Articles

A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications

The quality of data used for QSAR model derivation is extremely important as it strongly affects the final robustness and predictive power of the model. Ambiguous or wrong structures need to be carefully check...

Authors: Domenico Gadaleta, Anna Lombardo, Cosimo Toma and Emilio Benfenati

Chemlistem: chemical named entity recognition using recurrent neural networks

Chemical named entity recognition (NER) has traditionally been dominated by conditional random fields (CRF)-based approaches but given the success of the artificial neural network techniques known as “deep lea...

Authors: Peter Corbett and John Boyle

MER: a shell script and annotation server for minimal named entity recognition and linking

Named-entity recognition aims at identifying the fragments of text that mention entities of interest, that afterwards could be linked to a knowledge base where those entities are described. This manuscript pre...

Authors: Francisco M. Couto and Andre Lamurias

chemmodlab: a cheminformatics modeling laboratory R package for fitting and assessing machine learning models

The goal of chemmodlab is to streamline the fitting and assessment pipeline for many machine learning models in R, making it easy for researchers to compare the utility of these models. While focused on implem...

Authors: Jeremy R. Ash and Jacqueline M. Hughes-Oliver

Implicit-descriptor ligand-based virtual screening by means of collaborative filtering

Current ligand-based machine learning methods in virtual screening rely heavily on molecular fingerprinting for preprocessing, i.e., explicit description of ligands’ structural and physicochemical properties i...

Authors: Raghuram Srinivas, Pavel V. Klimovich and Eric C. Larson

Statistical-based database fingerprint: chemical space dependent representation of compound databases

Simplified representation of compound databases has several applications in cheminformatics. Herein, we introduce an alternative and general method to build single fingerprint representations of compound datab...

Authors: Norberto Sánchez-Cruz and José L. Medina-Franco

Improved understanding of aqueous solubility modeling through topological data analysis

Topological data analysis is a family of recent mathematical techniques seeking to understand the ‘shape’ of data, and has been used to understand the structure of the descriptor space produced from a standard...

Authors: Mariam Pirashvili, Lee Steinberg, Francisco Belchi Guillamon, Mahesan Niranjan, Jeremy G. Frey and Jacek Brodzki

Cheminformatics-based enumeration and analysis of large libraries of macrolide scaffolds

We report on the development of a cheminformatics enumeration technology and the analysis of a resulting large dataset of virtual macrolide scaffolds. Although macrolides have been shown to have valuable biolo...

Authors: Phyo Phyo Kyaw Zin, Gavin Williams and Denis Fourches

An automated framework for NMR chemical shift calculations of small organic molecules

When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typicall...

Authors: Yasemin Yesiltepe, Jamie R. Nuñez, Sean M. Colby, Dennis G. Thomas, Mark I. Borkum, Patrick N. Reardon, Nancy M. Washton, Thomas O. Metz, Justin G. Teeguarden, Niranjan Govind and Ryan S. Renslow

Choquet integral-based fuzzy molecular characterizations: when global definitions are computed from the dependency among atom/bond contributions (LOVIs/LOEIs)

Several topological (2D) and geometric (3D) molecular descriptors (MDs) are calculated from local vertex/edge invariants (LOVIs/LOEIs) by performing an aggregation process. To this end, norm-, mean- and statis...

Authors: César R. García-Jacas, Lisset Cabrera-Leyva, Yovani Marrero-Ponce, José Suárez-Lezcano, Fernando Cortés-Guzmán, Mario Pupo-Meriño and Ricardo Vivas-Reyes

A new chemoinformatics approach with improved strategies for effective predictions of potential drugs

Fast and accurate identification of potential drug candidates against therapeutic targets (i.e., drug–target interactions, DTIs) is a fundamental step in the early drug discovery process. However, experimental...

Authors: Ming Hao, Stephen H. Bryant and Yanli Wang

Evaluating parameters for ligand-based modeling with random forest on sparse data sets

Ligand-based predictive modeling is widely used to generate predictive models aiding decision making in e.g. drug discovery projects. With growing data sets and requirements on low modeling time comes the nece...

Authors: Alexander Kensert, Jonathan Alvarsson, Ulf Norinder and Ola Spjuth

Life beyond the Tanimoto coefficient: similarity measures for interaction fingerprints

Interaction fingerprints (IFP) have been repeatedly shown to be valuable tools in virtual screening to identify novel hit compounds that can subsequently be optimized to drug candidates. As a complementary met...

Authors: Anita Rácz, Dávid Bajusz and Károly Héberger

Exploring non-linear distance metrics in the structure–activity space: QSAR models for human estrogen receptor

Quantitative structure-activity relationship (QSAR) models are important tools used in discovering new drug candidates and identifying potentially harmful environmental chemicals. These models often face two f...

Authors: Ilya A. Balabin and Richard S. Judson

Novel applications of Machine Learning in cheminformatics

Authors: Ola Spjuth

“MS-Ready” structures for non-targeted high-resolution mass spectrometry screening studies

Chemical database searching has become a fixture in many non-targeted identification workflows based on high-resolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS does...

Authors: Andrew D. McEachran, Kamel Mansouri, Chris Grulke, Emma L. Schymanski, Christoph Ruttkies and Antony J. Williams

The influence of solid state information and descriptor selection on statistical models of temperature dependent aqueous solubility

Predicting the equilibrium solubility of organic, crystalline materials at all relevant temperatures is crucial to the digital design of manufacturing unit operations in the chemical industries. The work repor...

Authors: Richard L. Marchese Robinson, Kevin J. Roberts and Elaine B. Martin

Machine learning for the prediction of molecular dipole moments obtained by density functional theory

Machine learning (ML) algorithms were explored for the fast estimation of molecular dipole moments calculated by density functional theory (DFT) by B3LYP/6-31G(d,p) on the basis of molecular descriptors genera...

Authors: Florbela Pereira and João Aires-de-Sousa

Probing the chemical–biological relationship space with the Drug Target Explorer

Modern phenotypic high-throughput screens (HTS) present several challenges including identifying the target(s) that mediate the effect seen in the screen, characterizing ‘hits’ with a polypharmacologic target ...

Authors: Robert J. Allaway, Salvatore La Rosa, Justin Guinney and Sara J. C. Gosline

Ambit-SMIRKS: a software module for reaction representation, reaction search and structure transformation

Ambit-SMIRKS is an open source software, enabling structure transformation via the SMIRKS language and implemented as an extension of Ambit-SMARTS. As part of the Ambit project it builds on top of The Chemistr...

Authors: Nikolay Kochev, Svetlana Avramova and Nina Jeliazkova

Predictive classification models and targets identification for betulin derivatives as Leishmania donovani inhibitors

Betulin derivatives have been proven effective in vitro against Leishmania donovani amastigotes, which cause visceral leishmaniasis. Identifying the molecular targets and molecular mechanisms underlying their act...

Authors: Yuezhou Zhang, Henri Xhaard and Leo Ghemtio

P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure

Ligand binding site prediction from protein structure has many applications related to elucidation of protein function and structure based drug discovery. It often represents only one step of many in complex c...

Authors: Radoslav Krivák and David Hoksza

Annotation and detection of drug effects in text for pharmacovigilance

Pharmacovigilance (PV) databases record the benefits and risks of different drugs, as a means to ensure their safe and effective use. Creating and maintaining such resources can be complex, since a particular ...

Authors: Paul Thompson, Sophia Daikou, Kenju Ueno, Riza Batista-Navarro, Jun’ichi Tsujii and Sophia Ananiadou

Chemotion-ELN part 2: adaption of an embedded Ketcher editor to advanced research applications

The Ketcher editor, available as an Open Source software package for drawing chemical structures, has been expanded to include several features that allow storage, management and application of templates, as w...

Authors: Serhii Kotov, Pierre Tremouilhac, Nicole Jung and Stefan Bräse

PubChem chemical structure standardization

PubChem is a chemical information repository, consisting of three primary databases: Substance, Compound, and BioAssay. When individual data contributors submit chemical substance descriptions to Substance, th...

Authors: Volker D. Hähnke, Sunghwan Kim and Evan E. Bolton

SPICES: a particle-based molecular structure line notation and support library for mesoscopic simulation

Simplified Particle Input ConnEction Specification (SPICES) is a particle-based molecular structure representation derived from straightforward simplifications of the atom-based SMILES line notation. It aims a...

Authors: Karina van den Broek, Mirco Daniel, Matthias Epple, Hubert Kuhn, Jonas Schaub and Achim Zielesny

HAMdb: a database of human autophagy modulators with specific pathway and disease information

Autophagy is an important homeostatic cellular recycling mechanism responsible for degrading unnecessary or dysfunctional cellular organelles and proteins in all living cells. In addition to its vital homeosta...

Authors: Ning-Ning Wang, Jie Dong, Lin Zhang, Defang Ouyang, Yan Cheng, Alex F. Chen, Ai-Ping Lu and Dong-Sheng Cao

Multi-objective de novo drug design with conditional graph generative model

Recently, deep generative models have revealed itself as a promising way of performing de novo molecule design. However, previous research has focused mainly on generating SMILES strings instead of molecular g...

Authors: Yibo Li, Liangren Zhang and Zhenming Liu

Novel pharmacological maps of protein lysine methyltransferases: key for target deorphanization

Epigenetic therapies are being investigated for the treatment of cancer, cognitive disorders, metabolic alterations and autoinmune diseases. Among the different epigenetic target families, protein lysine methy...

Authors: Obdulia Rabal, Andrea Castellar and Julen Oyarzabal

Molecular generative model based on conditional variational autoencoder for de novo molecular design

We propose a molecular generative model based on the conditional variational autoencoder for de novo molecular design. It is specialized to control multiple molecular properties simultaneously by imposing them...

Authors: Jaechang Lim, Seongok Ryu, Jin Woo Kim and Woo Youn Kim

ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R...

Authors: Jie Dong, Ning-Ning Wang, Zhi-Jiang Yao, Lin Zhang, Yan Cheng, Defang Ouyang, Ai-Ping Lu and Dong-Sheng Cao

Inferring potential small molecule–miRNA association based on triple layer heterogeneous network

Recently, many biological experiments have indicated that microRNAs (miRNAs) are a newly discovered small molecule (SM) drug targets that play an important role in the development and progression of human comp...

Authors: Jia Qu, Xing Chen, Ya-Zhou Sun, Jian-Qiang Li and Zhong Ming

Putting hands to rest: efficient deep CNN-RNN architecture for chemical named entity recognition with no hand-crafted rules

Chemical named entity recognition (NER) is an active field of research in biomedical natural language processing. To facilitate the development of new and superior chemical NER systems, BioCreative released th...

Authors: Ilia Korvigo, Maxim Holmatov, Anatolii Zaikovskii and Mikhail Skoblov

Sachem: a chemical cartridge for high-performance substructure search

Structure search is one of the valuable capabilities of small-molecule databases. Fingerprint-based screening methods are usually employed to enhance the search performance by reducing the number of calls to t...

Authors: Miroslav Kratochvíl, Jiří Vondrášek and Jakub Galgonek

Effect of missing data on multitask prediction methods

There has been a growing interest in multitask prediction in chemoinformatics, helped by the increasing use of deep neural networks in this field. This technique is applied to multitarget data sets, where comp...

Authors: Antonio de la Vega de León, Beining Chen and Valerie J. Gillet

RepTB: a gene ontology based drug repurposing approach for tuberculosis

Tuberculosis (TB) is the world’s leading infectious killer with 1.8 million deaths in 2015 as reported by WHO. It is therefore imperative that alternate routes of identification of novel anti-TB compounds are ...

Authors: Anurag Passi, Neeraj Kumar Rajput, David J. Wild and Anshu Bhardwaj

Jdpd: an open java simulation kernel for molecular fragment dissipative particle dynamics

Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized ...

Authors: Karina van den Broek, Hubert Kuhn and Achim Zielesny

Using SMILES strings for the description of chemical connectivity in the Crystallography Open Database

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 des...

Authors: Miguel Quirós, Saulius Gražulis, Saulė Girdzijauskaitė, Andrius Merkys and Antanas Vaitkus

International chemical identifier for reactions (RInChI)

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 fi...

Authors: Guenter Grethe, Gerd Blanke, Hans Kraut and Jonathan M. Goodman

Finding the molecular scaffold of nuclear receptor inhibitors through high-throughput screening based on proteochemometric modelling

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 specifi...

Authors: Tianyi Qiu, Dingfeng Wu, Jingxuan Qiu and Zhiwei Cao

KRDS: a web server for evaluating drug resistance mutations in kinases by molecular docking

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 canc...

Authors: Aeri Lee, Seungpyo Hong and Dongsup Kim

Finding the K best synthesis plans

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 approac...

Authors: Rolf Fagerberg, Christoph Flamm, Rojin Kianian, Daniel Merkle and Peter F. Stadler

A confidence predictor for logD using conformal regression and a support-vector machine

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 c...

Authors: Maris Lapins, Staffan Arvidsson, Samuel Lampa, Arvid Berg, Wesley Schaal, Jonathan Alvarsson and Ola Spjuth

The dye-sensitized solar cell database

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, e...

Authors: Vishwesh Venkatraman, Rajesh Raju, Solon P. Oikonomopoulos and Bjørn K. Alsberg

PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions

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 b...

Authors: Jie Dong, Zhi-Jiang Yao, Lin Zhang, Feijun Luo, Qinlu Lin, Ai-Ping Lu, Alex F. Chen and Dong-Sheng Cao

A novel interaction fingerprint derived from per atom score contributions: exhaustive evaluation of interaction fingerprint performance in docking based virtual screening

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 fingerpr...

Authors: Julia B. Jasper, Lina Humbeck, Tobias Brinkjost and Oliver Koch

Comment on “The power metric: a new statistically robust enrichment-type metric for virtual screening applications with early recovery capability”

Authors: M. Šícho, M. Voršilák and D. Svozil

Reply to the comment made by Šicho, Vorśilák and Svozil on ‘The Power metric: a new statistically robust enrichment-type metric for virtual screening applications with early recovery capability’

Authors: Hans De Winter and Julio Cesar Dias Lopes

HIVprotI: an integrated web based platform for prediction and design of HIV proteins inhibitors

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...

Authors: Abid Qureshi, Akanksha Rajput, Gazaldeep Kaur and Manoj Kumar

Automated reaction database and reaction network analysis: extraction of reaction templates using cheminformatics

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 ...

Authors: Pieter P. Plehiers, Guy B. Marin, Christian V. Stevens and Kevin M. Van Geem