulation using four sources. The ability of the methods to detect the sources was quantified for each simulation. The MURA trajectory method proved to be superior at identifying sources for these simulations.
Stephanie Lee - One of the best experts on this subject based on the ideXlab platform.
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comparison of the mura and an improved Single Receptor sira trajectory source apportionment tsa method using artificial sources
Atmospheric Environment, 2007Co-Authors: Stephanie Lee, Lowell L AshbaughAbstract:Abstract Two trajectory source apportionment methods were tested using an artificially generated data set to determine their ability to detect the known sources. The forward-looking step from the multi-Receptor trajectory analysis (MURA) method was added to the conditional probability (CP)method of Ashbaugh et al. [1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment 19(8), 1263–1270] to develop the Single-Receptor forward CP (SIRA) method. The multi-Receptor (MURA) and the SIRA methods were tested with three simulations using artificially generated sources. The ability of the methods to detect the sources was quantified for each simulation. The first simulation showed that the SIRA method is an improvement over the original CP method. The MURA trajectory method proved to be superior at identifying sources for the simulation located in the west and comparable to the SIRA method for the two simulations located in the east.
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comparison of multi Receptor and Single Receptor trajectory source apportionment tsa methods using artificial sources
Atmospheric Environment, 2007Co-Authors: Stephanie Lee, Lowell L AshbaughAbstract:Abstract Two trajectory source apportionment methods were tested using an artificially generated data set to determine their ability to detect the known sources. The residence time or conditional probability method developed by Ashbaugh et al. [1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment 19(8), 1263–1270] uses a Single Receptor at a time, whereas the new multi-Receptor (MURA) method developed here uses several Receptors at once in an attempt to detect the sources with higher accuracy. The methods were first tested using a simulation with a Single source and then with another simulation using four sources. The ability of the methods to detect the sources was quantified for each simulation. The MURA trajectory method proved to be superior at identifying sources for these simulations.
Jerold Chun - One of the best experts on this subject based on the ideXlab platform.
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a Single Receptor encoded by vzg 1 lpa1 edg 2 couples to g proteins and mediates multiple cellular responses to lysophosphatidic acid
Proceedings of the National Academy of Sciences of the United States of America, 1998Co-Authors: Nobuyuki Fukushima, Yuka Kimura, Jerold ChunAbstract:Extracellular lysophosphatidic acid (LPA) produces diverse cellular responses in many cell types. Recent reports of several molecularly distinct G protein-coupled Receptors have raised the possibility that the responses to LPA stimulation could be mediated by the combination of several uni-functional Receptors. To address this issue, we analyzed one Receptor encoded by ventricular zone gene-1 (vzg-1) (also referred to as lpA1/edg-2) by using heterologous expression in a neuronal and nonneuronal cell line. VZG-1 expression was necessary and sufficient in mediating multiple effects of LPA: [3H]-LPA binding, G protein activation, stress fiber formation, neurite retraction, serum response element activation, and increased DNA synthesis. These results demonstrate that a Single Receptor, encoded by vzg-1, can activate multiple LPA-dependent responses in cells from distinct tissue lineages.
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A Single Receptor encoded by vzg-1/lpA1/edg-2 couples to G proteins and mediates multiple cellular responses to lysophosphatidic acid
Proceedings of the National Academy of Sciences of the United States of America, 1998Co-Authors: Nobuyuki Fukushima, Yuka Kimura, Jerold ChunAbstract:Extracellular lysophosphatidic acid (LPA) produces diverse cellular responses in many cell types. Recent reports of several molecularly distinct G protein-coupled Receptors have raised the possibility that the responses to LPA stimulation could be mediated by the combination of several uni-functional Receptors. To address this issue, we analyzed one Receptor encoded by ventricular zone gene-1 (vzg-1) (also referred to as lpA1/edg-2) by using heterologous expression in a neuronal and nonneuronal cell line. VZG-1 expression was necessary and sufficient in mediating multiple effects of LPA: [3H]-LPA binding, G protein activation, stress fiber formation, neurite retraction, serum response element activation, and increased DNA synthesis. These results demonstrate that a Single Receptor, encoded by vzg-1, can activate multiple LPA-dependent responses in cells from distinct tissue lineages.
Sukjoon Yoon - One of the best experts on this subject based on the ideXlab platform.
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Optimization of High Throughput Virtual Screening by Combining Shape‐Matching and Docking Methods.
ChemInform, 2008Co-Authors: Hui Sun Lee, Ruben Abagyan, Jiwon Choi, Irina Kufareva, Anton V. Filikov, Young Yang, Sukjoon YoonAbstract:Receptor flexibility is a critical issue in structure-based virtual screening methods. Although a multiple-Receptor conformation docking is an efficient way to account for Receptor flexibility, it is still too slow for large molecular libraries. It was reported that a fast ligand-centric, shape-based virtual screening was more consistent for hit enrichment than a typical Single-Receptor conformation docking. Thus, we designed a “distributed docking” method that improves virtual high throughput screening by combining a shape-matching method with a multiple-Receptor conformation docking. Database compounds are classified in advance based on shape similarities to one of the crystal ligands complexed with the target protein. This classification enables us to pick the appropriate Receptor conformation for a Single-Receptor conformation docking of a given compound, thereby avoiding time-consuming multiple docking. In particular, this approach utilizes cross-docking scores of known ligands to all available recep...
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Optimization of high throughput virtual screening by combining shape-matching and docking methods.
Journal of chemical information and modeling, 2008Co-Authors: Hui Sun Lee, Ruben Abagyan, Jiwon Choi, Irina Kufareva, Anton V. Filikov, Young Yang, Sukjoon YoonAbstract:Receptor flexibility is a critical issue in structure-based virtual screening methods. Although a multiple-Receptor conformation docking is an efficient way to account for Receptor flexibility, it is still too slow for large molecular libraries. It was reported that a fast ligand-centric, shape-based virtual screening was more consistent for hit enrichment than a typical Single-Receptor conformation docking. Thus, we designed a “distributed docking” method that improves virtual high throughput screening by combining a shape-matching method with a multiple-Receptor conformation docking. Database compounds are classified in advance based on shape similarities to one of the crystal ligands complexed with the target protein. This classification enables us to pick the appropriate Receptor conformation for a Single-Receptor conformation docking of a given compound, thereby avoiding time-consuming multiple docking. In particular, this approach utilizes cross-docking scores of known ligands to all available recep...
Ruben Abagyan - One of the best experts on this subject based on the ideXlab platform.
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Consistent Improvement of Cross-Docking Results Using Binding Site Ensembles Generated with Elastic Network Normal Modes
Journal of chemical information and modeling, 2009Co-Authors: Manuel Rueda, Giovanni Bottegoni, Ruben AbagyanAbstract:The representation of protein flexibility is still a challenge for the state-of-the-art flexible ligand docking protocols. In this article, we use a large and diverse benchmark to prove that is possible to improve consistently the cross-docking performance against a Single Receptor conformation, using an equilibrium ensemble of binding site conformers. The benchmark contained 28 proteins, and our method predicted the top-ranked near native ligand poses 20% more efficiently than using a Single Receptor. The multiple conformations were derived from the collective variable space defined by all heavy-atom elastic network normal modes, including backbone and side chains. We have found that the binding site displacements for best positioning of the ligand seem rather independent from the global collective motions of the protein. We also found that the number of binding site conformations needed to represent nonredundant flexibility was
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Optimization of High Throughput Virtual Screening by Combining Shape‐Matching and Docking Methods.
ChemInform, 2008Co-Authors: Hui Sun Lee, Ruben Abagyan, Jiwon Choi, Irina Kufareva, Anton V. Filikov, Young Yang, Sukjoon YoonAbstract:Receptor flexibility is a critical issue in structure-based virtual screening methods. Although a multiple-Receptor conformation docking is an efficient way to account for Receptor flexibility, it is still too slow for large molecular libraries. It was reported that a fast ligand-centric, shape-based virtual screening was more consistent for hit enrichment than a typical Single-Receptor conformation docking. Thus, we designed a “distributed docking” method that improves virtual high throughput screening by combining a shape-matching method with a multiple-Receptor conformation docking. Database compounds are classified in advance based on shape similarities to one of the crystal ligands complexed with the target protein. This classification enables us to pick the appropriate Receptor conformation for a Single-Receptor conformation docking of a given compound, thereby avoiding time-consuming multiple docking. In particular, this approach utilizes cross-docking scores of known ligands to all available recep...
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Optimization of high throughput virtual screening by combining shape-matching and docking methods.
Journal of chemical information and modeling, 2008Co-Authors: Hui Sun Lee, Ruben Abagyan, Jiwon Choi, Irina Kufareva, Anton V. Filikov, Young Yang, Sukjoon YoonAbstract:Receptor flexibility is a critical issue in structure-based virtual screening methods. Although a multiple-Receptor conformation docking is an efficient way to account for Receptor flexibility, it is still too slow for large molecular libraries. It was reported that a fast ligand-centric, shape-based virtual screening was more consistent for hit enrichment than a typical Single-Receptor conformation docking. Thus, we designed a “distributed docking” method that improves virtual high throughput screening by combining a shape-matching method with a multiple-Receptor conformation docking. Database compounds are classified in advance based on shape similarities to one of the crystal ligands complexed with the target protein. This classification enables us to pick the appropriate Receptor conformation for a Single-Receptor conformation docking of a given compound, thereby avoiding time-consuming multiple docking. In particular, this approach utilizes cross-docking scores of known ligands to all available recep...
