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Journal of Cheminformatics

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https://www.readbyqxmd.com/read/29349513/3d-qsar-study-of-steroidal-and-azaheterocyclic-human-aromatase-inhibitors-using-quantitative-profile-of-protein-ligand-interactions
#1
Sehan Lee, Mace G Barron
Aromatase is a member of the cytochrome P450 superfamily responsible for a key step in the biosynthesis of estrogens. As estrogens are involved in the control of important reproduction-related processes, including sexual differentiation and maturation, aromatase is a potential target for endocrine disrupting chemicals as well as breast cancer therapy. In this work, 3D-QSAR combined with quantitative profile of protein-ligand interactions was employed in the identification and characterization of critical steric and electronic features of aromatase-inhibitor complexes and the estimation of their quantitative contribution to inhibition potency...
January 18, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29340790/an-automated-framework-for-qsar-model-building
#2
Samina Kausar, Andre O Falcao
BACKGROUND: In-silico quantitative structure-activity relationship (QSAR) models based tools are widely used to screen huge databases of compounds in order to determine the biological properties of chemical molecules based on their chemical structure. With the passage of time, the exponentially growing amount of synthesized and known chemicals data demands computationally efficient automated QSAR modeling tools, available to researchers that may lack extensive knowledge of machine learning modeling...
January 16, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29290010/computer-aided-design-of-multi-target-ligands-at-a1r-a2ar-and-pde10a-key-proteins-in-neurodegenerative-diseases
#3
Leen Kalash, Cristina Val, Jhonny Azuaje, María I Loza, Fredrik Svensson, Azedine Zoufir, Lewis Mervin, Graham Ladds, José Brea, Robert Glen, Eddy Sotelo, Andreas Bender
Compounds designed to display polypharmacology may have utility in treating complex diseases, where activity at multiple targets is required to produce a clinical effect. In particular, suitable compounds may be useful in treating neurodegenerative diseases by promoting neuronal survival in a synergistic manner via their multi-target activity at the adenosine A1 and A2A receptors (A1R and A2AR) and phosphodiesterase 10A (PDE10A), which modulate intracellular cAMP levels. Hence, in this work we describe a computational method for the design of synthetically feasible ligands that bind to A1 and A2A receptors and inhibit phosphodiesterase 10A (PDE10A), involving a retrosynthetic approach employing in silico target prediction and docking, which may be generally applicable to multi-target compound design at several target classes...
December 30, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29282592/systematic-exploration-of-multiple-drug-binding-sites
#4
Mónika Bálint, Norbert Jeszenői, István Horváth, David van der Spoel, Csaba Hetényi
BACKGROUND: Targets with multiple (prerequisite or allosteric) binding sites have an increasing importance in drug design. Experimental determination of atomic resolution structures of ligands weakly bound to multiple binding sites is often challenging. Blind docking has been widely used for fast mapping of the entire target surface for multiple binding sites. Reliability of blind docking is limited by approximations of hydration models, simplified handling of molecular flexibility, and imperfect search algorithms...
December 28, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29282565/hawkrank-a-new-scoring-function-for-protein-protein-docking-based-on-weighted-energy-terms
#5
Ting Feng, Fu Chen, Yu Kang, Huiyong Sun, Hui Liu, Dan Li, Feng Zhu, Tingjun Hou
Deciphering the structural determinants of protein-protein interactions (PPIs) is essential to gain a deep understanding of many important biological functions in the living cells. Computational approaches for the structural modeling of PPIs, such as protein-protein docking, are quite needed to complement existing experimental techniques. The reliability of a protein-protein docking method is dependent on the ability of the scoring function to accurately distinguish the near-native binding structures from a huge number of decoys...
December 28, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29260340/molecular-structures-enumeration-and-virtual-screening-in-the-chemical-space-with-retropath2-0
#6
Mathilde Koch, Thomas Duigou, Pablo Carbonell, Jean-Loup Faulon
BACKGROUND: Network generation tools coupled with chemical reaction rules have been mainly developed for synthesis planning and more recently for metabolic engineering. Using the same core algorithm, these tools apply a set of rules to a source set of compounds, stopping when a sink set of compounds has been produced. When using the appropriate sink, source and rules, this core algorithm can be used for a variety of applications beyond those it has been developed for. RESULTS: Here, we showcase the use of the open source workflow RetroPath2...
December 19, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29238891/can-human-experts-predict-solubility-better-than-computers
#7
Samuel Boobier, Anne Osbourn, John B O Mitchell
In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R2 of 0.706...
December 13, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29234984/bober-web-interface-to-the-base-of-bioisosterically-exchangeable-replacements
#8
Samo Lešnik, Blaž Škrlj, Nika Eržen, Urban Bren, Stanislav Gobec, Janez Konc, Dušanka Janežič
We describe a novel freely available web server Base of Bioisosterically Exchangeable Replacements (BoBER), which implements an interface to a database of bioisosteric and scaffold hopping replacements. Bioisosterism and scaffold hopping are key concepts in drug design and optimization, and can be defined as replacements of biologically active compound's fragments with other fragments to improve activity, reduce toxicity, change bioavailability or to diversify the scaffold space. Our web server enables fast and user-friendly searches for bioisosteric and scaffold replacements which were obtained by mining the whole Protein Data Bank...
December 12, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29185065/consensus-queries-in-ligand-based-virtual-screening-experiments
#9
Francois Berenger, Oanh Vu, Jens Meiler
BACKGROUND: In ligand-based virtual screening experiments, a known active ligand is used in similarity searches to find putative active compounds for the same protein target. When there are several known active molecules, screening using all of them is more powerful than screening using a single ligand. A consensus query can be created by either screening serially with different ligands before merging the obtained similarity scores, or by combining the molecular descriptors (i.e. chemical fingerprints) of those ligands...
November 28, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29185060/the-comptox-chemistry-dashboard-a-community-data-resource-for-environmental-chemistry
#10
Antony J Williams, Christopher M Grulke, Jeff Edwards, Andrew D McEachran, Kamel Mansouri, Nancy C Baker, Grace Patlewicz, Imran Shah, John F Wambaugh, Richard S Judson, Ann M Richard
Despite an abundance of online databases providing access to chemical data, there is increasing demand for high-quality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities. The U.S. Environmental Protection Agency's (EPA) web-based CompTox Chemistry Dashboard is addressing these needs by integrating diverse types of relevant domain data through a cheminformatics layer, built upon a database of curated substances linked to chemical structures...
November 28, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29168051/efficient-conformational-ensemble-generation-of-protein-bound-peptides
#11
Yumeng Yan, Di Zhang, Sheng-You Huang
Conformation generation of protein-bound peptides is critical for the determination of protein-peptide complex structures. Despite significant progress in conformer generation of small molecules, few methods have been developed for modeling protein-bound peptide conformations. Here, we have developed a fast de novo peptide modeling algorithm, referred to as MODPEP, for conformational sampling of protein-bound peptides. Given a sequence, MODPEP builds the peptide 3D structure from scratch by assembling amino acids or helix fragments based on constructed rotamer and helix libraries...
November 22, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29159598/etox-allies-an-automated-pipeline-for-linear-interaction-energy-based-simulations
#12
Luigi Capoferri, Marc van Dijk, Ariën S Rustenburg, Tsjerk A Wassenaar, Derk P Kooi, Eko A Rifai, Nico P E Vermeulen, Daan P Geerke
BACKGROUND: Computational methods to predict binding affinities of small ligands toward relevant biological (off-)targets are helpful in prioritizing the screening and synthesis of new drug candidates, thereby speeding up the drug discovery process. However, use of ligand-based approaches can lead to erroneous predictions when structural and dynamic features of the target substantially affect ligand binding. Free energy methods for affinity computation can include steric and electrostatic protein-ligand interactions, solvent effects, and thermal fluctuations, but often they are computationally demanding and require a high level of supervision...
November 21, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29143270/an-efficient-computer-aided-structural-elucidation-strategy-for-mixtures-using-an-iterative-dynamic-programming-algorithm
#13
Bo-Han Su, Meng-Yu Shen, Yeu-Chern Harn, San-Yuan Wang, Alioune Schurz, Chieh Lin, Olivia A Lin, Yufeng J Tseng
The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure elucidation (CASE) strategies seek to automatically propose a list of possible chemical structures in mixtures by utilizing chromatographic and spectroscopic methods. However, current CASE tools still cannot automatically solve structures for experienced natural product chemists...
November 15, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29138947/a-posteriori-metadata-from-automated-provenance-tracking-integration-of-aiida-and-tcod
#14
Andrius Merkys, Nicolas Mounet, Andrea Cepellotti, Nicola Marzari, Saulius Gražulis, Giovanni Pizzi
In order to make results of computational scientific research findable, accessible, interoperable and re-usable, it is necessary to decorate them with standardised metadata. However, there are a number of technical and practical challenges that make this process difficult to achieve in practice. Here the implementation of a protocol is presented to tag crystal structures with their computed properties, without the need of human intervention to curate the data. This protocol leverages the capabilities of AiiDA, an open-source platform to manage and automate scientific computational workflows, and the TCOD, an open-access database storing computed materials properties using a well-defined and exhaustive ontology...
November 14, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29086154/open-chemistry-restful-web-apis-json-nwchem-and-the-modern-web-application
#15
Marcus D Hanwell, Wibe A de Jong, Christopher J Harris
An end-to-end platform for chemical science research has been developed that integrates data from computational and experimental approaches through a modern web-based interface. The platform offers an interactive visualization and analytics environment that functions well on mobile, laptop and desktop devices. It offers pragmatic solutions to ensure that large and complex data sets are more accessible. Existing desktop applications/frameworks were extended to integrate with high-performance computing resources, and offer command-line tools to automate interaction-connecting distributed teams to this software platform on their own terms...
October 30, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29086216/chemotion-eln-an-open-source-electronic-lab-notebook-for-chemists-in-academia
#16
Pierre Tremouilhac, An Nguyen, Yu-Chieh Huang, Serhii Kotov, Dominic Sebastian Lütjohann, Florian Hübsch, Nicole Jung, Stefan Bräse
The development of an electronic lab notebook (ELN) for researchers working in the field of chemical sciences is presented. The web based application is available as an Open Source software that offers modern solutions for chemical researchers. The Chemotion ELN is equipped with the basic functionalities necessary for the acquisition and processing of chemical data, in particular the work with molecular structures and calculations based on molecular properties. The ELN supports planning, description, storage, and management for the routine work of organic chemists...
September 25, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29086079/erratum-to-the-chemistry-development-kit-cdk-v2-0-atom-typing-depiction-molecular-formulas-and-substructure-searching
#17
Egon L Willighagen, John W Mayfield, Jonathan Alvarsson, Arvid Berg, Lars Carlsson, Nina Jeliazkova, Stefan Kuhn, Tomáš Pluskal, Miquel Rojas-Chertó, Ola Spjuth, Gilleain Torrance, Chris T Evelo, Rajarshi Guha, Christoph Steinbeck
No abstract text is available yet for this article.
September 20, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29086076/scoria-a-python-module-for-manipulating-3d-molecular-data
#18
Patrick Ropp, Aaron Friedman, Jacob D Durrant
Third-party packages have transformed the Python programming language into a powerful computational-biology tool. Package installation is easy for experienced users, but novices sometimes struggle with dependencies and compilers. This presents a barrier that can hinder the otherwise broad adoption of new tools. We present Scoria, a Python package for manipulating three-dimensional molecular data. Unlike similar packages, Scoria requires no dependencies, compilation, or system-wide installation. One can incorporate the Scoria source code directly into their own programs...
September 18, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29086161/g-a-m-e-gpu-accelerated-mixture-elucidator
#19
Alioune Schurz, Bo-Han Su, Yi-Shu Tu, Tony Tsung-Yu Lu, Olivia A Lin, Yufeng J Tseng
GPU acceleration is useful in solving complex chemical information problems. Identifying unknown structures from the mass spectra of natural product mixtures has been a desirable yet unresolved issue in metabolomics. However, this elucidation process has been hampered by complex experimental data and the inability of instruments to completely separate different compounds. Fortunately, with current high-resolution mass spectrometry, one feasible strategy is to define this problem as extending a scaffold database with sidechains of different probabilities to match the high-resolution mass obtained from a high-resolution mass spectrum...
September 15, 2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29086092/a-review-of-parameters-and-heuristics-for-guiding-metabolic-pathfinding
#20
REVIEW
Sarah M Kim, Matthew I Peña, Mark Moll, George N Bennett, Lydia E Kavraki
Recent developments in metabolic engineering have led to the successful biosynthesis of valuable products, such as the precursor of the antimalarial compound, artemisinin, and opioid precursor, thebaine. Synthesizing these traditionally plant-derived compounds in genetically modified yeast cells introduces the possibility of significantly reducing the total time and resources required for their production, and in turn, allows these valuable compounds to become cheaper and more readily available. Most biosynthesis pathways used in metabolic engineering applications have been discovered manually, requiring a tedious search of existing literature and metabolic databases...
September 15, 2017: Journal of Cheminformatics
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