Articles

ReactionCode: format for reaction searching, analysis, classification, transform, and encoding/decoding

In the past two decades a lot of different formats for molecules and reactions have been created. These formats were mostly developed for the purposes of identifiers, representation, classification, analysis a...

Authors: Victorien Delannée and Marc C. Nicklaus

A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19

Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sourc...

Authors: Alzbeta Tuerkova and Barbara Zdrazil

AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning

We present the open-source AiZynthFinder software that can be readily used in retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively breaks down a molecule to purchasable...

Authors: Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean-Louis Reymond, Ola Engkvist and Esben Bjerrum

LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates

Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predictin...

Authors: Emily J. Ha, Cara T. Lwin and Jacob D. Durrant

Memory-assisted reinforcement learning for diverse molecular de novo design

In de novo molecular design, recurrent neural networks (RNN) have been shown to be effective methods for sampling and generating novel chemical structures. Using a technique called reinforcement learning (RL),...

Authors: Thomas Blaschke, Ola Engkvist, Jürgen Bajorath and Hongming Chen

Too sweet: cheminformatics for deglycosylation in natural products

Sugar units in natural products are pharmacokinetically important but often redundant and therefore obstructing the study of the structure and function of the aglycon. Therefore, it is recommended to remove th...

Authors: Jonas Schaub, Achim Zielesny, Christoph Steinbeck and Maria Sorokina

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical class...

Authors: Gabriel Idakwo, Sundar Thangapandian, Joseph Luttrell, Yan Li, Nan Wang, Zhaoxian Zhou, Huixiao Hong, Bei Yang, Chaoyang Zhang and Ping Gong

DECIMER: towards deep learning for chemical image recognition

The automatic recognition of chemical structure diagrams from the literature is an indispensable component of workflows to re-discover information about chemicals and to make it available in open-access databa...

Authors: Kohulan Rajan, Achim Zielesny and Christoph Steinbeck

Chemoinformatics-based enumeration of chemical libraries: a tutorial

Virtual compound libraries are increasingly being used in computer-assisted drug discovery applications and have led to numerous successful cases. This paper aims to examine the fundamental concepts of library...

Authors: Fernanda I. Saldívar-González, C. Sebastian Huerta-García and José L. Medina-Franco

Predicting in silico electron ionization mass spectra using quantum chemistry

Compound identification by mass spectrometry needs reference mass spectra. While there are over 102 million compounds in PubChem, less than 300,000 curated electron ionization (EI) mass spectra are available f...

Authors: Shunyang Wang, Tobias Kind, Dean J. Tantillo and Oliver Fiehn

Predicting target profiles with confidence as a service using docking scores

Identifying and assessing ligand-target binding is a core component in early drug discovery as one or more unwanted interactions may be associated with safety issues.

Authors: Laeeq Ahmed, Hiba Alogheli, Staffan Arvidsson McShane, Jonathan Alvarsson, Arvid Berg, Anders Larsson, Wesley Schaal, Erwin Laure and Ola Spjuth

Maximum common property: a new approach for molecular similarity

The maximum common property similarity (MCPhd) method is presented using descriptors as a new approach to determine the similarity between two chemical compounds or molecular graphs. This method uses the conce...

Authors: Aurelio Antelo-Collado, Ramón Carrasco-Velar, Nicolás García-Pedrajas and Gonzalo Cerruela-García

A review of optical chemical structure recognition tools

Structural information about chemical compounds is typically conveyed as 2D images of molecular structures in scientific documents. Unfortunately, these depictions are not a machine-readable representation of ...

Authors: Kohulan Rajan, Henning Otto Brinkhaus, Achim Zielesny and Christoph Steinbeck

Correction to: The chemfp project

An amendment to this paper has been published and can be accessed via the original article.

Authors: Andrew Dalke

Compressed graph representation for scalable molecular graph generation

Recently, deep learning has been successfully applied to molecular graph generation. Nevertheless, mitigating the computational complexity, which increases with the number of nodes in a graph, has been a major...

Authors: Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Kyoham Shin and Seokho Kang

Linking chemical and disease entities to ontologies by integrating PageRank with extracted relations from literature

Named Entity Linking systems are a powerful aid to the manual curation of digital libraries, which is getting increasingly costly and inefficient due to the information overload. Models based on the Personaliz...

Authors: Pedro Ruas, Andre Lamurias and Francisco M. Couto

Molecular representations in AI-driven drug discovery: a review and practical guide

The technological advances of the past century, marked by the computer revolution and the advent of high-throughput screening technologies in drug discovery, opened the path to the computational analysis and v...

Authors: Laurianne David, Amol Thakkar, Rocío Mercado and Ola Engkvist

EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation

The objective of this work is to design a molecular generator capable of exploring known as well as unfamiliar areas of the chemical space. Our method must be flexible to adapt to very different problems. Ther...

Authors: Jules Leguy, Thomas Cauchy, Marta Glavatskikh, Béatrice Duval and Benoit Da Mota

Intuitive, reproducible high-throughput molecular dynamics in Galaxy: a tutorial

This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible an...

Authors: Simon A. Bray, Tharindu Senapathi, Christopher B. Barnett and Björn A. Grüning

DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach

We address the problem of generating novel molecules with desired interaction properties as a multi-objective optimization problem. Interaction binding models are learned from binding data using graph convolut...

Authors: Yash Khemchandani, Stephen O’Hagan, Soumitra Samanta, Neil Swainston, Timothy J. Roberts, Danushka Bollegala and Douglas B. Kell

CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration

In computer-assisted synthesis planning (CASP) programs, providing as many chemical synthetic routes as possible is essential for considering optimal and alternative routes in a chemical reaction network. As t...

Authors: Ryosuke Shibukawa, Shoichi Ishida, Kazuki Yoshizoe, Kunihiro Wasa, Kiyosei Takasu, Yasushi Okuno, Kei Terayama and Koji Tsuda

An open source chemical structure curation pipeline using RDKit

The ChEMBL database is one of a number of public databases that contain bioactivity data on small molecule compounds curated from diverse sources. Incoming compounds are typically not standardised according to...

Authors: A. Patrícia Bento, Anne Hersey, Eloy Félix, Greg Landrum, Anna Gaulton, Francis Atkinson, Louisa J. Bellis, Marleen De Veij and Andrew R. Leach

Neural machine translation of chemical nomenclature between English and Chinese

Machine translation of chemical nomenclature has considerable application prospect in chemical text data processing between languages. However, rule based machine translation tools have to face significant com...

Authors: Tingjun Xu, Weiming Chen, Junhong Zhou, Jingfang Dai, Yingyong Li and Yingli Zhao

spyrmsd: symmetry-corrected RMSD calculations in Python

Root mean square displacement (RMSD) calculations play a fundamental role in the comparison of different conformers of the same ligand. This is particularly important in the evaluation of protein-ligand dockin...

Authors: Rocco Meli and Philip C. Biggin

Atomic ring invariant and Modified CANON extended connectivity algorithm for symmetry perception in molecular graphs and rigorous canonicalization of SMILES

We propose new invariant (the product of the corresponding primes for the ring size of each bond of an atom) as a simple unambiguous ring invariant of an atom that allows distinguishing symmetry classes in the...

Authors: Dmytro G. Krotko

Adoption of the Citation Typing Ontology by the Journal of Cheminformatics

Authors: Egon Willighagen

A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions

Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in opti...

Authors: Tamer N. Jarada, Jon G. Rokne and Reda Alhajj

rMSIcleanup: an open-source tool for matrix-related peak annotation in mass spectrometry imaging and its application to silver-assisted laser desorption/ionization

Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyt...

Authors: Gerard Baquer, Lluc Sementé, María García-Altares, Young Jin Lee, Pierre Chaurand, Xavier Correig and Pere Ràfols

DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques

In silico prediction of drug–target interactions is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. How...

Authors: Maha A. Thafar, Rawan S. Olayan, Haitham Ashoor, Somayah Albaradei, Vladimir B. Bajic, Xin Gao, Takashi Gojobori and Magbubah Essack

One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome

Molecular fingerprints are essential cheminformatics tools for virtual screening and mapping chemical space. Among the different types of fingerprints, substructure fingerprints perform best for small molecule...

Authors: Alice Capecchi, Daniel Probst and Jean-Louis Reymond

Chemical space exploration based on recurrent neural networks: applications in discovering kinase inhibitors

With the rise of artificial intelligence (AI) in drug discovery, de novo molecular generation provides new ways to explore chemical space. However, because de novo molecular generation methods rely on abundant...

Authors: Xuanyi Li, Yinqiu Xu, Hequan Yao and Kejiang Lin

QSAR-derived affinity fingerprints (part 2): modeling performance for potency prediction

Affinity fingerprints report the activity of small molecules across a set of assays, and thus permit to gather information about the bioactivities of structurally dissimilar compounds, where models based on ch...

Authors: Isidro Cortés-Ciriano, Ctibor Škuta, Andreas Bender and Daniel Svozil

The ChemicalToolbox: reproducible, user-friendly cheminformatics analysis on the Galaxy platform

Here, we introduce the ChemicalToolbox, a publicly available web server for performing cheminformatics analysis. The ChemicalToolbox provides an intuitive, graphical interface for common tools for downloading,...

Authors: Simon A. Bray, Xavier Lucas, Anup Kumar and Björn A. Grüning

QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping

An affinity fingerprint is the vector consisting of compound’s affinity or potency against the reference panel of protein targets. Here, we present the QAFFP fingerprint, 440 elements long in silico QSAR-based...

Authors: C. Škuta, I. Cortés-Ciriano, W. Dehaen, P. Kříž, G. J. P. van Westen, I. V. Tetko, A. Bender and D. Svozil

SMILES-based deep generative scaffold decorator for de-novo drug design

Molecular generative models trained with small sets of molecules represented as SMILES strings can generate large regions of the chemical space. Unfortunately, due to the sequential nature of SMILES strings, t...

Authors: Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen and Ola Engkvist

EDock: blind protein–ligand docking by replica-exchange monte carlo simulation

Protein–ligand docking is an important approach for virtual screening and protein function annotation. Although many docking methods have been developed, most require a high-resolution crystal structure of the...

Authors: Wenyi Zhang, Eric W. Bell, Minghao Yin and Yang Zhang

Assessing the information content of structural and protein–ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning

For kinase inhibitors, X-ray crystallography has revealed different types of binding modes. Currently, more than 2000 kinase inhibitors with known binding modes are available, which makes it possible to derive...

Authors: Raquel Rodríguez-Pérez, Filip Miljković and Jürgen Bajorath

SYBA: Bayesian estimation of synthetic accessibility of organic compounds

SYBA (SYnthetic Bayesian Accessibility) is a fragment-based method for the rapid classification of organic compounds as easy- (ES) or hard-to-synthesize (HS). It is based on a Bernoulli naïve Bayes classifier ...

Authors: Milan Voršilák, Michal Kolář, Ivan Čmelo and Daniel Svozil

Activity landscape image analysis using convolutional neural networks

Activity landscapes (ALs) are graphical representations that combine compound similarity and activity data. ALs are constructed for visualizing local and global structure–activity relationships (SARs) containe...

Authors: Javed Iqbal, Martin Vogt and Jürgen Bajorath

Quantitative prediction of selectivity between the A₁ and A_2A adenosine receptors

The development of drugs is often hampered due to off-target interactions leading to adverse effects. Therefore, computational methods to assess the selectivity of ligands are of high interest. Currently, sele...

Authors: Lindsey Burggraaff, Herman W. T. van Vlijmen, Adriaan P. IJzerman and Gerard J. P. van Westen

kGCN: a graph-based deep learning framework for chemical structures

Deep learning is developing as an important technology to perform various tasks in cheminformatics. In particular, graph convolutional neural networks (GCNs) have been reported to perform well in many types of...

Authors: Ryosuke Kojima, Shoichi Ishida, Masateru Ohta, Hiroaki Iwata, Teruki Honma and Yasushi Okuno

The diatomic molecular spectroscopy database

The spectroscopy of diatomic molecules is an important research area in chemical physics due to its relevance in astrochemistry, combustion chemistry, and ultracold physics. However, there is currently no data...

Authors: Xiangyue Liu, Stefan Truppe, Gerard Meijer and Jesús Pérez-Ríos

Aromatic clusters in protein–protein and protein–drug complexes

Aromatic rings are important residues for biological interactions and appear to a large extent as part of protein–drug and protein–protein interactions. They are relevant for both protein stability and molecul...

Authors: Esteban Lanzarotti, Lucas A. Defelipe, Marcelo A. Marti and Adrián G. Turjanski

MFsim—an open Java all-in-one rich-client simulation environment for mesoscopic simulation

MFsim is an open Java all-in-one rich-client computing environment for mesoscopic simulation with Jdpd as its default simulation kernel for Molecular Fragment (Dissipative Particle) Dynamics. The new environme...

Authors: Karina van den Broek, Mirco Daniel, Matthias Epple, Jan-Mathis Hein, Hubert Kuhn, Stefan Neumann, Andreas Truszkowski and Achim Zielesny

CReM: chemically reasonable mutations framework for structure generation

Structure generators are widely used in de novo design studies and their performance substantially influences an outcome. Approaches based on the deep learning models and conventional atom-based approaches may...

Authors: Pavel Polishchuk

Inductive transfer learning for molecular activity prediction: Next-Gen QSAR Models with MolPMoFiT

Deep neural networks can directly learn from chemical structures without extensive, user-driven selection of descriptors in order to predict molecular properties/activities with high reliability. But these app...

Authors: Xinhao Li and Denis Fourches

Industry-scale application and evaluation of deep learning for drug target prediction

Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. ...

Authors: Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir Chupakhin, Hugo Ceulemans, Joerg Wegner, Jose-Felipe Golib-Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter…

AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization

We here present AutoGrow4, an open-source program for semi-automated computer-aided drug discovery. AutoGrow4 uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual l...

Authors: Jacob O. Spiegel and Jacob D. Durrant

KnowTox: pipeline and case study for confident prediction of potential toxic effects of compounds in early phases of development

Risk assessment of newly synthesised chemicals is a prerequisite for regulatory approval. In this context, in silico methods have great potential to reduce time, cost, and ultimately animal testing as they mak...

Authors: Andrea Morger, Miriam Mathea, Janosch H. Achenbach, Antje Wolf, Roland Buesen, Klaus-Juergen Schleifer, Robert Landsiedel and Andrea Volkamer

SIME: synthetic insight-based macrolide enumerator to generate the V1B library of 1 billion macrolides

We report on a new cheminformatics enumeration technology—SIME, synthetic insight-based macrolide enumerator—a new and improved software technology. SIME can enumerate fully assembled macrolides with synthetic...

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