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Journal of Cheminformatics

Domenico Gadaleta, Anna Lombardo, Cosimo Toma, Emilio Benfenati
It was highlighted that the original article [1] contained an error in the Funding section. This Correction article states the correct and incorrect versions of the Funding section.
April 25, 2019: Journal of Cheminformatics
Ankur Jai Sood, Coby Viner, Michael M Hoffman
Covalent DNA modifications, such as 5-methylcytosine (5mC), are increasingly the focus of numerous research programs. In eukaryotes, both 5mC and 5-hydroxymethylcytosine (5hmC) are now recognized as stable epigenetic marks, with diverse functions. Bacteria, archaea, and viruses contain various other modified DNA nucleobases. Numerous databases describe RNA and histone modifications, but no database specifically catalogues DNA modifications, despite their broad importance in epigenetic regulation. To address this need, we have developed DNAmod: the DNA modification database...
April 23, 2019: Journal of Cheminformatics
Jian-Yu Shi, Kui-Tao Mao, Hui Yu, Siu-Ming Yiu
BACKGROUND: Because drug-drug interactions (DDIs) may cause adverse drug reactions or contribute to complex-disease treatments, it is important to identify DDIs before multiple-drug medications are prescribed. As the alternative of high-cost experimental identifications, computational approaches provide a much cheaper screening for potential DDIs on a large scale manner. Nevertheless, most of them only predict whether or not one drug interacts with another, but neglect their enhancive (positive) and depressive (negative) changes of pharmacological effects...
April 8, 2019: Journal of Cheminformatics
Dominique Sydow, Andrea Morger, Maximilian Driller, Andrea Volkamer
Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for computer-aided drug design (CADD) is more and more built on modular, reproducible, and easy-to-share pipelines. While documentation for such tools is available, there are only a few freely accessible examples that teach the underlying concepts focused on CADD, especially addressing users new to the field. Here, we present TeachOpenCADD, a teaching platform developed by students for students, using open source compound and protein data as well as basic and CADD-related Python packages...
April 8, 2019: Journal of Cheminformatics
Kristijan Vukovic, Domenico Gadaleta, Emilio Benfenati
BACKGROUND: Several QSAR methodology developments have shown promise in recent years. These include the consensus approach to generate the final prediction of a model, utilizing new, advanced machine learning algorithms and streamlining, standardization and automation of various QSAR steps. One approach that seems under-explored is at-the-runtime generation of local models specific to individual compounds. This approach was quite likely limited by the computational requirements, but with current increases in processing power and the widespread availability of cluster-computing infrastructure, this limitation is no longer that severe...
April 3, 2019: Journal of Cheminformatics
Willem Jespers, Mauricio Esguerra, Johan Åqvist, Hugo Gutiérrez-de-Terán
The process of ligand binding to a biological target can be represented as the equilibrium between the relevant solvated and bound states of the ligand. This which is the basis of structure-based, rigorous methods such as the estimation of relative binding affinities by free energy perturbation (FEP). Despite the growing capacity of computing power and the development of more accurate force fields, a high throughput application of FEP is currently hampered due to the need, in the current schemes, of an expert user definition of the "alchemical" transformations between molecules in the series explored...
April 2, 2019: Journal of Cheminformatics
Daniela Kalafatovic, Goran Mauša, Toni Todorovski, Ernest Giralt
Random peptide libraries that cover large search spaces are often used for the discovery of new binders, even when the target is unknown. To ensure an accurate population representation, there is a tendency to use large libraries. However, parameters such as the synthesis scale, the number of library members, the sequence deconvolution and peptide structure elucidation, are challenging when increasing the library size. To tackle these challenges, we propose an algorithm-supported approach to peptide library design based on molecular mass and amino acid diversity...
March 28, 2019: Journal of Cheminformatics
Célien Jacquemard, Malgorzata N Drwal, Jérémy Desaphy, Esther Kellenberger
Docking is commonly used in drug discovery to predict how ligand binds to protein target. Best programs are generally able to generate a correct solution, yet often fail to identify it. In the case of drug-like molecules, the correct and incorrect poses can be sorted by similarity to the crystallographic structure of the protein in complex with reference ligands. Fragments are particularly sensitive to scoring problems because they are weak ligands which form few interactions with protein. In the present study, we assessed the utility of binding mode information in fragment pose prediction...
March 22, 2019: Journal of Cheminformatics
Samantha Kanza, Nicholas Gibbins, Jeremy G Frey
Scientific research is increasingly characterised by the volume of documents and data that it produces, from experimental plans and raw data to reports and papers. Researchers frequently struggle to manage and curate these materials, both individually and collectively. Previous studies of Electronic Lab Notebooks (ELNs) in academia and industry have identified semantic web technologies as a means for organising scientific documents to improve current workflows and knowledge management practices. In this paper, we present a qualitative, user-centred study of researcher requirements and practices, based on a series of discipline-specific focus groups...
March 21, 2019: Journal of Cheminformatics
Ying Shen, Kaiqi Yuan, Min Yang, Buzhou Tang, Yaliang Li, Nan Du, Kai Lei
Efficient representations of drugs provide important support for healthcare analytics, such as drug-drug interaction (DDI) prediction and drug-drug similarity (DDS) computation. However, incomplete annotated data and drug feature sparseness create substantial barriers for drug representation learning, making it difficult to accurately identify new drug properties prior to public release. To alleviate these deficiencies, we propose KMR, a knowledge-oriented feature-driven method which can learn drug related knowledge with an accurate representation...
March 14, 2019: Journal of Cheminformatics
Wahed Hemati, Alexander Mehler
BACKGROUND: Gene and protein related objects are an important class of entities in biomedical research, whose identification and extraction from scientific articles is attracting increasing interest. In this work, we describe an approach to the BioCreative V.5 challenge regarding the recognition and classification of gene and protein related objects. For this purpose, we transform the task as posed by BioCreative V.5 into a sequence labeling problem. We present a series of sequence labeling systems that we used and adapted in our experiments for solving this task...
March 14, 2019: Journal of Cheminformatics
Josep Arús-Pous, Thomas Blaschke, Silas Ulander, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
Recent applications of recurrent neural networks (RNN) enable training models that sample the chemical space. In this study we train RNN with molecular string representations (SMILES) with a subset of the enumerated database GDB-13 (975 million molecules). We show that a model trained with 1 million structures (0.1% of the database) reproduces 68.9% of the entire database after training, when sampling 2 billion molecules. We also developed a method to assess the quality of the training process using negative log-likelihood plots...
March 12, 2019: Journal of Cheminformatics
Sune Pletscher-Frankild, Lars Juhl Jensen
Most BioCreative tasks to date have focused on assessing the quality of text-mining annotations in terms of precision and recall. Interoperability, speed, and stability are, however, other important factors to consider for practical applications of text mining. For about a decade, we have run named entity recognition (NER) web services, which are designed to be efficient, implemented using a multi-threaded queueing system to robustly handle many simultaneous requests, and hosted at a supercomputer facility...
March 8, 2019: Journal of Cheminformatics
Ivan D Welsh, Jane R Allison
Bond orders and formal charges are fundamental chemical descriptors. In cheminformatic applications it is necessary to be able to assign these properties to a given molecular structure automatically, given minimal input information. Here we describe a method for determining the bond order and formal charge assignments from only the atom types and connectivity. Our method utilises a graph theoretical description of electron positions. Each electron position assignment is scored according to lookup tables of atomic and bond dissociation energies derived from quantum chemical calculations...
March 6, 2019: Journal of Cheminformatics
Sera Park, Yeajee Kwon, Hyesoo Jung, Sukyung Jang, Haeseung Lee, Wankyu Kim
Drug discovery typically involves investigation of a set of compounds (e.g. drug screening hits) in terms of target, disease, and bioactivity. CSgator is a comprehensive analytic tool for set-wise interpretation of compounds. It has two unique analytic features of Compound Set Enrichment Analysis (CSEA) and Compound Cluster Analysis (CCA), which allows batch analysis of compound set in terms of (i) target, (ii) bioactivity, (iii) disease, and (iv) structure. CSEA and CCA present enriched profiles of targets and bioactivities in a compound set, which leads to novel insights on underlying drug mode-of-action, and potential targets...
March 4, 2019: Journal of Cheminformatics
Ralf Weiskirchen, Sabine Weiskirchen, Philipp Kim, Robert Winkler
Mass spectrometry imaging (MSI) using laser ablation (LA) inductively coupled plasma (ICP) is an innovative and exciting methodology to perform highly sensitive elemental analyses. LA-ICP-MSI of metals, trace elements or isotopes in tissues has been applied to a range of biological samples. Several LA-ICP-MSI studies have shown that metals have a highly compartmentalized distribution in some organs, which might be altered in consequence of genetic diseases, intoxication, or malnutrition. Although metal imaging by LA-ICP-MSI is an established methodology, potential pitfalls in the determination of metal concentrations might result from erroneous calibration, standardization, and normalization...
February 18, 2019: Journal of Cheminformatics
Lindsey Burggraaff, Paul Oranje, Robin Gouka, Pieter van der Pijl, Marian Geldof, Herman W T van Vlijmen, Adriaan P IJzerman, Gerard J P van Westen
Sodium-dependent glucose co-transporter 1 (SGLT1) is a solute carrier responsible for active glucose absorption. SGLT1 is present in both the renal tubules and small intestine. In contrast, the closely related sodium-dependent glucose co-transporter 2 (SGLT2), a protein that is targeted in the treatment of diabetes type II, is only expressed in the renal tubules. Although dual inhibitors for both SGLT1 and SGLT2 have been developed, no drugs on the market are targeted at decreasing dietary glucose uptake by SGLT1 in the gastrointestinal tract...
February 14, 2019: Journal of Cheminformatics
Patrick J Ropp, Jesse C Kaminsky, Sara Yablonski, Jacob D Durrant
Small-molecule protonation can promote or discourage protein binding by altering hydrogen-bond, electrostatic, and van-der-Waals interactions. To improve virtual-screen pose and affinity predictions, researchers must account for all major small-molecule ionization states. But existing programs for calculating these states have notable limitations such as high cost, restrictive licenses, slow execution times, and poor modularity. Here, we present dimorphite-DL 1.0, a fast, accurate, accessible, and modular open-source program for enumerating small-molecule ionization states...
February 14, 2019: Journal of Cheminformatics
Emma Ricart, Valérie Leclère, Areski Flissi, Markus Mueller, Maude Pupin, Frédérique Lisacek
Proteinogenic and non-proteinogenic amino acids, fatty acids or glycans are some of the main building blocks of nonribsosomal peptides (NRPs) and as such may give insight into the origin, biosynthesis and bioactivities of their constitutive peptides. Hence, the structural representation of NRPs using monomers provides a biologically interesting skeleton of these secondary metabolites. Databases dedicated to NRPs such as Norine, already integrate monomer-based annotations in order to facilitate the development of structural analysis tools...
February 8, 2019: Journal of Cheminformatics
Kevin J Theisen
This is one part of a series of reviews concerning the application of programming languages in chemistry, edited by Dr. Rajarshi Guha. This article reviews the JavaScript technology as it applies to the chemistry discipline. A discussion of the history, scope and technical details of the programming language is presented.
February 5, 2019: Journal of Cheminformatics
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