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Journal of Cheminformatics

Ola Spjuth, Patrik Rydberg, Egon L Willighagen, Chris T Evelo, Nina Jeliazkova
Xenobiotic metabolism is an active research topic but the limited amount of openly available high-quality biotransformation data constrains predictive modeling. Current database often default to commonly available information: which enzyme metabolizes a compound, but neither experimental conditions nor the atoms that undergo metabolization are captured. We present XMetDB, an open access database for drugs and other xenobiotics and their respective metabolites. The database contains chemical structures of xenobiotic biotransformations with substrate atoms annotated as reaction centra, the resulting product formed, and the catalyzing enzyme, type of experiment, and literature references...
2016: Journal of Cheminformatics
Athira Dilip, Samo Lešnik, Tanja Štular, Dušanka Janežič, Janez Konc
Ligand-based virtual screening of large small-molecule databases is an important step in the early stages of drug development. It is based on the similarity principle and is used to reduce the chemical space of large databases to a manageable size where chosen ligands can be experimentally tested. Ligand-based virtual screening can also be used to identify bioactive molecules with different basic scaffolds compared to already known bioactive molecules, thus having the potential to increase the structural variability of compounds...
2016: Journal of Cheminformatics
Sakari Lätti, Sanna Niinivehmas, Olli T Pentikäinen
Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use...
2016: Journal of Cheminformatics
A McMillan, J B Renaud, G B Gloor, G Reid, M W Sumarah
Liquid chromatography-high resolution mass spectrometry (LC-MS) has emerged as one of the most widely used platforms for untargeted metabolomics due to its unparalleled sensitivity and metabolite coverage. Despite its prevalence of use, the proportion of true metabolites identified in a given experiment compared to background contaminants and ionization-generated artefacts remains poorly understood. Salt clusters are well documented artefacts of electrospray ionization MS, recognized by their characteristically high mass defects (for this work simply generalized as the decimal numbers after the nominal mass)...
2016: Journal of Cheminformatics
Nathalie Lagarde, Solenne Delahaye, Jean-François Zagury, Matthieu Montes
Nuclear receptors (NRs) constitute an important class of therapeutic targets. We evaluated the performance of 3D structure-based and ligand-based pharmacophore models in predicting the pharmacological profile of NRs ligands using the NRLiSt BDB database. We could generate selective pharmacophores for agonist and antagonist ligands and we found that the best performances were obtained by combining the structure-based and the ligand-based approaches. The combination of pharmacophores that were generated allowed to cover most of the chemical space of the NRLiSt BDB datasets...
2016: Journal of Cheminformatics
Gert-Jan Bekker, Haruki Nakamura, Akira R Kinjo
We have developed a new platform-independent web-based molecular viewer using JavaScript and WebGL. The molecular viewer, Molmil, has been integrated into several services offered by Protein Data Bank Japan and can be easily extended with new functionality by third party developers. Furthermore, the viewer can be used to load files in various formats from the user's local hard drive without uploading the data to a server. Molmil is available for all platforms supporting WebGL (e.g. Windows, Linux, iOS, Android) from http://gjbekker...
2016: Journal of Cheminformatics
Varsha S Kulkarni, David J Wild
BACKGROUND: Highly chemically similar drugs usually possess similar biological activities, but sometimes, small changes in chemistry can result in a large difference in biological effects. Chemically similar drug pairs that show extreme deviations in activity represent distinctive drug interactions having important implications. These associations between chemical and biological similarity are studied as discontinuities in activity landscapes. Particularly, activity cliffs are quantified by the drop in similar activity of chemically similar drugs...
2016: Journal of Cheminformatics
Maciej Barycki, Anita Sosnowska, Magdalena Piotrowska, Piotr Urbaszek, Anna Rybinska, Monika Grzonkowska, Tomasz Puzyn
BACKGROUND: Ionic liquids (ILs) found a variety of applications in today's chemistry. Since their properties depend on the ions constituting particular ionic liquid, it is possible to synthetize IL with desired specification, dependently on its further function. However, this task is not trivial, since knowledge regarding the influence of particular ion on the property of concern is crucial. Therefore, there is a strong need for new, fast and inexpensive methods supporting the process of ionic liquids' design, making it possible to predefine IL's properties even before the synthesis...
2016: Journal of Cheminformatics
Jonathan Alvarsson, Samuel Lampa, Wesley Schaal, Claes Andersson, Jarl E S Wikberg, Ola Spjuth
The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor...
2016: Journal of Cheminformatics
Jun Gao, Qingchen Zhang, Min Liu, Lixin Zhu, Dingfeng Wu, Zhiwei Cao, Ruixin Zhu
MOTIVATION: Protein-binding sites prediction lays a foundation for functional annotation of protein and structure-based drug design. As the number of available protein structures increases, structural alignment based algorithm becomes the dominant approach for protein-binding sites prediction. However, the present algorithms underutilize the ever increasing numbers of three-dimensional protein-ligand complex structures (bound protein), and it could be improved on the process of alignment, selection of templates and clustering of template...
2016: Journal of Cheminformatics
Ming Hao, Stephen H Bryant, Yanli Wang
BACKGROUND: As one of the largest publicly accessible databases for hosting chemical structures and biological activities, PubChem has been processing bioassay submissions from the community since 2004. With the increase in volume for the deposited data in PubChem, the diversity and wealth of information content also grows. Recently, the Tox21 program, has deposited a series of pairwise data in PubChem regarding to different mechanism of actions (MOA), such as androgen receptor (AR) agonist and antagonist datasets, to study cell toxicity...
2016: Journal of Cheminformatics
Noel M O'Boyle, Roger A Sayle
BACKGROUND: The concept of molecular similarity is one of the central ideas in cheminformatics, despite the fact that it is ill-defined and rather difficult to assess objectively. Here we propose a practical definition of molecular similarity in the context of drug discovery: molecules A and B are similar if a medicinal chemist would be likely to synthesise and test them around the same time as part of the same medicinal chemistry program. The attraction of such a definition is that it matches one of the key uses of similarity measures in early-stage drug discovery...
2016: Journal of Cheminformatics
Santiago Vilar, George Hripcsak
BACKGROUND: Drug-target identification is crucial to discover novel applications for existing drugs and provide more insights about mechanisms of biological actions, such as adverse drug effects (ADEs). Computational methods along with the integration of current big data sources provide a useful framework for drug-target and drug-adverse effect discovery. RESULTS: In this article, we propose a method based on the integration of 3D chemical similarity, target and adverse effect data to generate a drug-target-adverse effect predictor along with a simple leveraging system to improve identification of drug-targets and drug-adverse effects...
2016: Journal of Cheminformatics
Jie Dong, Zhi-Jiang Yao, Ming Wen, Min-Feng Zhu, Ning-Ning Wang, Hong-Yu Miao, Ai-Ping Lu, Wen-Bin Zeng, Dong-Sheng Cao
BACKGROUND: More and more evidences from network biology indicate that most cellular components exert their functions through interactions with other cellular components, such as proteins, DNAs, RNAs and small molecules. The rapidly increasing amount of publicly available data in biology and chemistry enables researchers to revisit interaction problems by systematic integration and analysis of heterogeneous data. Currently, some tools have been developed to represent these components...
2016: Journal of Cheminformatics
Ashenafi Legehar, Henri Xhaard, Leo Ghemtio
BACKGROUND: The disposition of a pharmaceutical compound within an organism, i.e. its Absorption, Distribution, Metabolism, Excretion, Toxicity (ADMET) properties and adverse effects, critically affects late stage failure of drug candidates and has led to the withdrawal of approved drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and ADMET or adverse effects, but this is limited by the size, quality, and heterogeneity of the data available from individual sources...
2016: Journal of Cheminformatics
Sunghwan Kim, Paul A Thiessen, Tiejun Cheng, Bo Yu, Benjamin A Shoemaker, Jiyao Wang, Evan E Bolton, Yanli Wang, Stephen H Bryant
BACKGROUND: PubChem is an open archive consisting of a set of three primary public databases (BioAssay, Compound, and Substance). It contains information on a broad range of chemical entities, including small molecules, lipids, carbohydrates, and (chemically modified) amino acid and nucleic acid sequences (including siRNA and miRNA). Currently (as of Nov. 2015), PubChem contains more than 150 million depositor-provided chemical substance descriptions, 60 million unique chemical structures, and 225 million biological activity test results provided from over 1 million biological assay records...
2016: Journal of Cheminformatics
Jakub Galgonek, Tomáš Hurt, Vendula Michlíková, Petr Onderka, Jan Schwarz, Jiří Vondrášek
BACKGROUND: In recent years, the Resource Description Framework (RDF) and the SPARQL query language have become more widely used in the area of cheminformatics and bioinformatics databases. These technologies allow better interoperability of various data sources and powerful searching facilities. However, we identified several deficiencies that make usage of such RDF databases restrictive or challenging for common users. RESULTS: We extended a SPARQL engine to be able to use special procedures inside SPARQL queries...
2016: Journal of Cheminformatics
Jean-Paul Ebejer, Michael H Charlton, Paul W Finn
BACKGROUND: It is now widely recognized that there is an urgent need for new antibacterial drugs, with novel mechanisms of action, to combat the rise of multi-drug resistant bacteria. However, few new compounds are reaching the market. Antibacterial drug discovery projects often succeed in identifying potent molecules in biochemical assays but have been beset by difficulties in obtaining antibacterial activity. A commonly held view, based on analysis of marketed antibacterial compounds, is that antibacterial drugs possess very different physicochemical properties to other drugs, and that this profile is required for antibacterial activity...
2016: Journal of Cheminformatics
Jeremy J Yang, Oleg Ursu, Christopher A Lipinski, Larry A Sklar, Tudor I Oprea, Cristian G Bologa
BACKGROUND: Bioassay data analysis continues to be an essential, routine, yet challenging task in modern drug discovery and chemical biology research. The challenge is to infer reliable knowledge from big and noisy data. Some aspects of this problem are general with solutions informed by existing and emerging data science best practices. Some aspects are domain specific, and rely on expertise in bioassay methodology and chemical biology. Testing compounds for biological activity requires complex and innovative methodology, producing results varying widely in accuracy, precision, and information content...
2016: Journal of Cheminformatics
Gergely Zahoránszky-Kőhalmi, Cristian G Bologa, Oleg Ursu, Tudor I Oprea
[This corrects the article DOI: 10.1186/s13321-016-0127-5.].
2016: Journal of Cheminformatics
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