Physics-inspired structural representations for molecules and materials

F Musil, A Grisafi, AP Bartók, C Ortner… - Chemical …, 2021 - ACS Publications
The first step in the construction of a regression model or a data-driven analysis, aiming to
predict or elucidate the relationship between the atomic-scale structure of matter and its …

Where is nano today and where is it headed? A review of nanomedicine and the dilemma of nanotoxicology

C Domingues, A Santos, C Alvarez-Lorenzo… - ACS …, 2022 - ACS Publications
Worldwide nanotechnology development and application have fueled many scientific
advances, but technophilic expectations and technophobic demands must be …

Converting nanotoxicity data to information using artificial intelligence and simulation

X Yan, T Yue, DA Winkler, Y Yin, H Zhu… - Chemical …, 2023 - ACS Publications
Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …

A review on the recent applications of deep learning in predictive drug toxicological studies

K Sinha, N Ghosh, PC Sil - Chemical Research in Toxicology, 2023 - ACS Publications
Drug toxicity prediction is an important step in ensuring patient safety during drug design
studies. While traditional preclinical studies have historically relied on animal models to …

[HTML][HTML] NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

A Afantitis, G Melagraki, P Isigonis, A Tsoumanis… - Computational and …, 2020 - Elsevier
Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting
unique physicochemical (PChem) properties compared to their bulk analogues. These …

Computational aspects of two important biochemical networks with respect to some novel molecular descriptors

A Ullah, Z Bano, S Zaman - Journal of Biomolecular Structure and …, 2024 - Taylor & Francis
Quantitative structure-activity relationship (QSAR) represents quantitative correlation of
biological structural features (called as topological indices) and pharmacological activity as …

Nanotoxicology data for in silico tools: a literature review

I Furxhi, F Murphy, M Mullins, A Arvanitis… - Nanotoxicology, 2020 - Taylor & Francis
The exercise of non-testing approaches in nanoparticles (NPs) hazard assessment is
necessary for the risk assessment, considering cost and time efficiency, to identify, assess …

QSAR, homology modeling, and docking simulation on SARS-CoV-2 and pseudomonas aeruginosa inhibitors, ADMET, and molecular dynamic simulations to find a …

EI Edache, A Uzairu, PA Mamza… - Journal of Genetic …, 2022 - Elsevier
Background In seek of potent and non-toxic iminoguanidine derivatives formerly assessed
as active Pseudomonas aeruginosa inhibitors, a combined mathematical approach of …

Nano-(Q) SAR for cytotoxicity prediction of engineered nanomaterials

AA Buglak, AV Zherdev, BB Dzantiev - Molecules, 2019 - mdpi.com
Although nanotechnology is a new and rapidly growing area of science, the impact of
nanomaterials on living organisms is unknown in many aspects. In this regard, it is extremely …

NanoEHS beyond toxicity–focusing on biocorona

S Lin, M Mortimer, R Chen, A Kakinen… - Environmental …, 2017 - pubs.rsc.org
The first phase of studies on environmental health and safety of nanomaterials (nanoEHS)
has been mainly focused on evidence-based investigations that probe the impact of …