Articles
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Citation: Journal of Cheminformatics 2022 14:63
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Machine learning for identification of silylated derivatives from mass spectra
Compound structure identification is using increasingly more sophisticated computational tools, among which machine learning tools are a recent addition that quickly gains in importance. These tools, of which ...
Citation: Journal of Cheminformatics 2022 14:62 -
Review of techniques and models used in optical chemical structure recognition in images and scanned documents
Extraction of chemical formulas from images was not in the top priority of Computer Vision tasks for a while. The complexity both on the input and prediction sides has made this task challenging for the conven...
Citation: Journal of Cheminformatics 2022 14:61 -
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions
Deep learning methods, such as reaction prediction and retrosynthesis analysis, have demonstrated their significance in the chemical field. However, the de novo generation of novel reactions using artificial i...
Citation: Journal of Cheminformatics 2022 14:60 -
Robustness under parameter and problem domain alterations of Bayesian optimization methods for chemical reactions
The related problems of chemical reaction optimization and reaction scope search concern the discovery of reaction pathways and conditions that provide the best percentage yield of a target product. The space ...
Citation: Journal of Cheminformatics 2022 14:59 -
FPocketWeb: protein pocket hunting in a web browser
Detecting macromolecular (e.g., protein) cavities where small molecules bind is an early step in computer-aided drug discovery. Multiple pocket-detection algorithms have been developed over the past several de...
Citation: Journal of Cheminformatics 2022 14:58 -
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials
Management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier for each...
Citation: Journal of Cheminformatics 2022 14:57 -
Predicting the mutation effects of protein–ligand interactions via end-point binding free energy calculations: strategies and analyses
Protein mutations occur frequently in biological systems, which may impact, for example, the binding of drugs to their targets through impairing the critical H-bonds, changing the hydrophobic interactions, etc...
Citation: Journal of Cheminformatics 2022 14:56 -
Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach
Application of chemical named entity recognition (CNER) algorithms allows retrieval of information from texts about chemical compound identifiers and creates associations with physical–chemical properties and ...
Citation: Journal of Cheminformatics 2022 14:55 -
Using Jupyter Notebooks for re-training machine learning models
Machine learning (ML) models require an extensive, user-driven selection of molecular descriptors in order to learn from chemical structures to predict actives and inactives with a high reliability. In additio...
Citation: Journal of Cheminformatics 2022 14:54 -
Correction to: Designing optimized drug candidates with Generative Adversarial Network
Citation: Journal of Cheminformatics 2022 14:53 -
Integrating concept of pharmacophore with graph neural networks for chemical property prediction and interpretation
Recently, graph neural networks (GNNs) have revolutionized the field of chemical property prediction and achieved state-of-the-art results on benchmark data sets. Compared with the traditional descriptor- and ...
Citation: Journal of Cheminformatics 2022 14:52 -
Paths to Cheminformatics: Q&A with Norberto Sánchez-Cruz and Emma Schymanski
Citation: Journal of Cheminformatics 2022 14:51 -
Confidence bands and hypothesis tests for hit enrichment curves
In virtual screening for drug discovery, hit enrichment curves are widely used to assess the performance of ranking algorithms with regard to their ability to identify early enrichment. Unfortunately, research...
Citation: Journal of Cheminformatics 2022 14:50 -
SimVec: predicting polypharmacy side effects for new drugs
Polypharmacy refers to the administration of multiple drugs on a daily basis. It has demonstrated effectiveness in treating many complex diseases , but it has a higher risk of adverse drug reactions. Hence, th...
Citation: Journal of Cheminformatics 2022 14:49 -
Machine intelligence-driven framework for optimized hit selection in virtual screening
Virtual screening (VS) aids in prioritizing unknown bio-interactions between compounds and protein targets for empirical drug discovery. In standard VS exercise, roughly 10% of top-ranked molecules exhibit act...
Citation: Journal of Cheminformatics 2022 14:48 -
Predicting protein network topology clusters from chemical structure using deep learning
Comparing chemical structures to infer protein targets and functions is a common approach, but basing comparisons on chemical similarity alone can be misleading. Here we present a methodology for predicting ta...
Citation: Journal of Cheminformatics 2022 14:47 -
In silico prediction of UGT-mediated metabolism in drug-like molecules via graph neural network
UDP-glucuronosyltransferases (UGTs) have gained increasing attention as they play important roles in the phase II metabolism of drugs. Due to the time-consuming process and high cost of experimental approaches...
Citation: Journal of Cheminformatics 2022 14:46 -
BitterMatch: recommendation systems for matching molecules with bitter taste receptors
Bitterness is an aversive cue elicited by thousands of chemically diverse compounds. Bitter taste may prevent consumption of foods and jeopardize drug compliance. The G protein-coupled receptors for bitter tas...
Citation: Journal of Cheminformatics 2022 14:45 -
Blood–brain barrier penetration prediction enhanced by uncertainty estimation
Blood–brain barrier is a pivotal factor to be considered in the process of central nervous system (CNS) drug development, and it is of great significance to rapidly explore the blood–brain barrier permeability...
Citation: Journal of Cheminformatics 2022 14:44 -
LigninGraphs: lignin structure determination with multiscale graph modeling
Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental cha...
Citation: Journal of Cheminformatics 2022 14:43 -
Correction to: Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs
Citation: Journal of Cheminformatics 2022 14:42 -
SwinOCSR: end-to-end optical chemical structure recognition using a Swin Transformer
Optical chemical structure recognition from scientific publications is essential for rediscovering a chemical structure. It is an extremely challenging problem, and current rule-based and deep-learning methods...
Citation: Journal of Cheminformatics 2022 14:41 -
Designing optimized drug candidates with Generative Adversarial Network
Drug design is an important area of study for pharmaceutical businesses. However, low efficacy, off-target delivery, time consumption, and high cost are challenges and can create barriers that impact this proc...
Citation: Journal of Cheminformatics 2022 14:40 -
AMADAR: a python-based package for large scale prediction of Diels–Alder transition state geometries and IRC path analysis
Predicting transition state geometries is one of the most challenging tasks in computational chemistry, which often requires expert-based knowledge and permanent human intervention. This short communication re...
Citation: Journal of Cheminformatics 2022 14:39 -
Commentary: the first twelve years of the Journal of Cheminformatics
This commentary provides an overview of the publications in, and the citations to, the first twelve volumes of the Journal of Cheminformatics, covering the period 2009–2020. The analysis is based on the 622 artic...
Citation: Journal of Cheminformatics 2022 14:38 -
KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study
As an alternative to one drug-one target approaches, systems biology methods can provide a deeper insight into the holistic effects of drugs. Network-based approaches are tools of systems biology, that can rep...
Citation: Journal of Cheminformatics 2022 14:37 -
DECIMER—hand-drawn molecule images dataset
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over...
Citation: Journal of Cheminformatics 2022 14:36 -
Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs
Facing the continuous emergence of new psychoactive substances (NPS) and their threat to public health, more effective methods for NPS prediction and identification are critical. In this study, the pharmacolog...
Citation: Journal of Cheminformatics 2022 14:35 -
PIKAChU: a Python-based informatics kit for analysing chemical units
As efforts to computationally describe and simulate the biochemical world become more commonplace, computer programs that are capable of in silico chemistry play an increasingly important role in biochemical r...
Citation: Journal of Cheminformatics 2022 14:34 -
Probabilistic metabolite annotation using retention time prediction and meta-learned projections
Retention time information is used for metabolite annotation in metabolomic experiments. But its usefulness is hindered by the availability of experimental retention time data in metabolomic databases, and by ...
Citation: Journal of Cheminformatics 2022 14:33 -
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction
Recently, imputation techniques have been adapted to predict activity values among sparse bioactivity matrices, showing improvements in predictive performance over traditional QSAR models. These models are abl...
Citation: Journal of Cheminformatics 2022 14:32 -
RanDepict: Random chemical structure depiction generator
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data ...
Citation: Journal of Cheminformatics 2022 14:31 -
InflamNat: web-based database and predictor of anti-inflammatory natural products
Natural products (NPs) are a valuable source for anti-inflammatory drug discovery. However, they are limited by the unpredictability of the structures and functions. Therefore, computational and data-driven pr...
Citation: Journal of Cheminformatics 2022 14:30 -
Chemical reaction network knowledge graphs: the OntoRXN ontology
The organization and management of large amounts of data has become a major point in almost all areas of human knowledge. In this context, semantic approaches propose a structure for the target data, defining ...
Citation: Journal of Cheminformatics 2022 14:29 -
canSAR chemistry registration and standardization pipeline
Integration of medicinal chemistry data from numerous public resources is an increasingly important part of academic drug discovery and translational research because it can bring a wealth of important knowled...
Citation: Journal of Cheminformatics 2022 14:28 -
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules
Unpredicted drug safety issues constitute the majority of failures in the pharmaceutical industry according to several studies. Some of these preclinical safety issues could be attributed to the non-selective ...
Citation: Journal of Cheminformatics 2022 14:27 -
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
Cyclic peptides formed by disulfide bonds have been one large group of common drug candidates in drug development. Structural information of a peptide is essential to understand its interaction with its target...
Citation: Journal of Cheminformatics 2022 14:26 -
Diversifying cheminformatics
Citation: Journal of Cheminformatics 2022 14:25 -
Surge: a fast open-source chemical graph generator
Chemical structure generators are used in cheminformatics to produce or enumerate virtual molecules based on a set of boundary conditions. The result can then be tested for properties of interest, such as adhe...
Citation: Journal of Cheminformatics 2022 14:24 -
Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes
Drug–drug interaction (DDI) often causes serious adverse reactions and thus results in inestimable economic and social loss. Currently, comprehensive DDI evaluation has become a major challenge in pharmaceutic...
Citation: Journal of Cheminformatics 2022 14:23 -
Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease
We present several workflows for protein-ligand docking and free energy calculation for use in the workflow management system Galaxy. The workflows are composed of several widely used open-source tools, includ...
Citation: Journal of Cheminformatics 2022 14:22 -
ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations
The introduction of machine learning to small molecule research– an inherently multidisciplinary field in which chemists and data scientists combine their expertise and collaborate - has been vital to making s...
Citation: Journal of Cheminformatics 2022 14:21 -
Explaining and avoiding failure modes in goal-directed generation of small molecules
Despite growing interest and success in automated in-silico molecular design, questions remain regarding the ability of goal-directed generation algorithms to perform unbiased exploration of novel chemical spa...
Citation: Journal of Cheminformatics 2022 14:20 -
Systemic evolutionary chemical space exploration for drug discovery
Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening technologies, computational de novo design has become a popula...
Citation: Journal of Cheminformatics 2022 14:19 -
Transformer-based molecular optimization beyond matched molecular pairs
Molecular optimization aims to improve the drug profile of a starting molecule. It is a fundamental problem in drug discovery but challenging due to (i) the requirement of simultaneous optimization of multiple...
Citation: Journal of Cheminformatics 2022 14:18 -
Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening
Structure-based drug repositioning has emerged as a promising alternative to conventional drug development. Regardless of the many success stories reported over the past years and the novel breakthroughs on th...
Citation: Journal of Cheminformatics 2022 14:17 -
A multitask GNN-based interpretable model for discovery of selective JAK inhibitors
The Janus kinase (JAK) family plays a pivotal role in most cytokine-mediated inflammatory and autoimmune responses via JAK/STAT signaling, and administration of JAK inhibitors is a promising therapeutic strate...
Citation: Journal of Cheminformatics 2022 14:16 -
Improving the performance of models for one-step retrosynthesis through re-ranking
Retrosynthesis is at the core of organic chemistry. Recently, the rapid growth of artificial intelligence (AI) has spurred a variety of novel machine learning approaches for data-driven synthesis planning. The...
Citation: Journal of Cheminformatics 2022 14:15 -
ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding
Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-tar...
Citation: Journal of Cheminformatics 2022 14:14