Articles

Software solutions for evaluation and visualization of laser ablation inductively coupled plasma mass spectrometry imaging (LA-ICP-MSI) data: a short overview

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 ...

Authors: Ralf Weiskirchen, Sabine Weiskirchen, Philipp Kim and Robert Winkler

Identification of novel small molecule inhibitors for solute carrier SGLT1 using proteochemometric modeling

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...

Authors: Lindsey Burggraaff, Paul Oranje, Robin Gouka, Pieter van der Pijl, Marian Geldof, Herman W. T. van Vlijmen, Adriaan P. IJzerman and Gerard J. P. van Westen

Dimorphite-DL: an open-source program for enumerating the ionization states of drug-like small molecules

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, researche...

Authors: Patrick J. Ropp, Jesse C. Kaminsky, Sara Yablonski and Jacob D. Durrant

rBAN: retro-biosynthetic analysis of nonribosomal peptides

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 bioa...

Authors: Emma Ricart, Valérie Leclère, Areski Flissi, Markus Mueller, Maude Pupin and Frédérique Lisacek

Implementing cheminformatics

Authors: Rajarshi Guha

Programming languages in chemistry: a review of HTML5/JavaScript

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 chemis...

Authors: Kevin J. Theisen

Chemoinformatics and structural bioinformatics in OCaml

OCaml is a functional programming language with strong static types, Hindley–Milner type inference and garbage collection. In this article, we share our experience in prototyping chemoinformatics and structura...

Authors: Francois Berenger, Kam Y. J. Zhang and Yoshihiro Yamanishi

Avoiding hERG-liability in drug design via synergetic combinations of different (Q)SAR methodologies and data sources: a case study in an industrial setting

In this paper, we explore the impact of combining different in silico prediction approaches and data sources on the predictive performance of the resulting system. We use inhibition of the hERG ion channel tar...

Authors: Thierry Hanser, Fabian P. Steinmetz, Jeffrey Plante, Friedrich Rippmann and Mireille Krier

The nature of ligand efficiency

Ligand efficiency is a widely used design parameter in drug discovery. It is calculated by scaling affinity by molecular size and has a nontrivial dependency on the concentration unit used to express affinity ...

Authors: Peter W. Kenny

OGER++: hybrid multi-type entity recognition

We present a text-mining tool for recognizing biomedical entities in scientific literature. OGER++ is a hybrid system for named entity recognition and concept recognition (linking), which combines a dictionary...

Authors: Lenz Furrer, Anna Jancso, Nicola Colic and Fabio Rinaldi

Universal nanohydrophobicity predictions using virtual nanoparticle library

To facilitate the development of new nanomaterials, especially nanomedicines, a novel computational approach was developed to precisely predict the hydrophobicity of gold nanoparticles (GNPs). The core of this...

Authors: Wenyi Wang, Xiliang Yan, Linlin Zhao, Daniel P. Russo, Shenqing Wang, Yin Liu, Alexander Sedykh, Xiaoli Zhao, Bing Yan and Hao Zhu

QBMG: quasi-biogenic molecule generator with deep recurrent neural network

Biogenic compounds are important materials for drug discovery and chemical biology. In this work, we report a quasi-biogenic molecule generator (QBMG) to compose virtual quasi-biogenic compound libraries by me...

Authors: Shuangjia Zheng, Xin Yan, Qiong Gu, Yuedong Yang, Yunfei Du, Yutong Lu and Jun Xu

Large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery

Structure–activity relationship modelling is frequently used in the early stage of drug discovery to assess the activity of a compound on one or several targets, and can also be used to assess the interaction ...

Authors: Nicolas Bosc, Francis Atkinson, Eloy Felix, Anna Gaulton, Anne Hersey and Andrew R. Leach

LSTMVoter: chemical named entity recognition using a conglomerate of sequence labeling tools

Chemical and biomedical named entity recognition (NER) is an essential preprocessing task in natural language processing. The identification and extraction of named entities from scientific articles is also attra...

Authors: Wahed Hemati and Alexander Mehler

BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification

A number of computational tools for metabolism prediction have been developed over the last 20 years to predict the structures of small molecules undergoing biological transformation or environmental degradati...

Authors: Yannick Djoumbou-Feunang, Jarlei Fiamoncini, Alberto Gil-de-la-Fuente, Russell Greiner, Claudine Manach and David S. Wishart

A retrosynthetic analysis algorithm implementation

The need for synthetic route design arises frequently in discovery-oriented chemistry organizations. While traditionally finding solutions to this problem has been the domain of human experts, several computat...

Authors: Ian A. Watson, Jibo Wang and Christos A. Nicolaou

Configurable web-services for biomedical document annotation

The need to efficiently find and extract information from the continuously growing biomedical literature has led to the development of various annotation tools aimed at identifying mentions of entities and rel...

Authors: Sérgio Matos

“We were here before the Web and hype…”: a brief history of and tribute to the Computational Chemistry List

The Computational Chemistry List is a mailing list, portal, and community which brings together people interested in computational chemistry, mostly practitioners. It was formed in 1991 and continues to exist ...

Authors: Frédéric Wieber, Alejandro Pisanty and Alexandre Hocquet

A probabilistic molecular fingerprint for big data settings

Among the various molecular fingerprints available to describe small organic molecules, extended connectivity fingerprint, up to four bonds (ECFP4) performs best in benchmarking drug analog recovery studies as...

Authors: Daniel Probst and Jean-Louis Reymond

A neural network approach to chemical and gene/protein entity recognition in patents

In biomedical research, patents contain the significant amount of information, and biomedical text mining has received much attention in patents recently. To accelerate the development of biomedical text minin...

Authors: Ling Luo, Zhihao Yang, Pei Yang, Yin Zhang, Lei Wang, Jian Wang and Hongfei Lin

Statistical principle-based approach for gene and protein related object recognition

The large number of chemical and pharmaceutical patents has attracted researchers doing biomedical text mining to extract valuable information such as chemicals, genes and gene products. To facilitate gene and...

Authors: Po-Ting Lai, Ming-Siang Huang, Ting-Hao Yang, Wen-Lian Hsu and Richard Tzong-Han Tsai

SIA: a scalable interoperable annotation server for biomedical named entities

Recent years showed a strong increase in biomedical sciences and an inherent increase in publication volume. Extraction of specific information from these sources requires highly sophisticated text mining and ...

Authors: Johannes Kirschnick, Philippe Thomas, Roland Roller and Leonhard Hennig

Chaos-embedded particle swarm optimization approach for protein-ligand docking and virtual screening

Protein-ligand docking programs are routinely used in structure-based drug design to find the optimal binding pose of a ligand in the protein’s active site. These programs are also used to identify potential d...

Authors: Hio Kuan Tai, Siti Azma Jusoh and Shirley W. I. Siu

JPlogP: an improved logP predictor trained using predicted data

The partition coefficient between octanol and water (logP) has been an important descriptor in QSAR predictions for many years and therefore the prediction of logP has been examined countless times. One of the...

Authors: Jeffrey Plante and Stephane Werner

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

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

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

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

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

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

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