Articles

LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds

Target prediction is a crucial step in modern drug discovery. However, existing experimental approaches to target prediction are time-consuming and costly. Here, we introduce LigTMap, an online server with a f...

Authors: Faraz Shaikh, Hio Kuan Tai, Nirali Desai and Shirley W. I. Siu

GNINA 1.0: molecular docking with deep learning

Molecular docking computationally predicts the conformation of a small molecule when binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline as they determine the fitness o...

Authors: Andrew T. McNutt, Paul Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri and David Ryan Koes

A machine learning platform for the discovery of materials

Authors: Carl E. Belle, Vural Aksakalli and Salvy P. Russo

Benchmarks for interpretation of QSAR models

Interpretation of QSAR models is useful to understand the complex nature of biological or physicochemical processes, guide structural optimization or perform knowledge-based validation of QSAR models. Highly p...

Authors: Mariia Matveieva and Pavel Polishchuk

InChI version 1.06: now more than 99.99% reliable

The software for the IUPAC Chemical Identifier, InChI, is extraordinarily reliable. It has been tested on large databases around the world, and has proved itself to be an essential tool in the handling and int...

Authors: Jonathan M. Goodman, Igor Pletnev, Paul Thiessen, Evan Bolton and Stephen R. Heller

Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study

Deep generative models have shown the ability to devise both valid and novel chemistry, which could significantly accelerate the identification of bioactive compounds. Many current models, however, use molecul...

Authors: Morgan Thomas, Robert T. Smith, Noel M. O’Boyle, Chris de Graaf and Andreas Bender

IDSM ChemWebRDF: SPARQLing small-molecule datasets

The Resource Description Framework (RDF), together with well-defined ontologies, significantly increases data interoperability and usability. The SPARQL query language was introduced to retrieve requested RDF ...

Authors: Jakub Galgonek and Jiří Vondrášek

SANCDB: an update on South African natural compounds and their readily available analogs

South African Natural Compounds Database (SANCDB; https://​sancdb.​rubi.​ru.​ac.​za/​) is the sole and a fully referenced database of natural chemical compounds of...

Authors: Bakary N’tji Diallo, Michael Glenister, Thommas M. Musyoka, Kevin Lobb and Özlem Tastan Bishop

Deep learning integration of molecular and interactome data for protein–compound interaction prediction

Virtual screening, which can computationally predict the presence or absence of protein–compound interactions, has attracted attention as a large-scale, low-cost, and short-term search method for seed compound...

Authors: Narumi Watanabe, Yuuto Ohnuki and Yasubumi Sakakibara

Assessing the calibration in toxicological in vitro models with conformal prediction

Machine learning methods are widely used in drug discovery and toxicity prediction. While showing overall good performance in cross-validation studies, their predictive power (often) drops in cases where the q...

Authors: Andrea Morger, Fredrik Svensson, Staffan Arvidsson McShane, Niharika Gauraha, Ulf Norinder, Ola Spjuth and Andrea Volkamer

STOUT: SMILES to IUPAC names using neural machine translation

Chemical compounds can be identified through a graphical depiction, a suitable string representation, or a chemical name. A universally accepted naming scheme for chemistry was established by the International...

Authors: Kohulan Rajan, Achim Zielesny and Christoph Steinbeck

Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 2: speed, consistency, diversity selection

Despite being a central concept in cheminformatics, molecular similarity has so far been limited to the simultaneous comparison of only two molecules at a time and using one index, generally the Tanimoto coeff...

Authors: Ramón Alain Miranda-Quintana, Anita Rácz, Dávid Bajusz and Károly Héberger

Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 1: Theory and characteristics^†

Quantification of the similarity of objects is a key concept in many areas of computational science. This includes cheminformatics, where molecular similarity is usually quantified based on binary fingerprints...

Authors: Ramón Alain Miranda-Quintana, Dávid Bajusz, Anita Rácz and Károly Héberger

Flame: an open source framework for model development, hosting, and usage in production environments

This article describes Flame, an open source software for building predictive models and supporting their use in production environments. Flame is a web application with a web-based graphic interface, which ca...

Authors: Manuel Pastor, José Carlos Gómez-Tamayo and Ferran Sanz

Multi-PLI: interpretable multi‐task deep learning model for unifying protein–ligand interaction datasets

The assessment of protein–ligand interactions is critical at early stage of drug discovery. Computational approaches for efficiently predicting such interactions facilitate drug development. Recently, methods ...

Authors: Fan Hu, Jiaxin Jiang, Dongqi Wang, Muchun Zhu and Peng Yin

QSAR-Co-X: an open source toolkit for multitarget QSAR modelling

Quantitative structure activity relationships (QSAR) modelling is a well-known computational tool, often used in a wide variety of applications. Yet one of the major drawbacks of conventional QSAR modelling is...

Authors: Amit Kumar Halder and M. Natália Dias Soeiro Cordeiro

SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

In drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore,...

Authors: Surendra Kumar and Mi-hyun Kim

Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach

Two-dimensional (2D) chemical fingerprints are widely used as binary features for the quantification of structural similarity of chemical compounds, which is an important step in similarity-based virtual scree...

Authors: Hiroyuki Kuwahara and Xin Gao

Molecular optimization by capturing chemist’s intuition using deep neural networks

A main challenge in drug discovery is finding molecules with a desirable balance of multiple properties. Here, we focus on the task of molecular optimization, where the goal is to optimize a given starting mol...

Authors: Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky and Ola Engkvist

Development and evaluation of two-parameter linear free energy models for the prediction of human skin permeability coefficient of neutral organic chemicals

The experimental values of skin permeability coefficients, required for dermal exposure assessment, are not readily available for many chemicals. The existing estimation approaches are either less accurate or ...

Authors: Sana Naseem, Yasuyuki Zushi and Deedar Nabi

MolFinder: an evolutionary algorithm for the global optimization of molecular properties and the extensive exploration of chemical space using SMILES

Here, we introduce a new molecule optimization method, MolFinder, based on an efficient global optimization algorithm, the conformational space annealing algorithm, and the SMILES representation. MolFinder fin...

Authors: Yongbeom Kwon and Juyong Lee

Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification

Chemical data is increasingly openly available in databases such as PubChem, which contains approximately 110 million compound entries as of February 2021. With the availability of data at such scale, the burd...

Authors: Janna Hastings, Martin Glauer, Adel Memariani, Fabian Neuhaus and Till Mossakowski

ChemProps: A RESTful API enabled database for composite polymer name standardization

The inconsistency of polymer indexing caused by the lack of uniformity in expression of polymer names is a major challenge for widespread use of polymer related data resources and limits broad application of m...

Authors: Bingyin Hu, Anqi Lin and L. Catherine Brinson

Diversity oriented Deep Reinforcement Learning for targeted molecule generation

In this work, we explore the potential of deep learning to streamline the process of identifying new potential drugs through the computational generation of molecules with interesting biological properties. Tw...

Authors: Tiago Pereira, Maryam Abbasi, Bernardete Ribeiro and Joel P. Arrais

DECIMER-Segmentation: Automated extraction of chemical structure depictions from scientific literature

Chemistry looks back at many decades of publications on chemical compounds, their structures and properties, in scientific articles. Liberating this knowledge (semi-)automatically and making it available to th...

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

Empowering large chemical knowledge bases for exposomics: PubChemLite meets MetFrag

Compound (or chemical) databases are an invaluable resource for many scientific disciplines. Exposomics researchers need to find and identify relevant chemicals that cover the entirety of potential (chemical a...

Authors: Emma L. Schymanski, Todor Kondić, Steffen Neumann, Paul A. Thiessen, Jian Zhang and Evan E. Bolton

Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification models

The development of selective inhibitors of the clinically relevant human Carbonic Anhydrase (hCA) isoforms IX and XII has become a major topic in drug research, due to their deregulation in several types of ca...

Authors: Annachiara Tinivella, Luca Pinzi and Giulio Rastelli

Structure‐based identification of dual ligands at the A_2AR and PDE10A with anti‐proliferative effects in lung cancer cell‐lines

Enhanced/prolonged cAMP signalling has been suggested as a suppressor of cancer proliferation. Interestingly, two key modulators that elevate cAMP, the A_2A receptor (A_2AR) and phosphodiesterase 10A (PDE10A), are ...

Authors: Leen Kalash, Ian Winfield, Dewi Safitri, Marcel Bermudez, Sabrina Carvalho, Robert Glen, Graham Ladds and Andreas Bender

What is the role of cheminformatics in a pandemic?

Authors: Rajarshi Guha, Egon Willighagen, Barbara Zdrazil and Nina Jeliazkova

Hybrid semantic recommender system for chemical compounds in large-scale datasets

The large, and increasing, number of chemical compounds poses challenges to the exploration of such datasets. In this work, we propose the usage of recommender systems to identify compounds of interest to scie...

Authors: Marcia Barros, Andre Moitinho and Francisco M. Couto

Using GANs with adaptive training data to search for new molecules

The process of drug discovery involves a search over the space of all possible chemical compounds. Generative Adversarial Networks (GANs) provide a valuable tool towards exploring chemical space and optimizing...

Authors: Andrew E. Blanchard, Christopher Stanley and Debsindhu Bhowmik

MAIP: a web service for predicting blood‐stage malaria inhibitors

Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year...

Authors: Nicolas Bosc, Eloy Felix, Ricardo Arcila, David Mendez, Martin R. Saunders, Darren V. S. Green, Jason Ochoada, Anang A. Shelat, Eric J. Martin, Preeti Iyer, Ola Engkvist, Andreas Verras, James Duffy, Jeremy Burrows, J. Mark F. Gardner and Andrew R. Leach

Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models

Graph neural networks (GNN) has been considered as an attractive modelling method for molecular property prediction, and numerous studies have shown that GNN could yield more promising results than traditional...

Authors: Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng Cao, Jian Wu and Tingjun Hou

Incorporating structural similarity into a scoring function to enhance the prediction of binding affinities

In this study, we developed a novel algorithm to improve the screening performance of an arbitrary docking scoring function by recalibrating the docking score of a query compound based on its structure similar...

Authors: Beihong Ji, Xibing He, Yuzhao Zhang, Jingchen Zhai, Viet Hoang Man, Shuhan Liu and Junmei Wang

RegioSQM20: improved prediction of the regioselectivity of electrophilic aromatic substitutions

We present RegioSQM20, a new version of RegioSQM (Chem Sci 9:660, 2018), which predicts the regioselectivities of electrophilic aromatic substitution (EAS) reactions from the calculation of proton affinities. ...

Authors: Nicolai Ree, Andreas H. Göller and Jan H. Jensen

The kernel-weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models

The ability of accurate predictions of biological response (biological activity/property/toxicity) of a given chemical makes the quantitative structure‐activity/property/toxicity relationship (QSAR/QSPR/QSTR) ...

Authors: Agnieszka Gajewicz-Skretna, Supratik Kar, Magdalena Piotrowska and Jerzy Leszczynski

ChemSpectra: a web-based spectra editor for analytical data

ChemSpectra, a web-based software to visualize and analyze spectroscopic data, integrating solutions for infrared spectroscopy (IR), mass spectrometry (MS), and one-dimensional ¹H and ¹³C NMR (proton and carbon n...

Authors: Yu-Chieh Huang, Pierre Tremouilhac, An Nguyen, Nicole Jung and Stefan Bräse

Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map

Protein solubility is significant in producing new soluble proteins that can reduce the cost of biocatalysts or therapeutic agents. Therefore, a computational model is highly desired to accurately predict prot...

Authors: Jianwen Chen, Shuangjia Zheng, Huiying Zhao and Yuedong Yang

ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions

Virtual screening (VS) based on molecular docking has emerged as one of the mainstream technologies of drug discovery due to its low cost and high efficiency. However, the scoring functions (SFs) implemented i...

Authors: Xujun Zhang, Chao Shen, Xueying Guo, Zhe Wang, Gaoqi Weng, Qing Ye, Gaoang Wang, Qiaojun He, Bo Yang, Dongsheng Cao and Tingjun Hou

Molecule Set Comparator (MSC): a CDK-based open rich‐client tool for molecule set similarity evaluations

The open rich-client Molecule Set Comparator (MSC) application enables a versatile and fast comparison of large molecule sets with a unique inter-set molecule-to-molecule mapping obtained e.g. by molecular-rec...

Authors: Kohulan Rajan, Jan-Mathis Hein, Christoph Steinbeck and Achim Zielesny

Substructure-based neural machine translation for retrosynthetic prediction

With the rapid improvement of machine translation approaches, neural machine translation has started to play an important role in retrosynthesis planning, which finds reasonable synthetic pathways for a target...

Authors: Umit V. Ucak, Taek Kang, Junsu Ko and Juyong Lee

Profiling and analysis of chemical compounds using pointwise mutual information

Pointwise mutual information (PMI) is a measure of association used in information theory. In this paper, PMI is used to characterize several publicly available databases (DrugBank, ChEMBL, PubChem and ZINC) i...

Authors: I. Čmelo, M. Voršilák and D. Svozil

COCONUT online: Collection of Open Natural Products database

Natural products (NPs) are small molecules produced by living organisms with potential applications in pharmacology and other industries as many of them are bioactive. This potential raised great interest in N...

Authors: Maria Sorokina, Peter Merseburger, Kohulan Rajan, Mehmet Aziz Yirik and Christoph Steinbeck

patRoon: open source software platform for environmental mass spectrometry based non-target screening

Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current data processin...

Authors: Rick Helmus, Thomas L. ter Laak, Annemarie P. van Wezel, Pim de Voogt and Emma L. Schymanski

From Big Data to Artificial Intelligence: chemoinformatics meets new challenges

The increasing volume of biomedical data in chemistry and life sciences requires development of new methods and approaches for their analysis. Artificial Intelligence and machine learning, especially neural ne...

Authors: Igor V. Tetko and Ola Engkvist

MET: a Java package for fast molecule equivalence testing

An important task in cheminformatics is to test whether two molecules are equivalent with respect to their 2D structure. Mathematically, this amounts to solving the graph isomorphism problem for labelled graph...

Authors: Jördis-Ann Schüler, Steffen Rechner and Matthias Müller-Hannemann

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