An Ontological Approach to Represent Molecular Structure Information

2005 ◽  
pp. 294-304 ◽  
Author(s):  
Eva Armengol ◽  
Enric Plaza
Keyword(s):  
Molecular Structure ◽  
Structure Information ◽  
Ontological Approach

scholarly journals Laser-induced blurring of molecular structure information in high harmonic spectroscopy

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
François Risoud ◽  
Camille Lévêque ◽  
Marie Labeye ◽  
Jérémie Caillat ◽  
Alfred Maquet ◽  
...  
Keyword(s):  
Molecular Structure ◽  
High Harmonic ◽  
Structure Information

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

1999 ◽  
Vol 18 (1) ◽  
pp. 7-18 ◽  
Author(s):  
Patrick Poulin ◽  
Kannan Krishnan
Keyword(s):  
Molecular Structure ◽  
A Priori ◽  
Venous Blood ◽  
Modeling Framework ◽  
Structure Information ◽  
Low Concentrations ◽  
Hepatic Extraction Ratio ◽  
Volatile Organic ◽  
Volatile Organic Chemicals ◽  
Animal Replacement

The objectives of the present study were: (1) to evaluate the adequacy of setting hepatic extraction ratio (E) equal to 0 or 1 in physiologically based toxicokinetic (PBTK) models to generate the theoretically plausible envelope of venous blood concentration (Cv) profiles, and (2) to couple this approach with molecular structure-based estimation of blood:air and tissue: blood partition coefficients (PCs) to predictthe Cv profiles of volatile organic chemicals (VOCs) in humans. Setting E= 0 or 1 in PBTK models provided simulations of Cv envelopes that contained the Cv values determined in humans exposed to low concentrations of dichloromethane(DCM), ethylbenzene (EBZ), toluene (TOL), m-xylene(XYL), trichloroethy-lene (TCE), and 1,1,1-trichloroethane(TRI). Following the validation of using E= 0 or 1 in conventional PBTK models to predict the theoretically plausible envelope of Cv, a quantitative structure-toxicokinetic relationship (QSTkR) model was constructed. The QSTkR model used molecular structure information as the sole input to predict the PCs and considered E= 0 or 1 to generate simulations of the envelope of Cv. The experimental data on Cv were in most cases within the envelopes simulated using QSTkR models for DCM, EBZ, TOL, and XYL, but were outside the envelopes for TCE and TRI. The discrepancy observed between the Cv envelopes obtained using PBTK and QSTkR models can be explained by the fact that blood:air PCs of some VOCs were under-predicted while using molecular structure information. The modeling framework presented in this article represents the first animal-replacement tool that can provide a priori predictions of the toxicokinetic profiles of VOCs prior to laboratory experiments.

scholarly journals CellPAINT: Turnkey Illustration of Molecular Cell Biology

2021 ◽  
Vol 1 ◽  
Author(s):  
Adam Gardner ◽  
Ludovic Autin ◽  
Daniel Fuentes ◽  
Martina Maritan ◽  
Benjamin A. Barad ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Protein Data Bank ◽  
Cell Biology ◽  
Data Bank ◽  
Hypothesis Generation ◽  
Digital Tool ◽  
Structure Information ◽  
Large Complex ◽  
Complex Scenes ◽  
Molecular Cell Biology

CellPAINT is an interactive digital tool that allows non-expert users to create illustrations of the molecular structure of cells and viruses. We present a new release with several key enhancements, including the ability to generate custom ingredients from structure information in the Protein Data Bank, and interaction, grouping, and locking functions that streamline the creation of assemblies and illustration of large, complex scenes. An example of CellPAINT as a tool for hypothesis generation in the interpretation of cryoelectron tomograms is presented. CellPAINT is freely available at http://ccsb.scripps.edu/cellpaint.

A Quantitative Structure-toxicokinetic Relationship Model for Highly Metabolised Chemicals

1998 ◽  
Vol 26 (1) ◽  
pp. 45-55
Author(s):  
Patrick Poulin ◽  
Kannan Krishnan
Keyword(s):  
Molecular Structure ◽  
Metabolic Rate ◽  
Rate Constants ◽  
Venous Blood ◽  
Liver Blood Flow ◽  
Hepatic Clearance ◽  
Blood Flow Rate ◽  
Quantitative Structure ◽  
Structure Information ◽  
Relationship Model

The aim of the present study was to develop a quantitative structure-toxicokinetic relationship (QSTkR) model for highly metabolised chemicals (HMCs). The proposed QSTkR model is essentially a physiologically based toxicokinetic (PBTK) model, in which the blood:air and tissue:blood partition coefficients (PCs) are predicted from the molecular structure of chemicals, and the liver blood flow rate (Q1) is used to describe hepatic clearance. Molecular structure-based prediction of the blood:air and tissue:blood PCs was performed from the n-octanol:water and water:air PCs of chemicals obtained with the conventional fragment constant methods. The validity of incorporating Q1 instead of metabolic rate constants, as the hepatic clearance factor, in PBTK models for HMCs (extraction ratio > 0.7) was verified by comparing the simulations of venous blood concentration (Cv) profiles obtained with both the QSTkR and PBTK model approaches for 1,1-dichloroethylehe, trichloroethylene and furan in the rat. Following the validation of this alternative approach for describing hepatic clearance of HMCs, a QSTkR model for dichloromethane was constructed. This model used molecular structure information as the sole input, and provided simulations of Cv for human exposure to low concentrations of dichloromethane. The QSTkR model simulations were similar to those obtained with the previously validated, conventional human PBTK model with experimentally determined PCs and metabolic rate constants (Vmax, Km and Kf) for dichloromethane. The present methodology is the first validated example of a mechanistically based prediction of the inhalation toxicokinetics of HMCs made solely from information on molecular structure.

scholarly journals Using Drug Descriptions and Molecular Structures for Drug-Drug Interaction Extraction from Literature

2020 ◽  
Author(s):  
Masaki Asada ◽  
Makoto Miwa ◽  
Yutaka Sasaki
Keyword(s):  
Molecular Structure ◽  
Large Scale ◽  
Molecular Structures ◽  
Data Set ◽  
Structure Information ◽  
Plain Text ◽  
Drug Database ◽  
Effective Combination ◽  
Interaction Extraction ◽  
Text Information

Abstract Motivation Neural methods to extract drug-drug interactions (DDIs) from literature require a large number of annotations. In this study, we propose a novel method to effectively utilize external drug database information as well as information from large-scale plain text for DDI extraction. Specifically, we focus on drug description and molecular structure information as the drug database information. Results We evaluated our approach on the DDIExtraction 2013 shared task data set. We obtained the following results. First, large-scale raw text information can greatly improve the performance of extracting DDIs when combined with the existing model and it shows the state-of-the-art performance. Second, each of drug description and molecular structure information is helpful to further improve the DDI performance for some specific DDI types. Finally, the simultaneous use of the drug description and molecular structure information can significantly improve the performance on all the DDI types. We showed that the plain text, the drug description information, and molecular structure information are complementary and their effective combination are essential for the improvement. Availability https://github.com/tticoin/DESC_MOL-DDIE

Molecular Structure of the Outermost Cell Wall Component of Spirillum Serpens

1977 ◽  
Vol 35 ◽  
pp. 342-343
Author(s):  
Wah Chiu ◽  
David Grano
Keyword(s):  
Molecular Structure ◽  
Cell Wall ◽  
Outer Membrane ◽  
Gel Electrophoresis ◽  
Electron Microscopic Examination ◽  
Electron Microscopic ◽  
Cell Wall Component ◽  
Protein Components ◽  
Exposure Technique ◽  
Structural Aspects

The periodic structure external to the outer membrane of Spirillum serpens VHA has been isolated by similar procedures to those used by Buckmire and Murray (1). From SDS gel electrophoresis, we have found that the isolated fragments contain several protein components, and that the crystalline structure is composed of a glycoprotein component with a molecular weight of ∽ 140,000 daltons (2). Under an electron microscopic examination, we have visualized the hexagonally-packed glycoprotein subunits, as well as the bilayer profile of the outer membrane. In this paper, we will discuss some structural aspects of the crystalline glycoproteins, based on computer-reconstructed images of the external cell wall fragments.The specimens were prepared for electron microscopy in two ways: negatively stained with 1% PTA, and maintained in a frozen-hydrated state (3). The micrographs were taken with a JEM-100B electron microscope with a field emission gun. The minimum exposure technique was essential for imaging the frozen- hydrated specimens.

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