. De novo drug design is a computational approach that generates novel molecular structures from atomic building blocks with no a priori relationships. Conventional methods include structure-based ...and ligand-based design, which depend on the properties of the active site of a biological target or its known active binders, respectively. Artificial intelligence, including machine learning, is an emerging field that has positively impacted the drug discovery process. Deep reinforcement learning is a subdivision of machine learning that combines artificial neural networks with reinforcement-learning architectures. This method has successfully been employed to develop novel de novo drug design approaches using a variety of artificial networks including recurrent neural networks, convolutional neural networks, generative adversarial networks, and autoencoders. This review article summarizes advances in de novo drug design, from conventional growth algorithms to advanced machine-learning methodologies and highlights hot topics for further development.
The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive impact on the drug development pipeline. Numerous ...challenges have been addressed with the growing exploitation of drug-related data and the advancement of deep learning technology. Several model frameworks have been proposed to enhance the performance of deep learning algorithms in molecular design. However, only a few have had an immediate impact on drug development since computational results may not be confirmed experimentally. This systematic review aims to summarize the different deep learning architectures used in the drug discovery process and are validated with further in vivo experiments. For each presented study, the proposed molecule or peptide that has been generated or identified by the deep learning model has been biologically evaluated in animal models. These state-of-the-art studies highlight that even if artificial intelligence in drug discovery is still in its infancy, it has great potential to accelerate the drug discovery cycle, reduce the required costs, and contribute to the integration of the 3R (Replacement, Reduction, Refinement) principles. Out of all the reviewed scientific articles, seven algorithms were identified: recurrent neural networks, specifically, long short-term memory (LSTM-RNNs), Autoencoders (AEs) and their Wasserstein Autoencoders (WAEs) and Variational Autoencoders (VAEs) variants; Convolutional Neural Networks (CNNs); Direct Message Passing Neural Networks (D-MPNNs); and Multitask Deep Neural Networks (MTDNNs). LSTM-RNNs were the most used architectures with molecules or peptide sequences as inputs.
Silver nanoparticles (AgNPs) may reach the soil compartment via sewage sludge or nanoagrochemical applications. Understanding how NPs interact with biological systems is crucial for an accurate ...hazard assessment. Therefore, this study aimed at determining the Ag toxicokinetics in the mealworm Tenebrio molitor, exposed via Lufa 2.2 soil or via food to different Ag forms (uncoated 50 nm AgNPs, paraffin coated 3–8 nm and PVP-stabilised 60 nm, Ag2S NPs 20 nm, and ionic Ag). Mealworms were exposed for 21 days followed by a 21-day elimination phase (clean soil/food). A one-compartment kinetics model with inert fraction (simulating a storage compartment, where detoxified forms are located) was used to describe Ag accumulation. Fully understanding the uptake route in mealworms is difficult. For that reason several approaches were used, showing that food, soil and pore water all are valid uptake routes, but with different importance. Silver taken up from soil pore water or from soil showed to be related to Ag dissolution in soil pore water. In general, the uptake and elimination rate constants were similar for 3–8 nm and 60 nm AgNPs and for AgNO3, but significantly different for the uncoated 50 nm AgNPs. Upon food exposure, uptake rate constants were similar for 50 nm AgNPs and AgNO3, while those for 60 nm and 3–8 nm AgNPs and for Ag2S NPs also grouped together. NP exposure in soil appeared more difficult to characterize, with different patterns obtained for the different NPs. But it was evident that upon soil or food exposure, particle characteristics highly affected Ag bioavailability and bioaccumulation. Although Ag2S NPs were taken up, their elimination was faster than for other Ag forms, showing the lowest inert fraction. The significantly different elimination rate constants suggest that the mechanism of elimination may not be the same for different AgNPs either.
Display omitted
•Mealworms accumulate Ag2S NPs despite its low dissolution in soil pore water.•Ag2S NPs were accumulated less than pristine AgNPs and ionic Ag in mealworms.•Mealworms exposed via soil and via food showed different Ag uptake kinetics.•AgNPs dissolution in soil pore water influences its uptake in the mealworms.•Mealworms eliminate Ag through the faeces and by shedding exuviae.
Land application of sewage sludge containing increasing levels of silver nanoparticles (AgNPs) raises concerns about the risk for plant exposure. This study compared the uptake kinetics and ...distribution of Ag in Brassica rapa seedlings grown in Lufa 2.2 natural soil spiked with 20 nm Ag2S NPs, with those from 3 to 8 nm AgNPs, 50 nm AgNPs and AgNO3 exposures (10 mg Ag/kg dry soil). A two-compartment model was used to describe the uptake kinetics of Ag in plants, distinguishing two stages: stage I with increasing Ag uptake followed by stage II with decreasing Ag uptake. The concentration of Ag in roots from Ag2S NPs was about 14 and 10 times lower than for the other AgNPs and AgNO3 exposures, respectively, at the end of stage I, with root translocation rate constants being higher for Ag2S NPs. In stage II, Ag uptake occurred only for the 50 nm AgNPs. The distribution of Ag in B. rapa exposed to pristine, ionic and sulfidized AgNPs differed at the end of exposure. This study shows that Ag uptake and distribution in plants depends on the Ag form in soil, highlighting the importance of studying the environmentally relevant chemical species in NPs risk assessment.
Display omitted
•The accumulation of Ag in Brassica rapa differed during the plant life cycle.•Pristine AgNPs accumulated 14 times more Ag in B. rapa roots than Ag2S NPs.•A two-stage two-compartment model described the Ag uptake kinetics.•In Ag2S NPs, Ag was transferred to the shoots faster than for the other Ag forms.•NP stability determined different Ag uptake and translocation in plants.
The environmental risks of silica nanoparticles (SiNP) reported in the literature are contradictory and bring into question its safety for use in consumer applications. Organisms are never exposed to ...NPs alone in the real environment, while studies of the combined toxicity of SiNP are limited. To address this, we compared the acute toxicity of fluorescent core-shell SiNPs alone and in mixtures with Cd2+ to Ceriodaphnia dubia in the absence and presence of NOM. We identified biodistribution and feeding behaviour in addition to the traditional endpoints. NOM increased the colloidal stability of SiNPs in reconstituted water. In immobility tests, no significant effects were observed from Cd2+ exposure with NOM and varying concentrations of SiNPs. A similar pattern of curve dose-response was observed for varying concentrations of SiNPs and increasing Cd2+ concentration and constant NOM. Fluorescence microscopy verified a dose-dependent bioaccumulation of SiNPs in C. dubia. Co-exposure to 10 mg L−1 SiNP with NOM and Cd2+ resulted in a stimulated stress feeding response at the lower Cd2+ concentrations which declined at the higher dose due to a functional impairment of the digestive tract. Alterations in feeding behaviour and the increasing bioaccumulation of SiNP indicate a potential ecological risk for Ceriodaphnia dubia from the mixture exposure.
Display omitted
•No influence of NOM in SiNPs size and surface charge.•NOM reduced the settling of SiNPs in reconstituted water.•No changes were observed in acute mixture toxicity of SiNPs with NOM and Cd2+.•Exposure to SiNPs with NOM and Cd2+ caused significant changes in feeding behavior.•The accumulation of SiNPs in C. dubia gut increased with higher doses.
Engineered nanoparticles released into surface water may accumulate in sediments, potentially threatening benthic organisms. This study determined the toxicokinetics in Chironomus riparius of Ag from ...pristine silver nanoparticles (Ag NPs), a simulating aged Ag NP form (Ag2S NPs), and AgNO3 as an ionic control. Chironomid larvae were exposed to these Ag forms through water, sediment, or food. The potential transfer of Ag from larvae to adult midges was also evaluated. Results revealed higher Ag uptake by C. riparius upon exposure to Ag2S NPs, while larvae exposed to pristine Ag NPs and AgNO3 generally presented similar uptake kinetics. Uptake patterns of the different Ag forms were generally similar in the tests with water or sediment exposures, suggesting that uptake from water was the most important route of Ag uptake in both experiments. For the sediment bioaccumulation test, uptake was likely a combination of water uptake and sediment particles ingestion. Ag uptake via food exposure was only significant for Ag2S NPs. Ag transfer to the terrestrial compartment was low. In our environmentally relevant exposure scenario, chironomid larvae accumulated relatively high Ag concentrations and elimination was extremely low in some cases. These results suggest that bioaccumulation of Ag in its nanoparticulate and/or ionic form may occur in the environment, raising concerns regarding chronic exposure and trophic transfer. This is the first study determining the toxicokinetics of NPs in Chironomus, providing important information for understanding chironomid exposure to NPs and their potential interactions in the environment.
Display omitted
•Toxicokinetic studies are essential to assess interactions between species and NPs.•Different exposure routes tested for Ag NPs, Ag2S NPs and AgNO3 in chironomids.•Higher uptake/bioaccumulation of Ag2S NPs than other Ag forms by chironomid larvae.•Chironomids showed similar Ag kinetics upon exposure to pristine Ag NPs and AgNO3.•Pupal exuviae are likely an elimination route for ionic and nanoparticulate Ag.
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 nanomaterial. Existing identifiers may not always be applicable or sufficient to definitively identify the specific nanomaterial used in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier. We here describe the background to this new identifier, including FAIR interoperability as defined by FAIRSharing, identifiers.org, Bioregistry, and the CHEMINF ontology, and show how it complements other identifiers such as CAS numbers and the ongoing efforts to extend the InChI identifier to cover nanomaterials. We provide examples of its use in various H2020-funded nanosafety projects.
Graphical Abstract
Toxicogenomics (TGx) approaches are increasingly applied to gain insight into the possible toxicity mechanisms of engineered nanomaterials (ENMs). Omics data can be valuable to elucidate the ...mechanism of action of chemicals and to develop predictive models in toxicology. While vast amounts of transcriptomics data from ENM exposures have already been accumulated, a unified, easily accessible and reusable collection of transcriptomics data for ENMs is currently lacking. In an attempt to improve the FAIRness of already existing transcriptomics data for ENMs, we curated a collection of homogenized transcriptomics data from human, mouse and rat ENM exposures in vitro and in vivo including the physicochemical characteristics of the ENMs used in each study.
The fate of engineered nanomaterials in ecosystems is unclear. An aquatic stream mesocosm explored the fate and bioaccumulation of silver sulfide nanoparticles (Ag2S NPs) compared to silver nitrate ...(AgNO3). The aims were to determine the total Ag in water, sediment and biota, and to evaluate the bioavailable fractions of silver in the sediment using a serial extraction method. The total Ag in the water column from a nominal daily dose of 10 μg L−1 of Ag for the AgNO3 or Ag2S NP treatments reached a plateau of around 13 and 12 μg L−1, respectively, by the end of the study. Similarly, the sediment of both Ag-treatments reached ~380 μg Ag kg−1, and with most of it being acid-extractable/labile. The biota accumulated 4–59 μg Ag g−1 dw, depending on the type of Ag-treatment and organism. The oligochaete worm, Lumbriculus variegatus, accumulated Ag from the Ag2S exposure over time, which was similar to the AgNO3 treatment by the end of the experiment. The planarian, Girardia tigrina, and the chironomid larva, Chironomus riparius, showed much higher Ag concentrations than the oligochaete worms; and with a clearer time-dependent statistically significant Ag accumulation relative to the untreated controls. For the pulmonate snail, Physa acuta, bioaccumulation of Ag from AgNO3 and Ag2S NP exposures was observed, but was lower from the nano treatment. The AgNO3 exposure caused appreciable Ag accumulation in the water flea, Daphnia magna, but accumulation was higher in the Ag2S NP treatment (reaching 59 μg g−1 dw). In the rainbow trout, Oncorhynchus mykiss, AgNO3, but not Ag2S NPs, caused total Ag concentrations to increase in the tissues. Overall, the study showed transfer of total Ag from the water column to the sediment, and Ag bioaccumulation in the biota, with Ag from Ag2S NP exposure generally being less bioavailable than that from AgNO3.
Display omitted
•Mesocosm experiments allow a more realistic understanding of nanomaterial fate.•Silver as AgNO3 or Ag2S NPs caused similar water and sediment contamination.•Ag-containing particles were found in the water of both Ag-treatments.•At day 14, Ag-treatment had no difference in Ag uptake in the snails or worms.•Silver as AgNO3 was more bioavailable to planarians and fish than Ag2S NPs.
The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for ...grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it. Here, we demonstrate, using specific worked case studies, how to organise the nano-community efforts to define metadata schemas, by organising the data management cycle as a joint effort of all players (data creators, analysts, curators, managers, and customers) supervised by the newly defined role of data shepherd. We propose that once researchers understand their tasks and responsibilities, they will naturally apply the available tools. Two case studies are presented (modelling of particle agglomeration for dose metrics, and consensus for NM dissolution), along with a survey of the currently implemented metadata schema in existing nanosafety databases. We conclude by offering recommendations on the steps forward and the needed workflows for metadata capture to ensure FAIR nanosafety data.
PDF
