Review of QSAR Models and Software Tools for Predicting of Genotoxicity and Carcinogenicity

This review of QSARs for genotoxicity and carcinogenicity was performed in a broad sense, considering both models available in software tools and models that are published in the literature. The review considered the potential applicability of diverse models to pesticides as well as to other types of regulated chemicals and pharmaceuticals. The availability of models and information on their applicability is summarised in tables, and a range of illustrative or informative examples are described in more detail in the text. In many cases, promising models were identified but they are still at the research stage. For routine application in a regulatory setting, further efforts will be needed to explore the applicability of such models for specific purposes, and to implement them in a practically useful form (i.e. user-friendly software). It is also noted that a range of software tools are research tools suitable for model development, and these require more specialised expertise than other tools that are aimed primarily at end-users such as risk assessors. It is concluded that the most useful models are those which are implemented in software tools and associated with transparent documentation on the model development and validation process. However, it is emphasised that the assessment of model predictions requires a reasonable amount of QSAR knowledge, even if it is not necessary to be a QSAR practitioner.JRC.DG.I.6-Systems toxicolog

The Use of Computational Methods in the Toxicological Assessment of Chemicals in Food: Current Status and Future Prospects

A wide range of chemicals are intentionally added to, or unintentially found in, food products, often in very small amounts. Depending on the situation, the experimental data needed to complete a dietary risk assessment, which is the scientific basis for protecting human health, may not be available or obtainable, for reasons of cost, time and animal welfare. For example, toxicity data are often lacking for the metabolites and degradation products of pesticide active ingredients. There is therefore an interest in the development and application of efficient and effective non-animal methods for assessing chemical toxicity, including Quantitative Structure-Activity Relationship (QSAR) models and related computational methods. This report gives an overview of how computational methods are currently used in the field of food safety by national regulatory bodies, international advisory organisations and the food industry. On the basis of an international survey, a comprehensive literature review and a detailed QSAR analysis, a range of recommendations are made with the long-term aim of promoting the judicious use of suitable QSAR methods. The current status of QSAR methods is reviewed not only for toxicological endpoints relevant to dietary risk assessment, but also for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their reaction products. By referring to the concept of the Threshold of Toxicological Concern (TTC), the risk assessment context in which QSAR methods can be expected to be used is also discussed. This Joint Research Centre (JRC) Reference Report provides a summary and update of the findings obtained in a study carried out by the JRC under the terms of a contract awarded by the European Food Safety Authority (EFSA).JRC.DG.I.6-Systems toxicolog

Investigation of in Silico Modelling to Predict the Human Health Effects of Cosmetics Ingredients

Animal experiments have been the standard method to assess the safety of chemicals used in cosmetic products for decades. However, public opinion has continued to demand that in vivo hazard identification methods conducted on animals are replaced with alternative methods. Research on alternative methods to replace in vivo toxicity testing continually increased over the past few decades with different alternatives developed, such as in vitro, in chemico and in silico approaches. Although different alternative techniques can be employed, no single technique can solely replace the complexity and an in vivo test, especially for chronic effects. Therefore, integrated testing strategies that can utilise the information from all available alternative testing approaches have been developed. Within the Adverse Outcome Pathway (AOP) paradigm, the molecular initiating event(s) MIE can be induced by several chemical key features which can be captured by structural alerts. When structural alerts for a MIE are compiled and supported by mechanistic and toxicity information confirming the induction of the same MIE, then they can be considered as an in silico profiler. The overall aim of the work presented in this thesis was to assess the current in silico profilers for carcinogenicity (both genotoxic and non-genotoxic), mutagenicity and skin sensitisation through assessment using multiple high-quality experimental databases. The research presented herein demonstrates the ability to assess the positive predictivity of two types of structural alert, mechanism- and chemistry-based that pertain to the endpoints and proposes ways to improve the overall accuracy of these profilers. In this context, this study has given an insight to those alerts that may be found equally in endpoint-positive or negative compounds, and those which may be more effectively utilised to form groups of analogues for read across predictions. A detailed analysis of positive predictivity of the available mutagenicity, carcinogenicity and skin sensitisation structural alerts and profilers Page 3 within the OECD QSAR Toolbox against experimental data is presented. This investigation showed the structural alerts that are accurate as such, and those that may need further refinement, or their use may need to be reconsidered. In addition, the relationship between scaffolds of a range of diverse compounds and carcinogenicity showed that a total of 17 carcinogenicity scaffolds could be identified from the available databases and could be used as a base for an in silico profiler. This work has also determined the need for further in-depth research in this area to study the suitability and merits of each of the alerts within the profilers currently included in the OECD QSAR Toolbox, and other in silico toxicity platforms, to identify the possibilities for improvement in their performance. This will, by implication, also improve the reliability of chemical read-across and grouping/categorisation for classification, labelling and risk assessment for regulatory use of the in silico methods

Large Scale Synthesis and Derivatization of Corannulene: The Smallest Buckybowl

The major part of my thesis work includes large scale production of corannulene, C20H10, a bowl-shaped Polycyclic Aromatic Hydrocarbon. Over the road towards corannulene via tetramethylfluoranthene, we improved several steps of the existing multistep procedure. These improvements include: -Nucleophilic displacement of chloride in 2,7-dimethyl-1-chloromethyl- naphthalene with cyanide gave an excellent yield of 2,7-dimethyl-1-naphthalene- acetonitrile when performed in acetonitrile instead of DMSO or acetone/water. -Oxidation of 3,8-dimethyl-1-acenaphthenone to 3,8-dimethylacenaphthaquinone was successfully achieved with HBr/DMSO instead of selenium dioxide, which usually requires tedious work up. -Overall yield of 3,8-dimethylacenaphth- aquinone was greatly improved in comparison with the previous reports. -Palladium catalyzed large scale debromination of tetrabromocorannulene was accomplished within thirty minutes of brief reflux, in contrast to the original Zn/KI method which took weeks for completion. Alternative palladium catalyzed ring closure methods where tested for synthesis of 1,6,7,10-tetramethylfluroanthene (25), a key intermediate in corannulene production. A structurally similar system, 7,10-dimethylfluoranthene was synthesized by this new approach in low yield. Unfortunately, we did not succeed in the synthesis of 25 using similar methodology, since all our attempts to produce the prerequisite 2,7-dimethyl-1-naphthylboronic acid failed. Elaboration of the corannulene core by coupling tetrabromocorannulene with p-methoxyphenylboronic acid and p-methoxycarbonylphenylboronic acid under Suzuki conditions resulted in formation of two vital intermediates which can be used to build capsules with corannulene caps

Adaptation of High-Throughput Screening in Drug Discovery—Toxicological Screening Tests

High-throughput screening (HTS) is one of the newest techniques used in drug design and may be applied in biological and chemical sciences. This method, due to utilization of robots, detectors and software that regulate the whole process, enables a series of analyses of chemical compounds to be conducted in a short time and the affinity of biological structures which is often related to toxicity to be defined. Since 2008 we have implemented the automation of this technique and as a consequence, the possibility to examine 100,000 compounds per day. The HTS method is more frequently utilized in conjunction with analytical techniques such as NMR or coupled methods e.g., LC-MS/MS. Series of studies enable the establishment of the rate of affinity for targets or the level of toxicity. Moreover, researches are conducted concerning conjugation of nanoparticles with drugs and the determination of the toxicity of such structures. For these purposes there are frequently used cell lines. Due to the miniaturization of all systems, it is possible to examine the compound’s toxicity having only 1–3 mg of this compound. Determination of cytotoxicity in this way leads to a significant decrease in the expenditure and to a reduction in the length of the study

Characteristics of fine and ultrafine aerosols in the London underground.

Underground railway systems are recognised spaces of increased personal pollution exposure. We studied the number-size distribution and physico-chemical characteristics of ultrafine (PM0.1), fine (PM0.1-2.5) and coarse (PM2.5-10) particles collected on a London underground platform. Particle number concentrations gradually increased throughout the day, with a maximum concentration between 18:00 h and 21:00 h (local time). There was a maximum decrease in mass for the PM2.5, PM2.5-10 and black carbon of 3.9, 4.5 and ~ 21-times, respectively, between operable (OpHrs) and non-operable (N-OpHrs) hours. Average PM10 (52 μg m-3) and PM2.5 (34 μg m-3) concentrations over the full data showed levels above the World Health Organization Air Quality Guidelines. Respiratory deposition doses of particle number and mass concentrations were calculated and found to be two- and four-times higher during OpHrs compared with N-OpHrs, reflecting events such as train arrival/departure during OpHrs. Organic compounds were composed of aromatic hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) which are known to be harmful to health. Specific ratios of PAHs were identified for underground transport that may reflect an interaction between PAHs and fine particles. Scanning transmission electron microscopy (STEM) chemical maps of fine and ultrafine fractions show they are composed of Fe and O in the form of magnetite and nanosized mixtures of metals including Cr, Al, Ni and Mn. These findings, and the low air change rate (0.17 to 0.46 h-1), highlight the need to improve the ventilation conditions

Characteristics of fine and ultrafine aerosols in the London underground

\ua9 2022 The Authors. Underground railway systems are recognised spaces of increased personal pollution exposure. We studied the number-size distribution and physico-chemical characteristics of ultrafine (PM0.1), fine (PM0.1–2.5) and coarse (PM2.5–10) particles collected on a London underground platform. Particle number concentrations gradually increased throughout the day, with a maximum concentration between 18:00 h and 21:00 h (local time). There was a maximum decrease in mass for the PM2.5, PM2.5–10 and black carbon of 3.9, 4.5 and ~ 21-times, respectively, between operable (OpHrs) and non-operable (N-OpHrs) hours. Average PM10 (52 μg m−3) and PM2.5 (34 μg m−3) concentrations over the full data showed levels above the World Health Organization Air Quality Guidelines. Respiratory deposition doses of particle number and mass concentrations were calculated and found to be two- and four-times higher during OpHrs compared with N-OpHrs, reflecting events such as train arrival/departure during OpHrs. Organic compounds were composed of aromatic hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) which are known to be harmful to health. Specific ratios of PAHs were identified for underground transport that may reflect an interaction between PAHs and fine particles. Scanning transmission electron microscopy (STEM) chemical maps of fine and ultrafine fractions show they are composed of Fe and O in the form of magnetite and nanosized mixtures of metals including Cr, Al, Ni and Mn. These findings, and the low air change rate (0.17 to 0.46 h−1), highlight the need to improve the ventilation conditions

NMR and Computational Characterization of Protein Structure and Ligand Binding

Nuclear magnetic resonance (NMR) techniques combined with computational methods such as docking and cheminformatics were used to characterize protein structure and ligand binding. The thioredoxin system of Mycobacterium tuberculosis consists of a thioredoxin reductase and at least three thioredoxins. This system is responsible for maintaining the cellular protein thiol redox state in normal state. This maintenance is important as the bacterium is engulfed by the human macrophage. Here it is bombarded by reactive oxygen and nitrogen species in an attempt to disrupt normal cellular function in part by perturbing the protein thiols. To this end, the solution structures of the three thioredoxins, A, B, and C, in the oxidized state were solved by NMR. Additionally, the reduced form of thioredoxin C was solved as well. Docking and NMR chemical shit pertubation experiments show promise for the inhibition of the thioredoxin C-thioredoxin reductase catalytic turnover. Automated docking is the process of computationally predicting how tightly a ligand binds to a protein and the correct orientation. The docking of an in-house collection of 10,590 chemicals into a protein called dual specificity phosphatase 5 identified potential ligands. These compounds were characterized as inhibitors in a phosphatase assay and as ligands in NMR chemical shift perturbation experiments. Based on a promising lead compound, additional chemicals were identified using cheminformatics and subjected to the same experimental verification

Solid-state nanopores: a new platform for DNA biomarker discovery

Solid-state (SS) nanopores emerged as a molecular detection platform in 2001, offering many advantages over their biological counterparts, α-hemolysin nanopores (α-HL). These advantages include better chemical, electrical, mechanical, and thermal stability, as well as size tunability and device integration. In addition, the size of α-HL restricts its application to translocations of single-stranded polynucleotides (ssDNA and ssRNA). This research project focused on developing a SS-nanopore platform for biomarker detection, based on differentiating ssDNA and double-stranded DNA (dsDNA) at the single-molecule scale. Reported dsDNA translocation measurements result in an average residence time of ~ 30 ns/bp, so the temporal resolution required for detection of small DNA duplexes can exceed available bandwidth limitations. To address this issue, several system parameters were explored in order to slow down translocation speed, thereby increasing temporal resolution and signal-to-noise ratio. These parameters included: applied voltage, pH, pore geometry, DNA binding agents, salt composition and concentration, and temperature. Experimental findings showed that SS-nanopores can be precisely fabricated using a controlled helium ion milling technique, acidic conditions cause DNA depurination that results in slower translocation durations, and single-stranded binding proteins (SSBs) bind preferentially to ssDNA, forming complexes with distinct translocation characteristics that permit large (> 7 kb) ds- and ssDNA to be effectively distinguished. Together, these data show that SS-nanopores can serve as a tool to electronically detect the presence and relative concentration of target DNA molecules with ultrahigh sensitivity, thus demonstrating their potential utility as a biomarker discovery platform in both biomedical and environmental applications

Exploring Molecular Diversity: There is Plenty of Room at Markush's

L'estratègia de les etapes inicials del descobriment de fàrmacs està normalment basada en un procés anomenat hit-to-lead que implica un extens estudi entorn de la síntesi de derivats d'una molècula original que prèviament hagi mostrat certa activitat biològica davant d'una diana concreta. Per tant, aquest procés comporta la síntesi de molts anàlegs que descriurien una subquimioteca, que generalment evidencia que aquests estudis estan molt focalitzats al voltant de l'espai químic del compost original. Així i tot, quan aquesta molècula és finalment patentada, es descriu un espai químic molt més vast per mitjà d'estructures Markush donant per suposat que alguns dels seus derivats puguin presentar també activitat biològica. Tot i això, la presència d'aquestes estructures no implica la síntesi comprovada de tota la biblioteca molecular sinó només una petita mostra de la mateixa. La nostra hipòtesi és que hi ha una gran part de l’espai químic d’aquestes biblioteques que està sense explorar i pot amagar possibles candidats que poden fins i tot superar l’activitat del hit original. A través d'aquest projecte, es proposa una alternativa que sosté que una selecció racional de poques molècules – basat en l'agrupament segons semblança molecular – pot representar de manera més significativa l'espai químic establert, oferint la possibilitat d'explorar regions desconegudes que podrien amagar més potencial biològic. Després de revisar els darrers fàrmacs aprovats per la FDA en el període del 2008 al 2020 i la base de dades de molècules bioactives de ChEMBL, s'ha dut a terme una exploració de l'ampli espai químic resultant de molècules petites amb propietats similars a les dels medicaments per definir nous espais accessibles que podrien ocultar activitat. Els resultats obtinguts de set casos d'estudis reals han demostrat que tant la selecció racional com l’aleatòria representen més significativament les biblioteques combinatòries declarades a les patents, que les molècules descrites fins ara. S'han realitzat dos estudis pràctics que implementen aquesta metodologia suggerida per descriure millor l'espai químic del fàrmac antipalúdic Tafenoquina i del Dacomitinib, un inhibidor de tirosina cinases de segona generació per al tractament del càncer de pulmó de cèl·lules no petites. L’exploració de l’espai químic d’aquestes dues famílies ha portat a la síntesi racional de set anàlegs antipalúdics i vuit inhibidors de cinases que han mostrat interessants activitats inhibidores. Aquests resultats demostren que l'aplicació de la quimioinformàtica per a la selecció de biblioteques pot millorar la capacitat d'inspeccionar millor els conjunts de dades químiques per identificar nous compostos precandidats i representar grans biblioteques per a posteriors campanyes de reposicionament.La estrategia de las etapas iniciales del descubrimiento de fármacos está normalmente basada en un proceso denominado hit-to-lead que implica un extenso estudio entorno a la síntesis de derivados de una molécula original que previamente haya expresado cierta actividad biológica frente a una diana concreta. Por ende, este proceso conlleva la síntesis de muchos análogos que describirían una sublibrería química, la cual generalmente evidencia que estos estudios están muy focalizados alrededor del espacio químico del compuesto original. Aún y así, cuando esta molécula es finalmente patentada, se describe un espacio químico mucho más vasto por medio de estructuras Markush teorizando que algunos de sus derivados puedan presentar también actividad biológica. Sin embargo, la presencia de estas estructuras no implica la síntesis comprobada de toda la biblioteca molecular sino solo una pequeña muestra de la misma. Nuestra hipótesis es que hay una gran parte del espacio químico de estas bibliotecas que está sin explorar y puede ocultar posibles candidatos que pueden hasta superar la actividad del hit original. A través de este proyecto, se propone una alternativa que sostiene que una selección racional de pocas moléculas – fundada en el agrupamiento según su similitud química – puede representar de manera más significativa el espacio químico establecido, ofreciendo la posibilidad de explorar regiones desconocidas que podrían ocultar más potencial biológico. Después de revisar los últimos fármacos aprobados por la FDA en el período de 2008 a 2020 y la base de datos de moléculas bioactivas de ChEMBL, se ha llevado a cabo una exploración del amplio espacio químico resultante de moléculas pequeñas con propiedades similares a las de los medicamentos para definir nuevos espacios accesible que podrían ocultar actividad. Los resultados obtenidos de siete casos de estudios reales han demostrado que tanto la selección racional como la aleatoria representan más significativamente las bibliotecas combinatorias declaradas en las patentes que las moléculas descritas hasta la fecha. Se han desarrollado dos estudios prácticos que implementan esta metodología sugerida para describir mejor el espacio químico del fármaco antipalúdico Tafenoquina y Dacomitinib, un inhibidor de la tirosina quinasa de segunda generación para el tratamiento del cáncer de pulmón de células no pequeñas. La exploración del espacio químico de estas dos familias ha llevado a la síntesis racional de siete análogos antipalúdicos y ocho inhibidores de quinasas que han mostrado interesantes actividades inhibidoras. Estos resultados demuestran que la aplicación de la quimioinformática para la selección de bibliotecas puede mejorar la capacidad de inspeccionar mejor los conjuntos de datos químicos para identificar nuevos potenciales hits y representar grandes bibliotecas para fines de reposicionamiento.The early Drug Discovery strategy is commonly based on a hit-to-lead process which involves large research on the synthesis of derivatives of an original molecule that had previously shown biological activity against a specific biological target. Therefore, this process implies the synthesis of many analogs leading to the description of a chemical sub-library which generally leads to a highly focused study on the chemical space nearby the hit compound. However, when this drug is finally patented, a wider chemical space derived from a Markush structure is described, theorizing that some analogs within may present biological activity. Nevertheless, this claim involving the Markush structure does not imply the proven synthesis of all the chemical library but just a small population of it. We hypothesize that there is a great part of the chemical space of these libraries that is unexplored and can hide potential lead candidates which may even surpass the activity of the original hit. Through this project, an alternative is proposed claiming that a rational selection of a short sample of small molecules – founded on similarity-based clustering – can represent more significatively the stated chemical space offering the possibility to explore the unknown space that could hide more potential biological activity. After a review on the latest approved drugs by the FDA in the period from 2008 to 2020 and the ChEMBL database of bioactive molecules, an exploration of the resulting wide chemical space of small molecules with drug-like properties has been assessed in order to define accessible spots that might hide biological activity. The obtained results from seven real cases of study have proven that random and rationally selected molecules represent more significantly the combinatorial libraries stated in the patents rather than the reported molecules until date. Furthermore, two practical studies implementing our suggested methodology have been developed to better describe the chemical space of the antimalarial drug Tafenoquine and Dacomitinib, a second-generation tyrosine kinase inhibitor for non-small-cell lung cancer treatment. The assessment driven by a better chemical space exploration of these two families have led to the rational synthesis of seven antimalarial analogs and eight kinase inhibitors which have shown interesting inhibitory activities. Our results evince that the application of cheminformatics for library selection may improve the ability to better inspect chemical datasets in order to identify new potential hits and represent large libraries for further reprofiling purposes