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Journal of Cheminformatics

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https://www.readbyqxmd.com/read/28316657/comprehensive-identification-of-sphingolipid-species-by-in-silico-retention-time-and-tandem-mass-spectral-library
#1
Hiroshi Tsugawa, Kazutaka Ikeda, Wataru Tanaka, Yuya Senoo, Makoto Arita, Masanori Arita
BACKGROUND: Liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is used for comprehensive metabolome and lipidome analyses. Compound identification relies on similarity matching of the retention time (RT), precursor m/z, isotopic ratio, and MS/MS spectrum with reference compounds. For sphingolipids, however, little information on the RT and MS/MS references is available. RESULTS: Negative-ion ESI-MS/MS is a useful method for the structural characterization of sphingolipids...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28316656/analysis-of-drug-endogenous-human-metabolite-similarities-in-terms-of-their-maximum-common-substructures
#2
Steve O'Hagan, Douglas B Kell
In previous work, we have assessed the structural similarities between marketed drugs ('drugs') and endogenous natural human metabolites ('metabolites' or 'endogenites'), using 'fingerprint' methods in common use, and the Tanimoto and Tversky similarity metrics, finding that the fingerprint encoding used had a dramatic effect on the apparent similarities observed. By contrast, the maximal common substructure (MCS), when the means of determining it is fixed, is a means of determining similarities that is largely independent of the fingerprints, and also has a clear chemical meaning...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28316655/excape-db-an-integrated-large-scale-dataset-facilitating-big-data-analysis-in-chemogenomics
#3
Jiangming Sun, Nina Jeliazkova, Vladimir Chupakin, Jose-Felipe Golib-Dzib, Ola Engkvist, Lars Carlsson, Jörg Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay Kochev, Thomas J Ashby, Hongming Chen
Chemogenomics data generally refers to the activity data of chemical compounds on an array of protein targets and represents an important source of information for building in silico target prediction models. The increasing volume of chemogenomics data offers exciting opportunities to build models based on Big Data. Preparing a high quality data set is a vital step in realizing this goal and this work aims to compile such a comprehensive chemogenomics dataset. This dataset comprises over 70 million SAR data points from publicly available databases (PubChem and ChEMBL) including structure, target information and activity annotations...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28316654/predicting-drug-drug-interactions-through-drug-structural-similarities-and-interaction-networks-incorporating-pharmacokinetics-and-pharmacodynamics-knowledge
#4
Takako Takeda, Ming Hao, Tiejun Cheng, Stephen H Bryant, Yanli Wang
Drug-drug interactions (DDIs) may lead to adverse effects and potentially result in drug withdrawal from the market. Predicting DDIs during drug development would help reduce development costs and time by rigorous evaluation of drug candidates. The primary mechanisms of DDIs are based on pharmacokinetics (PK) and pharmacodynamics (PD). This study examines the effects of 2D structural similarities of drugs on DDI prediction through interaction networks including both PD and PK knowledge. Our assumption was that a query drug (Dq) and a drug to be examined (De) likely have DDI if the drugs in the interaction network of De are structurally similar to Dq...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28316653/large-scale-virtual-screening-on-public-cloud-resources-with-apache-spark
#5
Marco Capuccini, Laeeq Ahmed, Wesley Schaal, Erwin Laure, Ola Spjuth
BACKGROUND: Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28316652/a-novel-descriptor-based-on-atom-pair-properties
#6
Masataka Kuroda
BACKGROUND: Molecular descriptors have been widely used to predict biological activities and physicochemical properties or to analyze chemical libraries on the basis of similarity. Although fingerprints and properties are generally used as descriptors, neither is perfect for these purposes. A fingerprint can distinguish between molecules, whereas a property may not do the same in certain cases, and vice versa. When the number of the training set is especially small, the construction of good predictive models is difficult...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28303165/modeling-framework-for-isotopic-labeling-of-heteronuclear-moieties
#7
Mark I Borkum, Patrick N Reardon, Ronald C Taylor, Nancy G Isern
BACKGROUND: Isotopic labeling is an analytic technique that is used to track the movement of isotopes through reaction networks. In general, the applicability of isotopic labeling techniques is limited to the investigation of reaction networks that consider homonuclear moieties, whose atoms are of one tracer element with two isotopes, distinguished by the presence of one additional neutron. RESULTS: This article presents a reformulation of the modeling framework for isotopic labeling, generalized to arbitrarily large, heteronuclear moieties, arbitrary numbers of isotopic tracer elements, and arbitrary numbers of isotopes per element, distinguished by arbitrary numbers of additional neutrons...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28303164/adverse-drug-reactions-triggered-by-the-common-hla-b-57-01-variant-a-molecular-docking-study
#8
George Van Den Driessche, Denis Fourches
BACKGROUND: Human leukocyte antigen (HLA) surface proteins are directly involved in idiosyncratic adverse drug reactions. Herein, we present a structure-based analysis of the common HLA-B*57:01 variant known to be responsible for several HLA-linked adverse effects such as the abacavir hypersensitivity syndrome. METHODS: First, we analyzed three X-ray crystal structures involving the HLA-B*57:01 protein variant, the anti-HIV drug abacavir, and different co-binding peptides present in the antigen-binding cleft...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28286574/nontargeted-homologue-series-extraction-from-hyphenated-high-resolution-mass-spectrometry-data
#9
Martin Loos, Heinz Singer
BACKGROUND: A large proportion of polar anthropogenic compounds routinely released into the environment comprises homologue series, i.e., sets of chemicals differing in a repeating chemical unit. Using analytical techniques such as liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), these compounds are readily measurable as signal sets with characteristic differences in mass and typically retention time. However, and despite such distinct characteristics, no computational approach for the direct, simultaneous and untargeted detection of all such signal sets comprising both LC and HRMS information has to date been presented...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28286573/technical-implications-of-new-iupac-elements-in-cheminformatics
#10
EDITORIAL
John W Mayfield, Roger A Sayle
The symbols for the new IUPAC elements named in November 2016 can introduce subtle ambiguities within cheminformatics software. The ambiguities are described and demonstrated by highlighting inconsistencies between software when handling existing element symbols.
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28270862/the-polypharmacology-browser-a-web-based-multi-fingerprint-target-prediction-tool-using-chembl-bioactivity-data
#11
Mahendra Awale, Jean-Louis Reymond
BACKGROUND: Several web-based tools have been reported recently which predict the possible targets of a small molecule by similarity to compounds of known bioactivity using molecular fingerprints (fps), however predictions in each case rely on similarities computed from only one or two fps. Considering that structural similarity and therefore the predicted targets strongly depend on the method used for comparison, it would be highly desirable to predict targets using a broader set of fps simultaneously...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28224019/database-fingerprint-dfp-an-approach-to-represent-molecular-databases
#12
Eli Fernández-de Gortari, César R García-Jacas, Karina Martinez-Mayorga, José L Medina-Franco
BACKGROUND: Molecular fingerprints are widely used in several areas of chemoinformatics including diversity analysis and similarity searching. The fingerprint-based analysis of chemical libraries, in particular of large collections, usually requires the molecular representation of each compound in the library that may lead to issues of storage space and redundant calculations. In fact, information redundancy is inherent to the data, resulting on binary digit positions in the fingerprint without significant information...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28217147/automatic-procedure-for-generating-symmetry-adapted-wavefunctions
#13
Marcus Johansson, Valera Veryazov
Automatic detection of point groups as well as symmetrisation of molecular geometry and wavefunctions are useful tools in computational quantum chemistry. Algorithms for developing these tools as well as an implementation are presented. The symmetry detection algorithm is a clustering algorithm for symmetry invariant properties, combined with logical deduction of possible symmetry elements using the geometry of sets of symmetrically equivalent atoms. An algorithm for determining the symmetry adapted linear combinations (SALCs) of atomic orbitals is also presented...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28203291/the-power-metric-a-new-statistically-robust-enrichment-type-metric-for-virtual-screening-applications-with-early-recovery-capability
#14
Julio Cesar Dias Lopes, Fábio Mendes Dos Santos, Andrelly Martins-José, Koen Augustyns, Hans De Winter
A new metric for the evaluation of model performance in the field of virtual screening and quantitative structure-activity relationship applications is described. This metric has been termed the power metric and is defined as the fraction of the true positive rate divided by the sum of the true positive and false positive rates, for a given cutoff threshold. The performance of this metric is compared with alternative metrics such as the enrichment factor, the relative enrichment factor, the receiver operating curve enrichment factor, the correct classification rate, Matthews correlation coefficient and Cohen's kappa coefficient...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28203290/mapping-and-classifying-molecules-from-a-high-throughput-structural-database
#15
Sandip De, Felix Musil, Teresa Ingram, Carsten Baldauf, Michele Ceriotti
High-throughput computational materials design promises to greatly accelerate the process of discovering new materials and compounds, and of optimizing their properties. The large databases of structures and properties that result from computational searches, as well as the agglomeration of data of heterogeneous provenance leads to considerable challenges when it comes to navigating the database, representing its structure at a glance, understanding structure-property relations, eliminating duplicates and identifying inconsistencies...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28194231/skinsensdb-a-curated-database-for-skin-sensitization-assays
#16
Chia-Chi Wang, Ying-Chi Lin, Shan-Shan Wang, Chieh Shih, Yi-Hui Lin, Chun-Wei Tung
Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment. Prediction of chemical skin sensitizer had traditionally relied on data from rodent models. The development of the adverse outcome pathway (AOP) and associated alternative in vitro assays have reshaped the assessment of skin sensitizers. The integration of multiple assays as key events in the AOP has been shown to have improved prediction performance. Current computational models to predict skin sensitization mainly based on in vivo assays without incorporating alternative in vitro assays...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28184255/a-metadata-driven-approach-to-data-repository-design
#17
Matthew J Harvey, Andrew McLean, Henry S Rzepa
The design and use of a metadata-driven data repository for research data management is described. Metadata is collected automatically during the submission process whenever possible and is registered with DataCite in accordance with their current metadata schema, in exchange for a persistent digital object identifier. Two examples of data preview are illustrated, including the demonstration of a method for integration with commercial software that confers rich domain-specific data analytics without introducing customisation into the repository itself...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28184254/npcare-database-of-natural-products-and-fractional-extracts-for-cancer-regulation
#18
Hwanho Choi, Sun Young Cho, Ho Jeong Pak, Youngsoo Kim, Jung-Yun Choi, Yoon Jae Lee, Byung Hee Gong, Yeon Seok Kang, Taehoon Han, Geunbae Choi, Yeeun Cho, Soomin Lee, Dekwoo Ryoo, Hwangseo Park
BACKGROUND: Natural products have increasingly attracted much attention as a valuable resource for the development of anticancer medicines due to the structural novelty and good bioavailability. This necessitates a comprehensive database for the natural products and the fractional extracts whose anticancer activities have been verified. DESCRIPTION: NPCARE (http://silver.sejong.ac.kr/npcare) is a publicly accessible online database of natural products and fractional extracts for cancer regulation...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28123452/s2rsldb-a-comprehensive-manually-curated-internet-accessible-database-of-the-sigma-2-receptor-selective-ligands
#19
Giovanni Nastasi, Carla Miceli, Valeria Pittalà, Maria N Modica, Orazio Prezzavento, Giuseppe Romeo, Antonio Rescifina, Agostino Marrazzo, Emanuele Amata
BACKGROUND: Sigma (σ) receptors are accepted as a particular receptor class consisting of two subtypes: sigma-1 (σ1) and sigma-2 (σ2). The two receptor subtypes have specific drug actions, pharmacological profiles and molecular characteristics. The σ2 receptor is overexpressed in several tumor cell lines, and its ligands are currently under investigation for their role in tumor diagnosis and treatment. The σ2 receptor structure has not been disclosed, and researchers rely on σ2 receptor radioligand binding assay to understand the receptor's pharmacological behavior and design new lead compounds...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28316651/improving-chemical-disease-relation-extraction-with-rich-features-and-weakly-labeled-data
#20
Yifan Peng, Chih-Hsuan Wei, Zhiyong Lu
BACKGROUND: Due to the importance of identifying relations between chemicals and diseases for new drug discovery and improving chemical safety, there has been a growing interest in developing automatic relation extraction systems for capturing these relations from the rich and rapid-growing biomedical literature. In this work we aim to build on current advances in named entity recognition and a recent BioCreative effort to further improve the state of the art in biomedical relation extraction, in particular for the chemical-induced disease (CID) relations...
2016: Journal of Cheminformatics
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