Roberto Todeschini

• full professor of chemometrics
• Professor Emeritus at Università degli Studi di Milano-Bicocca

Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of molecular weight, multiple stereocenters and higher fraction of sp³-hybridized carbons. This makes the encodin...

Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of molecular weight, multiple stereocenters and higher fraction of sp3-hybridized carbons. This makes the encodin...

The capacity to discriminate safe from dangerous compounds has played an important role in the evolution of species, including human beings. Highly evolved senses such as taste receptors allow humans to navigate and survive in the environment through information that arrives to the brain through electrical pulses. Specifically, taste receptors prov...

Multitask learning allows to model multiple tasks simultaneously through information sharing. In the context of quantitative structure–activity relationships and computational toxicology, multitask learning is gaining more and more interest, owed to its potential to improve the predictive performance of underrepresented tasks and to predict the mul...

The interest in multitask and deep learning strategies has been increasing in the last few years, in application to large and complex dataset for quantitative structure‐activity relationship (QSAR) analysis. Multitask approaches allow the simultaneous prediction of molecular properties that are related, through information sharing, whereas deep lea...

The study concerns the photodegradation of the antidepressant escitalopram (ESC), the S-enantiomer of the citalopram raceme, both in ultrapure and surface water, considering the contribution of indirect photolysis through the presence of nitrate and bicarbonate. The effect of nitrate and bicarbonate concentrations was investigated by full factorial...

Mass spectrometry (MS) is widely used for the identification of chemical compounds by matching the experimentally acquired mass spectrum against a database of reference spectra. However, this approach suffers from a limited coverage of the existing databases causing a failure in the identification of a compound not present in the database. Among th...

Minimum Spanning Tree (MST) is a well-known clustering algorithm that provides a graphical tree representation of the objects in a data set by exploiting local information to link each pair of similar objects. The a-posteriori analysis of this tree in terms of nodes and edges provides the basis to derive simple classifiers, namely semi-supervised c...

Neural networks are rapidly gaining popularity in chemical modeling and Quantitative Structure–Activity Relationship (QSAR) thanks to their ability to handle multitask problems. However, outcomes of neural networks depend on the tuning of several hyperparameters, whose small variations can often strongly affect their performance. Hence, optimizatio...

Nuclear receptors (NRs) are involved in fundamental human health processes and are a relevant target for toxicological risk assessment. To help prioritize chemicals that can mimic natural hormones and be endocrine disruptors, computational models can be a useful tool.1,2 In this work we i) created an exhaustive collection of NR modulators and ii) a...

Nuclear receptors (NRs) are involved in fundamental human health processes and are a relevant target for toxicological risk assessment. To help prioritize chemicals that can mimic natural hormones and be endocrine disruptors, computational models can be a useful tool.1,2 In this work we i) created an exhaustive collection of NR modulators and ii) a...

Multivariate regression is a fundamental supervised chemometric approach that defines the relationship between a set of independent variables and a quantitative response. It enables the subsequent prediction of the response for future samples, thus avoiding its experimental measurement. Regression approaches have been widely applied for data analys...

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...

In the analysis of complex and multivariate systems, set priorities and rank all the available objects is not a trivial task. In this framework, several multi-criteria decision-making (MCDM) techniques have been proposed, with successful applications in different research fields. However, it would be desirable to customize the ranking by weighting...

Chianti is a precious red wine and enjoys a high reputation for its high quality in the world wine market. Despite this, the production region is small and product needs efficient tools to protect its brands and prevent adulterations. In this sense, ICP-MS combined with chemometrics has demonstrated its usefulness in food authentication. In this st...

Several similarity/diversity measures for data mining, chemometrics, and chemoinformatics are presented and discussed toward the different data they are applied to. After a short presentation of the axioms for dissimilarity and similarity functions, their relationships and the required data pretreatment, the theoretical definitions and formulas of...

Multi-criteria decision making processes comprehend several ranking methods able to handle multiple and often conflicting criteria and sorting objects according to a definition of the optimality direction for each criterion. In the field of polypharmacology it can be useful for virtual screening or prioritization purposes to rank molecules distingu...

Background: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need i...

The ICCVAM Acute Toxicity Workgroup (U.S. Department of Health and Human Services), in collaboration with the U.S. Environmental Protection Agency (U.S. EPA, National Center for Computational Toxicology), coordinated the “Predictive Models for Acute Oral Systemic Toxicity” collaborative project to develop in silico models to predict acute oral syst...

Ranking and multi-criteria decision-making approaches are useful tools to analyse multivariate data and obtain useful insights into data structure and the relationships between samples and variables. In this study, we present a new ranking approach, named Deep Ranking Analysis by Power Eigenvectors (DRAPE), which is based on the Power-Weakness Rati...

Quantitative Structure – Activity Relationship (QSAR) models play a central role in medicinal chemistry, toxicology and computer‐assisted molecular design, as well as a support for regulatory decisions and animal testing reduction. Thus, assessing their predictive ability becomes an essential step for any prospective application. Many metrics have...

High-level data fusion strategies combine and integrate predictions obtained by means of individual models calibrated on single information sources. With respect to other fusion techniques, high-level methods aim at improving prediction performances, as well as reducing the total uncertainty associated with the final combined outcome. In fact, when...

Local classification models were used to establish quantitative structure-activity relationships (QSARs) of bioactive di-, tri- and tetrapeptides, with their capacity to inhibit Angiotensin Converting Enzyme (ACE). These discrete models can thus predict this activity for other peptides obtained from functional foods. These types of peptides allow s...

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Natural products offer unexplored molecular frameworks for the development of chemical leads and innovative drugs. However, the structural complexity of natural products compared with synthetic drug-like molecules often limits the scaffold hopping potential of natural-product-inspired molecular design. Here we introduce a holistic molecular represe...

El objetivo de este trabajo es la calibración de una relación cuantitativa estructura-actividad (QSAR) para la predicción de la actividad antiinflamatoria de alcaloides. La base de datos considerada está constituida por 100 moléculas, 52 activas y 48 inactivas. Cada estructura molecular fue modelada mediante mecánica molecular (MM+) y el método sem...

Molecular descriptors capture diverse parts of the structural information of molecules and they are the support of many contemporary computer-assisted toxicological and chemical applications. After briefly introducing some fundamental concepts of structure–activity applications (e.g., molecular descriptor dimensionality, classical vs. fingerprint d...

In the last ten years, the concept of activity cliff gained a lot of interest by medicinal chemists and QSAR modellers. The reason of this interest is its capacity to highlight problematic as well as interesting situations in analysing the activity/property of pairs of compounds, thus focusing the research on the reasons why two similar compounds s...

The assessment of the classification performance can be based on class indices, such as sensitivity, specificity and precision, which describe the classification results achieved on each modelled class. However, in several situations, it is useful to represent the global classification performance with a single number. Therefore, several measures h...

A new chemoinformatic approach, called Mapping of Activity through Dichotomic Scores, is introduced. Its goal is the supervised projection of molecules, represented with strings of binary digits expressing the presence or absence of selected structural features, onto a novel 2-dimensional space, which highlights regions of active (inactive) molecul...

Molecular descriptors encode a wide variety of molecular information and have become the support of many contemporary chemoinformatic and bioinformatic applications. They grasp specific molecular features (e.g., geometry, shape, pharmacophores, or atomic properties) and directly affect computational models, in terms of outcome, performance, and app...

REACH requires that all chemicals produced or imported for more than 1 ton/year must be tested for ready biodegradability, a screening test for the assessment of chemical persistence. Since REACH encourages the use of in-silico approaches, several Quantitative Structure-Activity Relationship models have been calibrated to predict this property. Pre...

This work describes a novel approach based on advanced molecular similarity to predict the sweetness of chemicals. The proposed Quantitative Structure-Taste Relationship (QSTR) model is an expert system developed keeping in mind the five principles defined by the Organization for Economic Co-operation and Development (OECD) for the validation of (Q...

Atmospheric pollutants can originate the decay of historic paintings exposed to the outdoor elements. This is a cause of great concern, since such contaminants can produce physical-chemical alterations manifested initially in undesirable color change. This paper tests an unsupervised multivariate approach on discrete data color parameters in a pion...

Despite the number of available chemicals growing exponentially, testing of their toxicological and environmental behavior is often a critical issue and alternative strategies are required. Additionally, there is the need to predict properties of not yet synthesized compounds to reduce the costs of synthesis, selecting only those that have the maxi...

There is an increasing necessity for multidisciplinary collaborations in molecular science between experimentalists and theoretical scientists, as well as among theoretical scientists from different fields. One of the more important forces driving this necessity is the accumulation of large amounts of data as a result of important advances in Chemi...

This communication deals with the scientific problem of evaluating the similarity between two chemical systems, each described by a finite discrete set of elements/members, which are in turn p-dimensional vectors of chemical/biological descriptors. A variant of the Hausdorff measure, called Hausdorff-like similarity (Hs), is proposed aimed at takin...

The aim of this work was the development of an expert system model based on quantitative structure-taste relationships (QSTRs) to predict the sweetness of molecules. Molecules were described by extended connectivity fingerprints (ECFPs) and conformation-independent molecular descriptors (MDs).

El objetivo de este trabajo fue el desarrollo de dos modelos preliminares basados en las relaciones cuantitativas estructura-actividad (QSARs), usando los métodos de clasificación N3 y PLSDA, para clasificar moléculas dulces y no dulces.

En este trabajo se presenta el desarrollo de una relación cuantitativa estructura-actividad basado en el nuevo método de clasificación de los N-vecinos (QSAR-N3) para péptidos bioactivos (PBA) con capacidad de inhibir enzima convertidora de la angiotensina (ACE)

Molecular descriptors capture diverse structural information of molecules and are a prerequisite for ligand-based similarity searching. In this study, we introduce topological matrix-based descriptors to virtual screening for hit discovery. We evaluated the usefulness of matrix-based descriptors in a retrospective setting and compared them with top...

Validation is an essential step of QSAR modelling and it can be performed by both internal validation techniques (e.g. cross-validation, bootstrap) or by an external set of test objects, that is, objects not used for model development and/or optimisation. The evaluation of model predictive ability is then established comparing experimental and pred...

Cytochromes P450 (CYP) are the main actors in the oxidation of xenotibiotics and play a crucial role in drug safety, persistence, bioactivation, and drug-drug/food-drug interaction. This work aims to develop Quantitative Structure-Activity Relationship (QSAR) models to predict the drug interaction with two of the most important CYP isoforms, namely...

In this paper, a new concept of similarity is introduced with the aim of detecting higher-order similarities among objects and meta-distances and meta-similarities are derived from it. A total of 100 meta-distances were obtained from a set of ten classical distances and were compared, in terms of classification performances, against classical dista...

A systematic guide to the growing jungle of citation indices and other bibliometric indicators. Written with the aim of providing a complete and unbiased overview of all available statistical measures for scientific productivity, the core of this reference is an alphabetical dictionary of indices and other algorithms used to evaluate the importance...

This chapter presents a list of terms regarding statistical measures for scientific productivity, commencing with the Greek Letters such as µ, π, ϕ, and ρ. Scientific outputs, references, and citations represent the observable features or the raw facts on which bibliometric indicators are built. Bibliometric indicators were originally developed for...

Keywords: paint dosimeter; natural aging test; portable spectrophotometer; PCA; Decay of outdoor paint artworks due to polluted urban atmospheres is an outstanding problem with paramount cultural and economic consequences that is attracting the attention of researchers in the last decades [1][2]. In this context, evaluation of the effects of urban...

Keywords: paint mock-ups, UV artificial ageing test; MALDI-TOF-MS; micro-Raman spectroscopy; portable spectrophotometer; similarity index. Degradation and darkening of outdoor paintings exposed to polluted and coastal urban atmosphere is acquiring significance due to new atmospheric contaminants and the effects of climate change. This problem is en...

This paper proposes a scheme to predict whether a compound (1) is mainly stored within lipid tissues, (2) has additional storage sites (e.g., proteins), or (3) is metabolized/eliminated with a reduced bioconcentration. The approach is based on two validated QSAR (Quantitative-Structure Activity Relationship) trees, whose salient features are: (a) d...

Similarity searching, a technique used for ligand-based virtual screening in drug discovery, exploits the structural information of known active compounds to find new ones with the desired biological activity. The effectiveness of similarity searching can be enhanced by combining independent searches, executed with different reference structures, t...

The aim of this work was the calibration and validation of mathematical models based on a quantitative structure–activity relationship approach to discriminate sweet, tasteless and bitter molecules. The sweet-tasteless and the sweet-bitter datasets included 566 and 508 compounds, respectively. A total of 3763 conformation-independent Dragon molecul...

Background: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemica...

Two novel classification methods, called N3 (N-Nearest Neighbours) and BNN (Binned Nearest Neighbours), are proposed. Both methods are inspired by the principles of the K-Nearest Neighbours (KNN) method, being both based on object pairwise similarities. Their performance was evaluated in comparison with nine well-known classification methods. In or...

This work presents a modified version of Hasse Diagram technique, the weighted Regularized Hasse (wR-Hasse), which aims to reduce the number of incomparabilities and derive weighted rankings of the objects. These objectives are accomplished by: (a) introducing a mathematical threshold on the definition of incomparability and (b) weighting criteria...

Congress of Theoretical Chemists of Latin Expression. Turin, Italy. 26-31 July

Several similarity/diversity measures for data mining and chemometrics are presented and discussed toward the different data they are applied to. After a short presentation of the axioms for dissimilarity and similarity functions, their relationships, and the required data pretreatment, the theoretical definitions and formulas of distance and simil...

REACH regulation demands information about acute toxicity of chemicals towards fish and supports the use of QSAR models, provided compliance with OECD principles. Existing models present some drawbacks that may limit their regulatory application. In this study, a dataset of 908 chemicals was used to develop a QSAR model to predict the LC50 96 hours...

A series of 436 Munro database chemicals were studied with respect to their corresponding experimental LD50 values to investigate the possibility of establishing a global QSAR model for acute toxicity. Dragon molecular descriptors were used for the QSAR model development and genetic algorithms were used to select descriptors better correlated with...

In 1971 McClelland obtained lower and upper bounds for the total pi-electron energy. We now formulate the generalized version of these bounds, applicable to the energy-like expression E-X =, Sigma(n)(i=1)vertical bar x(i) - (x) over bar vertical bar where x(1),x(2),...,x(n) are any real numbers, and (x) over bar is their arithmetic mean. In particu...

In this preliminary study, mathematical models based on quantitative structure property relationships (QSPR) were applied in order to analyze how molecular structure of chloroprene rubber accelerators relates to their rheological and mechanical properties. QSPR models were developed in order to disclose which structural features mainly affect the m...

Several classical and two recently proposed Applicability Domain (AD) approaches were implemented on a set of three classification models retrieved from a published study to assess the ready biodegradability of chemicals. Each model was associated with an optimal AD approa¬ch based on its ability to a) retain maximum test molecules within the model...

This work aimed to compare the Reshaped Sequential Replacement (RSR) method with some reference variable selection techniques for QSPR (Quantitative Structure-Property Relationship) modelling in regression. Results highlighted the capability of RSR to select optimal subsets of variables and to perform an extensive exploration of the variables space...

In this study, a QSAR model was developed from a data set consisting of 546 organic molecules, to predict acute aquatic toxicity toward Daphnia magna. A modified k-Nearest Neighbour (kNN) strategy was used as the regression method, which provided prediction only for those molecules with an average distance from the k nearest neighbours lower than a...

Quantitative Structure-Activity Relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss: (i) the development and evolution of QSAR; (ii) the...

Background With the growing popularity of using QSAR predictions towards regulatory purposes, such predictive models are now required to be strictly validated, an essential feature of which is to have the model’s Applicability Domain (AD) defined clearly. Although in recent years several different approaches have been proposed to address this goal,...

The European REACH regulation requires information on ready biodegradation, which is a screening test to assess the biodegradability of chemicals. At the same time REACH encourages the use of alternatives to animal testing which includes predictions from QSAR models. The aim of this study was to build QSAR models to predict ready biodegradation of...

One of the OECD principles for model validation requires defining the Applicability Domain (AD) for the QSAR models. This is important since the reliable predictions are generally limited to query chemicals structurally similar to the training compounds used to build the model. Therefore, characterization of interpolation space is significant in de...