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Journal of Cheminformatics

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
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
M Šícho, M Voršilák, D Svozil
No abstract text is available yet for this article.
March 15, 2018: Journal of Cheminformatics
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
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
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
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
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
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
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
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
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
George Van Den Driessche, Denis Fourches
BACKGROUND: Idiosyncratic adverse drug reactions have been linked to a drug's ability to bind with a human leukocyte antigen (HLA) protein. However, due to the thousands of HLA variants and limited structural data for drug-HLA complexes, predicting a specific drug-HLA combination represents a significant challenge. Recently, we investigated the binding mode of abacavir with the HLA-B*57:01 variant using molecular docking. Herein, we developed a new ensemble screening workflow involving three X-ray crystal derived docking procedures to screen the DrugBank database and identify potentially HLA-B*57:01 liable drugs...
January 30, 2018: Journal of Cheminformatics
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
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
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
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
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
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
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