Nanosafety: an evolving concept to bring the safest possible nanomaterials to society and environment

The use of nanomaterials has been increasing in recent times, and they are widely used in industries such as cosmetics, drugs, food, water treatment, and agriculture. The rapid development of new nanomaterials demands a set of approaches to evaluate the potential toxicity and risks related to them. In this regard, nanosafety has been using and adapting already existing methods (toxicological approach), but the unique characteristics of nanomaterials demand new approaches (nanotoxicology) to fully understand the potential toxicity, immunotoxicity, and (epi)genotoxicity. In addition, new technologies, such as organs-on-chips and sophisticated sensors, are under development and/or adaptation. All the information generated is used to develop new in silico approaches trying to predict the potential effects of newly developed materials. The overall evaluation of nanomaterials from their production to their final disposal chain is completed using the life cycle assessment (LCA), which is becoming an important element of nanosafety considering sustainability and environmental impact. In this review, we give an overview of all these elements of nanosafety.European Union’s H2020 project Sinfonia (N.857253). SbDToolBox, with reference NORTE-01-0145-FEDER-000047, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fun

Structural Basis for the Limited Response to Oxidative and Thiol-Conjugating Agents by Triosephosphate Isomerase From the Photosynthetic Bacteria Synechocystis

In plants, the ancestral cyanobacterial triosephosphate isomerase (TPI) was replaced by a duplicated version of the cytosolic TPI. This isoform acquired a transit peptide for chloroplast localization and functions in the Calvin-Benson cycle. To gain insight into the reasons for this gene replacement in plants, we characterized the TPI from the photosynthetic bacteria Synechocystis (SyTPI). SyTPI presents typical TPI enzyme kinetics profiles and assembles as a homodimer composed of two subunits that arrange in a (β-α)8 fold. We found that oxidizing agents diamide (DA) and H2O2, as well as thiol-conjugating agents such as oxidized glutathione (GSSG) and methyl methanethiosulfonate (MMTS), do not inhibit the catalytic activity of SyTPI at concentrations required to inactivate plastidic and cytosolic TPIs from the plant model Arabidopsis thaliana (AtpdTPI and AtcTPI, respectively). The crystal structure of SyTPI revealed that each monomer contains three cysteines, C47, C127, and C176; however only the thiol group of C176 is solvent exposed. While AtcTPI and AtpdTPI are redox-regulated by chemical modifications of their accessible and reactive cysteines, we found that C176 of SyTPI is not sensitive to redox modification in vitro. Our data let us postulate that SyTPI was replaced by a eukaryotic TPI, because the latter contains redox-sensitive cysteines that may be subject to post-translational modifications required for modulating TPI's enzymatic activity

Caracterización de la diversidad molecular, cobertura del espacio químico y reconocimiento molecular de inhibidores de DNA metiltransferasas

Ciencias Química

MOESM1 of Database fingerprint (DFP): an approach to represent molecular databases

Additional file 1:Table S1. DFPs of representative data sets used in this work. Table S2. Inter-set relationship computed with the newly developed database fingerprint using DFP/Tanimoto coefficient. Fig. S1 Distributions of MACCS keys (166-bits) of selected data sets studied in this work (others are shown in the main text). Fig. S2 Visual representation of the distance matrix comparing inter-set relationships of the compound data sets computed with the database fingerprint (DFP) and city block distance. Fig. S3 Relationship between inverse normalized city block distance and Tanimoto similarity using the DFP. Fig. S4 Inter-set relationships of the compound data sets computed with MACCS keys and the Tanimoto coefficient. Fig. S5 Relationship between mean similarities computed with MACCS keys and DFP. Fig. S6 Relationship Shannon Entropy and DFP/Tanimoto similarity and k-mean Euclidean clustering for the ten compound data sets in Table 2 at threshold of 0.6. Fig. S7 Probability distribution of the 198 significant bit positions recovered from the original databases represented by PubChem fingerprint at threshold of 0.6.Fig. S8 Relationship Shannon Entropy and DFP/Tanimoto similarity and k-mean Euclidean clustering for the ten compound data sets in Table 2 at threshold of 0.7. Fig. S9 Probability distribution of the 198 significant bit positions recovered from the original databases represented by PubChem fingerprint at threshold of 0.7

Nanomaterial Exposure, Extracellular Vesicle Biogenesis and Adverse Cellular Outcomes: A Scoping Review

The progressively increasing use of nanomaterials (NMs) has awakened issues related to nanosafety and its potential toxic effects on human health. Emerging studies suggest that NMs alter cell communication by reshaping and altering the secretion of extracellular vesicles (EVs), leading to dysfunction in recipient cells. However, there is limited understanding of how the physicochemical characteristics of NMs alter the EV content and their consequent physiological functions. Therefore, this review explored the relevance of EVs in the nanotoxicology field. The current state of the art on how EVs are modulated by NM exposure and the possible regulation and modulation of signaling pathways and physiological responses were assessed in detail. This review followed the manual for reviewers produced by The Joanna Brigs Institute for Scoping Reviews and the PRISMA extension for Scoping Reviews (PRISMA-ScR): checklist and explanation. The research question, “Do NMs modulate cellular responses mediated by EVs?” was analyzed following the PECO model (P (Population) = EVs, E (Exposure) = NMs, C (Comparator) = EVs without exposure to NMs, O (Outcome) = Cellular responses/change in EVs) to help methodologically assess the association between exposure and outcome. For each theme in the PECO acronym, keywords were defined, organized, and researched in PubMed, Science Direct, Scopus, Web of Science, EMBASE, and Cochrane databases, up to 30 September 2021. In vitro, in vivo, ex vivo, and clinical studies that analyzed the effect of NMs on EV biogenesis, cargo, and cellular responses were included in the analysis. The methodological quality assessment was conducted using the ToxRTool, ARRIVE guideline, Newcastle Ottawa and the EV-TRACK platform. The search in the referred databases identified 2944 articles. After applying the eligibility criteria and two-step screening, 18 articles were included in the final review. We observed that depending on the concentration and physicochemical characteristics, specific NMs promote a significant increase in EV secretion as well as changes in their cargo, especially regarding the expression of proteins and miRNAs, which, in turn, were involved in biological processes that included cell communication, angiogenesis, and activation of the immune response, etc. Although further studies are necessary, this work suggests that molecular investigations on EVs induced by NM exposure may become a potential tool for toxicological studies since they are widely accessible biomarkers that may form a bridge between NM exposure and the cellular response and pathological outcome

Chemoinformatics and Artificial Intelligence Colloquium: Progress and Challenges to Develop Bioactive Compounds

We report the main conclusions of the first Chemoinformatics and Artificial Intelligence Colloquium, Mexico City, June 15-17, 2022. Fifteen lectures were presented during a virtual public event with speakers from industry, academia, and non-for-profit organizations. Twelve hundred and ninety students and academics from more than 60 countries. During the meeting, applications, challenges, and opportunities in drug discovery, de novo drug design, ADME-Tox (absorption, distribution, metabolism, excretion and toxicity) property predictions, organic chemistry, peptides, and antibiotic resistance were discussed. The program along with the recordings of all sessions are freely available at https://www.difacquim.com/english/events/2022-colloquium

Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds

We report the main conclusions of the first Chemoinformatics and Artificial Intelligence Colloquium, Mexico City, June 15-17, 2022. Fifteen lectures were presented during a virtual public event with speakers from industry, academia, and non-for-profit organizations. Twelve hundred and ninety students and academics from more than 60 countries. During the meeting, applications, challenges, and opportunities in drug discovery, de novo drug design, ADME-Tox (absorption, distribution, metabolism, excretion and toxicity) property predictions, organic chemistry, peptides, and antibiotic resistance were discussed. The program along with the recordings of all sessions are freely available at https://www.difacquim.com/english/events/2022-colloquium/