Domenico GadaletaMario Negri Institute for Pharmacological Research | Mario Negri · Department of Environmental Health Sciences
Domenico Gadaleta
PhD
Researcher
About
75
Publications
11,906
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1,411
Citations
Citations since 2017
Introduction
Additional affiliations
February 2016 - February 2022
September 2013 - March 2014
January 2013 - December 2015
Education
September 2007 - November 2012
Publications
Publications (75)
Oxidative stress is the consequence of an abnormal increase of reactive oxygen species (ROS). ROS are generated mainly during the metabolism in both normal and pathological conditions as well as from exposure to xenobiotics. Xenobiotics can, on the one hand, disrupt molecular machinery involved in redox processes and, on the other hand, reduce the...
The reduction and replacement of in vivo tests have become crucial in terms of resources and animal benefits. The read-across approach reduces the number of substances to be tested, exploiting existing experimental data to predict the properties of untested substances. Currently, several tools have been developed to perform read-across, but other a...
Drug-induced cardiotoxicity is a common side effect of drugs in clinical use or under postmarket surveillance and is commonly due to off-target interactions with the cardiac human-ether-ago go related (hERG) potassium channel. Therefore, prioritizing drug candidates based on their hERG blocking potential is a mandatory step in the early preclinical...
The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation,...
In silico (computational) methods continue to evolve as part of a robust 21st century public health strategy in risk assessment, relevant to all sectors of chemical safety including preclinical drug discovery, industrial chemicals testing, food and cosmetics. Alongside in vitro methods as components of intelligent testing and pathway driven strateg...
Developmental and adult/ageing neurotoxicity is an area needing alternative methods for chemical risk assessment. The formulation of a strategy to screen large numbers of chemicals is highly relevant due to potential exposure to compounds that may have long-term adverse health consequences on the nervous system, leading to neurodegeneration. Advers...
Many regulatory contexts require the evaluation of repeated-dose toxicity (RDT) studies conducted in laboratory animals. The main outcome of RDT studies is the identification of the no observed adverse effect level (NOAEL) and the lowest observed adverse effect level (LOAEL) that are normally used as point of departure for the establishment of heal...
Due to the link with serious adverse health effects, genotoxicity is an important toxicological endpoint in each regulatory setting with respect to human health, including for pharmaceuticals. To this extent, a compound potential to induce gene mutations as well as chromosome damage needs to be addressed. For chromosome damage, i.e., the induction...
This read-across case study characterises thirteen, structurally similar carboxylic acids demonstrating the application of in vitro and in silico human-based new approach methods, to determine biological similarity. Based on data from in vivo animal studies, the read-across hypothesis is that all analogues are steatotic and so should be considered...
The thyroid system plays a major role in the regulation of several physiological processes. The dysregulation of the thyroid system caused by the interference of xenobiotics and contaminants may bring to pathologies like hyper- and hypothyroidism and it has been recently correlated with adverse outcomes leading to cancer, obesity, diabetes and neur...
Cancer is a main concern for human health and there is a need of alternative methodologies to rapidly screen large quantitative of compounds that may represent a toxicological risk. Here a statistical analyses is performed on a benchmark database of experimental Ames data to identify chemical descriptors discriminating mutagens and non-mutagens. A...
Growing interest in environmental toxicity assessment using Thamnocephalus platyurus as organism has led to an increased availability of acute toxicity data. Despite this growing interest in tests with this organism, however, to the best of our knowledge there are no computational models to predict the acute toxicity in T. platyurus. In view of the...
Background:
Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditi...
Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure–activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predic...
Developmental toxicity refers to the occurrence of adverse effects on a developing organism as a consequence of exposure to hazardous chemicals. The assessment of developmental toxicity has become relevant to the safety assessment process of chemicals. The zebrafish embryo developmental toxicology assay is an emerging test used to screen the terato...
Repeated-dose toxicity (RDT) is a critical endpoint for hazard characterisation of chemicals, and is assessed to derive safe levels of exposure for human health. Here we present the first attempt to model simultaneously no-observed-(adverse)-effect-level) (NO(A)EL) and lowest-observed-(adverse)-effect-level (LO(A)EL). Classification and regression...
Read-across (RAX) is a popular data-gap filling technique that uses category and analogue approaches to predict toxicological endpoints for a target. Despite its increasing relevance, RAX relies on human expert judgement and lacks a reproducible and automated protocol. It also only relies on structural similarity for identifying the analogues, whil...
Read-across (RAX) is a popular data gap-filling technique that uses category and analogue approaches to predict toxicological endpoints for a target. Despite its increasing relevance, RAX relies on human expert judgement and lacks a reproducible and automated protocol. It also relies only on structural similarity for identifying the analogues, whil...
Read-across (RAX) is a popular data gap-filling technique that uses category and analogue approaches to predict toxicological endpoints for a target. Despite its increasing relevance, RAX relies on human expert judgement and lacks a reproducible and automated protocol. It also relies only on structural similarity for identifying the analogues, whil...
Highlights
• New in silico models for genotoxicity assessment of organic chemicals are proposed.
• The fragment-based model is the best performing model.
• Proposed fragments include structural alerts for genotoxicity and non-genotoxicity.
• 24 active structural alerts are completely new.
• Best model will be freely available on VEGA hub platform....
![Workflow for aiQSAR-based model development
(Adapted from [34])](publication/335507443/figure/fig3/AS:963413844975636@1606707168689/Workflow-for-aiQSAR-based-model-development-Adapted-from-34_Q320.jpg)
Abstract The median lethal dose for rodent oral acute toxicity (LD50) is a standard piece of information required to categorize chemicals in terms of the potential hazard posed to human health after acute exposure. The exclusive use of in vivo testing is limited by the time and costs required for performing experiments and by the need to sacrifice...
It was highlighted that the original article [1] contained an error in the Funding section. This Correction article states the correct and incorrect versions of the Funding section.
![Calculating the ADM. μpubchem\documentclass[12pt]{minimal}...](publication/332181480/figure/fig4/AS:963413794639896@1606707156671/Calculating-the-ADM-mpubchemdocumentclass12ptminimal-usepackageamsmath_Q320.jpg)
Background
Several QSAR methodology developments have shown promise in recent years. These include the consensus approach to generate the final prediction of a model, utilizing new, advanced machine learning algorithms and streamlining, standardization and automation of various QSAR steps. One approach that seems under-explored is at-the-runtime ge...
Purpose
This study explored several strategies to improve the performance of literature QSAR models for plasma protein binding (PPB), such as a suitable endpoint transformation, a correct representation of chemicals, more consistency in the dataset, and a reliable definition of the applicability domain.
Methods
We retrieved human fraction unbound...
![Workflow for data curation.
Adapted from [2]](publication/329550938/figure/fig1/AS:963413752688644@1606707146072/Workflow-for-data-curation-Adapted-from-2_Q320.jpg)
The quality of data used for QSAR model derivation is extremely important as it strongly affects the final robustness and predictive power of the model. Ambiguous or wrong structures need to be carefully checked, because they lead to errors in calculation of descriptors, hence leading to meaningless results. The increasing amounts of data, however,...
Nontesting methods (NTM) proved to be a valuable resource for risk assessment of chemical substances. Indeed, they can be particularly useful when the information provided by different sources was integrated to increase the confidence in the final result. This integration can be sometimes difficult because different methods can lead to conflicting...
Plasma Protein Binding (PPB) is an important pharmacokinetic parameter related to the capacity of drugs to form reversible bounds to plasmatic proteins. It has impact on half-life and therapeutic index, and it is responsible to most failures in early stage drug development.
In the last years, the new availability of new PPB data justified the need...
Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships...
Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes. A benchmark dataset of Ames data for 354 azo dyes was employed to develop three...
Retrospective validation studies carried out on three benchmark databases containing a small fraction (that is 2.80%) of known tubulin binders permitted us to develop a computational platform very effective in selecting easier manageable subsets showing by far higher percentages of actives (about 25%). These studies relied on the hierarchical appli...
Designing high selective human monoamine oxidase (hMAO) inhibitors is a challenging goal on the road to a more effective treatment of depression and anxiety (inhibition of hMAO-A isoform) as well as neurodegenerative diseases (inhibition of hMAO-B isoform). To uncover the molecular rationale of hMAO selectivity, two recently prepared 2H-chromene-2-...
Computational methods have advanced toxicology towards the development of target-specific models based on a clear cause-effect rationale. However, the predictive potential of these models presents strengths and weaknesses. On the good side, in silico models are valuable cheap alternatives to in vitro and in vivo experiments. On the other, the uncon...
Quantitative Structure-Activity Relationships are widely acknowledged predictive methods employed, for years, in organic and medicinal chemistry. More recently, they have assumed a central role also in the context of the explorative toxicology for the protection of environment and human health. However, their real-life application has not been alwa...
The potential for a compound to cause hepatotoxicity and nephrotoxicity is a matter of extreme interest for human health risk assessment. To assess liver and kidney toxicity, repeated-dose toxicity (RDT) studies are conducted mainly on rodents. However, these tests are expensive, time-consuming and require large numbers of animals. For early toxici...
The multifactorial nature of Alzheimer's disease calls for the development of multitarget agents addressing key pathogenic processes. To this end, by following a docking-assisted hybridization strategy, a number of aminocoumarins were designed, prepared and tested as monoamine oxidases (MAOs), acetyl- and butyryl-cholinesterase (AChE and BChE) inhi...
The in vivo repeated dose toxicity (RDT) test is intended to provide information on the possible risk caused by repeated exposure to a substance over a limited period of time. The measure of the RDT is the no observed adverse effect level (NOAEL) that is the dose at which no effects are observed, i.e., this endpoint indicates the safety level for a...
Repeated dose toxicity is of the utmost importance to characterize the toxicological profile of a chemical after repeated administration. Its evaluation refers to the Lowest-Observed-(Adverse)-Effect-Level (LO(A)EL) explicitly requested in several regulatory contexts, such as REACH and EC Regulation 1223/2009 on cosmetic products. So far invivo tes...
Repeated dose toxicity is of the utmost importance to characterize the toxicological profile of a chemical after repeated administration. Its evaluation refers to the Lowest-Observed-(Adverse)-Effect-Level (LO(A)EL) explicitly requested in several regulatory contexts, such as REACH and EC Regulation 1223/2009 on cosmetic products. So far in vivo te...
REACH (Registration, Evaluation, Authorization and restriction of Chemicals) and BPR (Biocide Product Regulation) regulations strongly promote the use of non-animal testing techniques to evaluate chemical risk. This has renewed the interest towards alternative methods such as QSAR in the regulatory context. The assessment of Bioconcentration Factor...
QSAR (Quantitative Structure Activity Relationship) models can be a valuable alternative method to replace or reduce animal test required by REACH. In particular, some endpoints such as bioconcentration factor (BCF) are easier to predict and many useful models have been already developed. In this paper we describe how to integrate two popular BCF m...
Questions
Question (1)
I developed a series of QSAR models from the same dataset by using different techniques (Random Forest, Artificial Neural Networks, Support Vector Machine, Naive Bayes Classifier, Decision Trees) and I need to select the best one on the basis of internal validation. I used out-of-bag statistics for Random Forest model while for others model I used Leave-Many-Out cross-validation statistics. It makes sense to compare these two kind of statistics?
