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Journal of Cheminformatics

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https://www.readbyqxmd.com/read/29777317/using-smiles-strings-for-the-description-of-chemical-connectivity-in-the-crystallography-open-database
#1
Miguel Quirós, Saulius Gražulis, Saulė Girdzijauskaitė, Andrius Merkys, Antanas Vaitkus
Computer descriptions of chemical molecular connectivity are necessary for searching chemical databases and for predicting chemical properties from molecular structure. In this article, the ongoing work to describe the chemical connectivity of entries contained in the Crystallography Open Database (COD) in SMILES format is reported. This collection of SMILES is publicly available for chemical (substructure) search or for any other purpose on an open-access basis, as is the COD itself. The conventions that have been followed for the representation of compounds that do not fit into the valence bond theory are outlined for the most frequently found cases...
May 18, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29740723/international-chemical-identifier-for-reactions-rinchi
#2
Guenter Grethe, Gerd Blanke, Hans Kraut, Jonathan M Goodman
The Reaction InChI (RInChI) extends the idea of the InChI, which provides a unique descriptor of molecular structures, towards reactions. Prototype versions of the RInChI have been available since 2011. The first official release (RInChI-V1.00), funded by the InChI Trust, is now available for download ( http://www.inchi-trust.org/downloads/ ). This release defines the format and generates hashed representations (RInChIKeys) suitable for database and web operations. The RInChI provides a concise description of the key data in chemical processes, and facilitates the manipulation and analysis of reaction data...
May 9, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29651663/finding-the-molecular-scaffold-of-nuclear-receptor-inhibitors-through-high-throughput-screening-based-on-proteochemometric-modelling
#3
Tianyi Qiu, Dingfeng Wu, Jingxuan Qiu, Zhiwei Cao
Nuclear receptors (NR) are a class of proteins that are responsible for sensing steroid and thyroid hormones and certain other molecules. In that case, NR have the ability to regulate the expression of specific genes and associated with various diseases, which make it essential drug targets. Approaches which can predict the inhibition ability of compounds for different NR target should be particularly helpful for drug development. In this study, proteochemometric modelling was introduced to analysis the bioactivity between chemical compounds and NR targets...
April 12, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29633047/krds-a-web-server-for-evaluating-drug-resistance-mutations-in-kinases-by-molecular-docking
#4
Aeri Lee, Seungpyo Hong, Dongsup Kim
Kinases are major targets of anti-cancer therapies owing to their importance in signaling processes that regulate cell growth and proliferation. However, drug resistance has emerged as a major obstacle to cancer therapy. Resistance to drugs has various underlying mechanisms, including the acquisition of mutations at drug binding sites and the resulting reduction in drug binding affinity. Therefore, the identification of mutations that are relevant to drug resistance may be useful to overcome this issue. We hypothesized that these mutations can be identified by combining recent advances in computational methods for protein structure modeling and ligand docking simulation...
April 10, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29623440/finding-the-k-best-synthesis-plans
#5
Rolf Fagerberg, Christoph Flamm, Rojin Kianian, Daniel Merkle, Peter F Stadler
In synthesis planning, the goal is to synthesize a target molecule from available starting materials, possibly optimizing costs such as price or environmental impact of the process. Current algorithmic approaches to synthesis planning are usually based on selecting a bond set and finding a single good plan among those induced by it. We demonstrate that synthesis planning can be phrased as a combinatorial optimization problem on hypergraphs by modeling individual synthesis plans as directed hyperpaths embedded in a hypergraph of reactions (HoR) representing the chemistry of interest...
April 5, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29616425/a-confidence-predictor-for-logd-using-conformal-regression-and-a-support-vector-machine
#6
Maris Lapins, Staffan Arvidsson, Samuel Lampa, Arvid Berg, Wesley Schaal, Jonathan Alvarsson, Ola Spjuth
Lipophilicity is a major determinant of ADMET properties and overall suitability of drug candidates. We have developed large-scale models to predict water-octanol distribution coefficient (logD) for chemical compounds, aiding drug discovery projects. Using ACD/logD data for 1.6 million compounds from the ChEMBL database, models are created and evaluated by a support-vector machine with a linear kernel using conformal prediction methodology, outputting prediction intervals at a specified confidence level. The resulting model shows a predictive ability of [Formula: see text] and with the best performing nonconformity measure having median prediction interval of [Formula: see text] log units at 80% confidence and [Formula: see text] log units at 90% confidence...
April 3, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29616364/the-dye-sensitized-solar-cell-database
#7
Vishwesh Venkatraman, Rajesh Raju, Solon P Oikonomopoulos, Bjørn K Alsberg
BACKGROUND: Dye-sensitized solar cells (DSSCs) have garnered a lot of attention in recent years. The solar energy to power conversion efficiency of a DSSC is influenced by various components of the cell such as the dye, electrolyte, electrodes and additives among others leading to varying experimental configurations. A large number of metal-based and metal-free dye sensitizers have now been reported and tools using such data to indicate new directions for design and development are on the rise...
April 3, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29556758/pybiomed-a-python-library-for-various-molecular-representations-of-chemicals-proteins-and-dnas-and-their-interactions
#8
Jie Dong, Zhi-Jiang Yao, Lin Zhang, Feijun Luo, Qinlu Lin, Ai-Ping Lu, Alex F Chen, Dong-Sheng Cao
BACKGROUND: With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important...
March 20, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29549526/a-novel-interaction-fingerprint-derived-from-per-atom-score-contributions-exhaustive-evaluation-of-interaction-fingerprint-performance-in-docking-based-virtual-screening
#9
Julia B Jasper, Lina Humbeck, Tobias Brinkjost, Oliver Koch
Protein ligand interaction fingerprints are a powerful approach for the analysis and assessment of docking poses to improve docking performance in virtual screening. In this study, a novel interaction fingerprint approach (PADIF, protein per atom score contributions derived interaction fingerprint) is presented which was specifically designed for utilising the GOLD scoring functions' atom contributions together with a specific scoring scheme. This allows the incorporation of known protein-ligand complex structures for a target-specific scoring...
March 16, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29546548/reply-to-the-comment-made-by-%C3%A5-icho-vor%C3%A5-il%C3%A3-k-and-svozil-on-the-power-metric-a-new-statistically-robust-enrichment-type-metric-for-virtual-screening-applications-with-early-recovery-capability
#10
LETTER
https://www.readbyqxmd.com/read/29546531/comment-on-the-power-metric-a-new-statistically-robust-enrichment-type-metric-for-virtual-screening-applications-with-early-recovery-capability
#11
LETTER
M Šícho, M Voršilák, D Svozil
No abstract text is available yet for this article.
March 15, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29524042/automated-reaction-database-and-reaction-network-analysis-extraction-of-reaction-templates-using-cheminformatics
#12
Pieter P Plehiers, Guy B Marin, Christian V Stevens, Kevin M Van Geem
Both the automated generation of reaction networks and the automated prediction of synthetic trees require, in one way or another, the definition of possible transformations a molecule can undergo. One way of doing this is by using reaction templates. In view of the expanding amount of known reactions, it has become more and more difficult to envision all possible transformations that could occur in a studied system. Nonetheless, most reaction network generation tools rely on user-defined reaction templates...
March 9, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29524011/hivproti-an-integrated-web-based-platform-for-prediction-and-design-of-hiv-proteins-inhibitors
#13
Abid Qureshi, Akanksha Rajput, Gazaldeep Kaur, Manoj Kumar
A number of anti-retroviral drugs are being used for treating Human Immunodeficiency Virus (HIV) infection. Due to emergence of drug resistant strains, there is a constant quest to discover more effective anti-HIV compounds. In this endeavor, computational tools have proven useful in accelerating drug discovery. Although methods were published to design a class of compounds against a specific HIV protein, but an integrated web server for the same is lacking. Therefore, we have developed support vector machine based regression models using experimentally validated data from ChEMBL repository...
March 9, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29520515/opera-models-for-predicting-physicochemical-properties-and-environmental-fate-endpoints
#14
Kamel Mansouri, Chris M Grulke, Richard S Judson, Antony J Williams
The collection of chemical structure information and associated experimental data for quantitative structure-activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes...
March 8, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29516311/spectrophores-as-one-dimensional-descriptors-calculated-from-three-dimensional-atomic-properties-applications-ranging-from-scaffold-hopping-to-multi-target-virtual-screening
#15
Rafaela Gladysz, Fabio Mendes Dos Santos, Wilfried Langenaeker, Gert Thijs, Koen Augustyns, Hans De Winter
Spectrophores are novel descriptors that are calculated from the three-dimensional atomic properties of molecules. In our current implementation, the atomic properties that were used to calculate spectrophores include atomic partial charges, atomic lipophilicity indices, atomic shape deviations and atomic softness properties. This approach can easily be widened to also include additional atomic properties. Our novel methodology finds its roots in the experimental affinity fingerprinting technology developed in the 1990's by Terrapin Technologies...
March 7, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29492726/efficient-iterative-virtual-screening-with-apache-spark-and-conformal-prediction
#16
Laeeq Ahmed, Valentin Georgiev, Marco Capuccini, Salman Toor, Wesley Schaal, Erwin Laure, Ola Spjuth
BACKGROUND: Docking and scoring large libraries of ligands against target proteins forms the basis of structure-based virtual screening. The problem is trivially parallelizable, and calculations are generally carried out on computer clusters or on large workstations in a brute force manner, by docking and scoring all available ligands. CONTRIBUTION: In this study we propose a strategy that is based on iteratively docking a set of ligands to form a training set, training a ligand-based model on this set, and predicting the remainder of the ligands to exclude those predicted as 'low-scoring' ligands...
March 1, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29468427/maximizing-gain-in-high-throughput-screening-using-conformal-prediction
#17
Fredrik Svensson, Avid M Afzal, Ulf Norinder, Andreas Bender
Iterative screening has emerged as a promising approach to increase the efficiency of screening campaigns compared to traditional high throughput approaches. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models, resulting in more efficient screening. One way to evaluate screening is to consider the cost of screening compared to the gain associated with finding an active compound. In this work, we introduce a conformal predictor coupled with a gain-cost function with the aim to maximise gain in iterative screening...
February 21, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29464421/two-inhibitors-of-yeast-plasma-membrane-atpase-1-scpma1p-toward-the-development-of-novel-antifungal-therapies
#18
Sabine Ottilie, Gregory M Goldgof, Andrea L Cheung, Jennifer L Walker, Edgar Vigil, Kenneth E Allen, Yevgeniya Antonova-Koch, Carolyn W Slayman, Yo Suzuki, Jacob D Durrant
Given that many antifungal medications are susceptible to evolved resistance, there is a need for novel drugs with unique mechanisms of action. Inhibiting the essential proton pump Pma1p, a P-type ATPase, is a potentially effective therapeutic approach that is orthogonal to existing treatments. We identify NSC11668 and hitachimycin as structurally distinct antifungals that inhibit yeast ScPma1p. These compounds provide new opportunities for drug discovery aimed at this important target.
February 20, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29427195/key-features-and-updates-for-origin-2018
#19
REVIEW
James G Moberly, Matthew T Bernards, Kristopher V Waynant
OriginLab's newest version update to Origin and OriginPro includes ease-of-use features, like Origin Central updates and creation of an App Center, as well as larger changes like the addition of Unicode characters, alteration to how user files are stored and visually searched, and user input formula in cells within worksheets. These features add additional value to an already powerful data analysis and plotting software package.
February 9, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29411163/mordred-a-molecular-descriptor-calculator
#20
Hirotomo Moriwaki, Yu-Shi Tian, Norihito Kawashita, Tatsuya Takagi
Molecular descriptors are widely employed to present molecular characteristics in cheminformatics. Various molecular-descriptor-calculation software programs have been developed. However, users of those programs must contend with several issues, including software bugs, insufficient update frequencies, and software licensing constraints. To address these issues, we propose Mordred, a developed descriptor-calculation software application that can calculate more than 1800 two- and three-dimensional descriptors...
February 6, 2018: Journal of Cheminformatics
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