SAR Database Research Articles

Identification and deformation analysis of potential landslides after the Jiuzhaigou earthquake by SBAS-InSAR.

A World Natural Heritage Site, Jiuzhaigou, is the first nature reserve in China whose primary purpose is to protect natural scenery. On August 8, 2017, a Ms 7.0 earthquake caused many unstable slopes in Jiuzhaigou, Sichuan Province, China. In the extreme storm conditions that follow, the unstable slopes tend to develop into potential landslides, which can cause many casualties and property losses in scenic areas. Sentinel-1A ascending orbit data were obtained in this paper to establish a SAR database. The large-scale deformation rate map of the study area was obtained using a small baseline set InSAR technology. The potential landslides in the deformation area are preliminarily confirmed with remote sensing interpretation. The field verification is further carried out by studying the deformation information of the characteristic points on the potential landslides. The results show that 13 deformation zones were preliminarily identified, and three typical deformation zones were selected for coupling verification and identified as potential landslides. At the same time, further analysis shows that the four potential landslides have been in continuous linear deformation for a long time since the earthquake, posing a severe threat to the safety of local people's lives and property. The research results provide a reference for the early identification and warning of potential landslides in earthquake-prone regions.

In Vitro, Molecular Docking and In Silico ADME/Tox Studies of Emodin and Chrysophanol against Human Colorectal and Cervical Carcinoma.

Anthraquinones (AQs) are present in foods, dietary supplements, pharmaceuticals, and traditional treatments and have a wide spectrum of pharmacological activities. In the search for anti-cancer drugs, AQ derivatives are an important class. In this study, anthraquinone aglycons chrysophanol (Chr), emodin (EM) and FDA-approved anticancer drug fluorouracil were analyzed by molecular docking studies against receptor molecules caspase-3, apoptosis regulator Bcl-2, TRAF2 and NCK-interacting protein kinase (TNIK) and cyclin-dependent protein kinase 2 (CDK2) as novel candidates for future anticancer therapeutic development. The ADMET SAR database was used to predict the toxicity profile and pharmacokinetics of the Chr and EM. Furthermore, in silico results were validated by the in vitro anticancer activity against HCT-116 and HeLa cell lines to determine the anticancer effect. According to the docking studies simulated by the docking program AutoDock Vina 4.0, Chr and EM had good binding energies against the target proteins. It has been observed that Chr and EM show stronger molecular interaction than that of the FDA-approved anticancer drug fluorouracil. In the in vitro results, Chr and EM demonstrated promising anticancer activity in HCT-116 and HeLa cells. These findings lay the groundwork for the potential use of Chr and EM in the treatment of human colorectal and cervical carcinomas.

Identification of substances with a carcinogenic potential in spray-formulated engine/brake cleaners and lubricating products, available in the European Union (EU) – based on IARC and EU-harmonised classifications and QSAR predictions

Spray-formulated engine/brake cleaners and lubricating agents are widely used to maintain machines. The occupational exposure to their aerosols is evident. To assess the carcinogenic potential of these products, we identified such products available in the European Union (EU). We built a database with CAS numbers of 1) mono-constituent substances, and 2) multi-constituent-substances, and unknown-or-variable-composition,-complex-reaction-products-and-biological-materials (multi-constituent/UVCBs). The compositions of multi-constituent/UVCBs were unravelled with European Chemicals Agency (ECHA) registration dossiers. To identify carcinogenic potentials, we searched for 1) International Agency for Research on Cancer (IARC) classification; 2) Harmonised classifications in Annex VI to the EU classification, labelling and packaging (CLP) Regulation; and 3) whether they had a Danish Environmental Protection Agency advisory CLP self-classification based on quantitative structure-activity relationships (QSARs) for genotoxicity and carcinogenicity in the Danish (Q)SAR Database. In 82 products, we identified 332 mono-constituent substances and 44 multi-constituent/UVCBs. Six substances were either IARC 1 or 2B classified. Twelve mono-constituent substances and 22 multi-constituent/UVCBs had harmonised classifications as Carcinogenic Category 1A, 1B or 2, while nine substances fulfilled the QSAR-based advisory self-classification algorithms for mutagenicity or carcinogenicity. At the product level, 39 products contained substances of carcinogenic concern by either IARC, harmonised classification or QSAR. We conclude that in the investigated EU marketed spray-formulated engine/brake cleaners and lubricants, 24 of 332 mono-constituent substances and 28 of 44 multi-constituent/UVCBs had a carcinogenic potential. At the product level, 39 of 82 contained substances with an identified carcinogenic potential. Regulators and manufacturers can use this determination of carcinogenic potential to decrease occupational risk.

Asthma-inducing potential of 28 substances in spray cleaning products-Assessed by quantitative structure activity relationship (QSAR) testing and literature review.

Exposure to spray cleaning products constitutes a potential risk for asthma induction. We set out to review whether substances in such products are potential inducers of asthma. We identified 101 spray cleaning products for professional use. Twenty‐eight of their chemical substances were selected. We based the selection on (a) positive prediction for respiratory sensitisation in humans based on quantitative structure activity relationship (QSAR) in the Danish (Q)SAR Database, (b) positive QSAR prediction for severe skin irritation in rabbits and (c) knowledge on the substances' physico‐chemical characteristics and toxicity. Combining the findings in the literature and QSAR predictions, we could group substances into four classes: (1) some indication in humans for asthma induction: chloramine, benzalkonium chloride; (2) some indication in animals for asthma induction: ethylenediaminetetraacetic acid (EDTA), citric acid; (3) equivocal data: hypochlorite; (4) few or lacking data: nitriloacetic acid, monoethanolamine, 2‐(2‐aminoethoxy)ethanol, 2‐diethylaminoethanol, alkyldimethylamin oxide, 1‐aminopropan‐2‐ol, methylisothiazolinone, benzisothiazolinone and chlormethylisothiazolinone; three specific sulphonates and sulfamic acid, salicylic acid and its analogue sodium benzoate, propane‐1,2‐diol, glycerol, propylidynetrimethanol, lactic acid, disodium malate, morpholine, bronopol and benzyl alcohol. In conclusion, we identified an asthma induction potential for some of the substances. In addition, we identified major knowledge gaps for most substances. Thus, more data are needed to feed into a strategy of safe‐by‐design, where substances with potential for induction of asthma are avoided in future (spray) cleaning products. Moreover, we suggest that QSAR predictions can serve to prioritise substances that need further testing in various areas of toxicology.

Digital Elevation Model resolution: Effects on the chronometry-oriented morphological analysis of monogenetic scoria cones in the Sierra Chichinautzin, central Mexico

Morphological characterization of monogenetic cones provides essential information on different genetic, evolutionary, and hazard-related features of dispersive volcanism. Specifically, it may be used to measure the degree of erosional shape alteration of scoria cones, and from there, to estimate the age of individual volcanoes in extensive volcanic fields and the hazard implications of the cones' age distribution. Here we compare diverse morphometric parameters, some resulting from the elevation profiles analyses, and a novel one obtained from a shape characterization of elevation contours using Elliptical Fourier Descriptors, of 19 radiometrically-dated monogenetic scoria cones in the Sierra Chichinautzin Volcanic Field in Central Mexico. The parameters were calculated from two independent Digital Elevation Models with different resolutions: the 12 m resolution TanDEM-X SAR database, and a 5 m resolution airborne LIDAR DEM. From the analysis of the available information on the volcanic cones in the age range 1.6 to 222 ka, we conclude that the age-relevant morphometric parameters calculated from the TanDEM-X satellite DEM render alike values and perform equally well as the LIDAR airborne DEM for the morpho-chronological characterization of scoria cones, expanding the role of digital satellite elevation data to the study of detailed features of distributed volcanism at a global level.

QSAR Use in REACH Analyses of Alternatives to Predict Human Health and Environmental Toxicity of Alternative Chemical Substances.

In 2006, the European Union (EU) enacted the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) to address growing concerns of hazardous chemicals in the EU market. Under REACH, companies seeking authorization to use priority substances identified as substances of very high concern (SVHCs) and included in the authorization list must apply and submit health and environmental effects data in analyses of alternatives (AoAs) to the European Chemicals Agency (ECHA). To assess safer alternatives, especially in AoA hazard assessment cases where vital information could be missing or insufficient, quantitative structure-activity relationship (QSAR) nontesting methods have gained increasing acceptance and importance. This article assesses AoA applicants' use of QSAR sources and documentation while looking for meaningful trends. In this assessment, usage and frequency of QSAR sources were evaluated in 189 analyses of alternatives for 15 physicochemical properties and 19 human health and environmental endpoints to determine the scope of purpose of QSAR use in AoAs. We found that only 24 out of 189 applications cited QSAR sources to rank or evaluate the safety of their alternative substances relative to the REACH Annex XIV chemical. For human health and environmental hazard endpoints, applicants cited the Danish (Q)SAR Database (n = 63) and unidentified QSARs (n = 36) most frequently. While QSARs were not used to eliminate an alternative, 7.9% and 1.4% per maximum opportunity (MOP) of hazard endpoint and physicochemical QSAR predictions reported background information on alternatives using weight of evidence (WoE). In addition, 3.0% per MOP of hazard endpoint QSAR predictions supported the safety of the alternative while 0.7% per MOP of physicochemical QSAR predictions gave mixed support for their alternative's safety. Documentation regarding QSARs was absent in all 24 AoAs that used QSARs. Limited QSAR use and missing documentation may be the result of several factors, including inconsistent regulatory guidance. Integr Environ Assess Manag 2020;16:745-760. © 2020 SETAC.

Drug design: 4-thiazolidinones applications. Part 2. Pharmacological profiles

Following of the chemical diversity of 4-thiazolidinones the in-house library of new heterocycles have been designed and synthesized (more 7000 compounds). Anticancer, antitrypanosomal, antituberculosis and antiviral activity screening led to SAR database formation; lead-compounds identification; design of focused sub-libraries; formation and validation of hypotheses for structure optimization: i) complications of C5 fragment and/or functionalization of N3 position; ii) creation of the hybrid molecules; iii) fixation of 5-ene-4-thiazolidinones in fused heterocycles via annulation (thiopyrano[2,3-d]thiazoles were found as a cyclic isosteric mimetics of 5-ene-4-thiazolidinones); iv) the leukemia panel was detected to be the most sensitive among all cancer cell lines. Following the in silico and pharmacological data for the investigation of molecular mechanism of anticancer effect the argument in favor of the apoptotic related and mild prooxidant actions for active compounds have been found.

QSAR modeling of different minimum potency levels for in vitro human CAR activation and inhibition and screening of 80,086 REACH and 54,971 U.S. substances

The human Constitutive Androstane Receptor (hCAR) is together with the human Pregnane X Receptor (hPXR) a key regulator of the metabolism and excretion of xenobiotics and endogenous compounds. Inhibition or activation of hCAR by xenobiotics can alter protein expression, leading to decreased or enhanced turnover of both xenobiotics and endogenous substances. Impacts from these alternations can potentially disturb physiological homeostasis and cause adverse effects. Tens-of-thousands of manufactured substances of which humans are potentially exposed are not tested for their potential to inhibit or activate hCAR. In this study, the U.S. Toxicology in the 21st Century (Tox21) high-throughput in vitro assay results for hCAR inhibition and activation were used in a comprehensive in-house process to derive training sets for different potency cut-offs, and to develop suites of quantitative structure–activity relationship (QSAR) models with binary outputs. Final, expanded models, which include substances from the external validation sets, were developed for select minimum potency levels. Rigorous cross- and external validations demonstrated good predictive accuracies for the models. The final models were applied to screen 80,086 EU and 54,971 U.S. substances, and the models predicted around 60% of the substances within their respective applicability domains (AD). Finally, statistical comparisons of hCAR predictions and QSAR predictions for a number of other endpoints related to e.g. Pregnane X, aryl hydrocarbon, estrogen and androgen receptors, as well as genotoxicity, cancer, sensitization and teratogenicity from the Danish (Q)SAR database were made to explore possible implications related to hCAR antagonists and agonists. The final models from this study will be made available in the free Danish (Q)SAR Models website. Predictions made with models from this study for 650,000 substances will be made available in the free Danish (Q)SAR Database. Predictions from the models developed in this study can for example contribute to priority setting, read-across cases and weight-of-evidence assessments of chemicals.

QSAR modelling of a large imbalanced aryl hydrocarbon activation dataset by rational and random sampling and screening of 80,086 REACH pre-registered and/or registered substances.

The Aryl hydrocarbon receptor (AhR) plays important roles in many normal and pathological physiological processes, including endocrine homeostasis, foetal development, cell cycle regulation, cellular oxidation/antioxidation, immune regulation, metabolism of endogenous and exogenous substances, and carcinogenesis. An experimental data set for human in vitro AhR activation comprising 324,858 substances, of which 1,982 were confirmed actives, was used to test an in-house-developed approach to rationally select Quantitative Structure-Activity Relationship (QSAR) training set substances from an unbalanced data set. In the first iteration, active and inactive substances were selected by random to make QSAR models. Then, more inactive substances were added to the training set in two further iterations based on incorrect or out-of-domain predictions to produce larger models. The resulting ‘rational’ model, comprising 832 actives and four times as many inactives, i.e. 3,328, was compared to a model with a training set of same size and proportion of inactives chosen entirely by random. Both models underwent robust cross-validation and external validation showing good statistical performance, with the rational model having external validation sensitivity of 85.1% and specificity of 97.1%, compared to the random model with sensitivity 89.1% and specificity 91.3%. Furthermore, we integrated the training sets for both models with the 93 external validation test set actives and 372 randomly selected inactives to make two final models. They also underwent external validations for specificity and cross-validations, which confirmed that good predictivity was maintained. All developed models were applied to predict 80,086 EU REACH substances. The rational and random final models had 63.1% and 56.9% coverage of the REACH set, respectively, and predicted 1,256 and 3,214 substances as actives. The final models as well as predictions for AhR activation for 650,000 substances will be published in the Danish (Q)SAR Database and can, for example, be used for priority setting, in read-across predictions and in weight-of-evidence assessments of chemicals.

Construction of an integrated database for hERG blocking small molecules.

The inhibition of the hERG potassium channel is closely related to the prolonged QT interval, and thus assessing this risk could greatly facilitate the development of therapeutic compounds and the withdrawal of hazardous marketed drugs. The recent increase in SAR information about hERG inhibitors in public databases has led to many successful applications of machine learning techniques to predict hERG inhibition. However, most of these reports constructed their prediction models based on only one SAR database because the differences in the data format and ontology hindered the integration of the databases. In this study, we curated the hERG-related data in ChEMBL, PubChem, GOSTAR, and hERGCentral, and integrated them into the largest database about hERG inhibition by small molecules. Assessment of structural diversity using Murcko frameworks revealed that the integrated database contains more than twice as many chemical scaffolds for hERG inhibitors than any of the individual databases, and covers 18.2% of the Murcko framework-based chemical space occupied by the compounds in ChEMBL. The database provides the most comprehensive information about hERG inhibitors and will be useful to design safer compounds for drug discovery. The database is freely available at http://drugdesign.riken.jp/hERGdb/.

Protocols for the Design of Kinase-focused Compound Libraries.

Protocols for the design of kinase-focused compound libraries are presented. Kinase-focused compound libraries can be differentiated based on the design goal. Depending on whether the library should be a discovery library specific for one particular kinase, a general discovery library for multiple distinct kinase projects, or even phenotypic screening, there exists today a variety of in silico methods to design candidate compound libraries. We address the following scenarios: 1) Datamining of SAR databases and kinase focused vendor catalogues; 2) Predictions and virtual screening; 3) Structure-based design of combinatorial kinase inhibitors; 4) Design of covalent kinase inhibitors; 5) Design of macrocyclic kinase inhibitors; and 6) Design of allosteric kinase inhibitors and activators.

The new Danish (Q)SAR database: A freely available tool with predictions for >600,000 substances

The new Danish (Q)SAR database: A freely available tool with predictions for >600,000 substances

Mobi-Kids Study: 휴대전화의 전자파 노출량 평가 -II. 머리 SAR 및 누적노출 평가 방법

본 논문은 Mobi-Kids 연구의 노출량 평가를 위해 휴대전화 대표 모델에 대해 연구 프로토콜에 따른 SAR 계산방법을 분석하고, 역학조사 대상자가 사용한 휴대전화의 무선주파수 누적 노출량을 평가하는 방법을 제안한다. 휴대전화 대표 모델의 출력을 동일하게 가정하고, 서로 다른 연령의 4개 머리 모델에서의 SAR 분포를 계산하여 데이터베이스를 구축한다. 역학조사 대상자가 사용한 특정 휴대전화 모델의 머리 SAR은 SAR 적합성 시험결과를 활용하여 보정 인자를 적용함으로써 구한다. 그리고 휴대전화 특성과 함께 사용 시간, 좌 우측 비율 같은 대상자의 휴대전화 사용 패턴에 대한 인자를 고려하여 누적 에너지를 산출하게 된다. SAR calculation method following the Mobi-Kids study protocol is analyzed and evaluation method of cumulative RF dose from mobile phones which have been used by a subject of case and control groups is proposed. An SAR database is built by calculating SAR distributions in 4 head models at different ages for representative phone models with the same conducted power. To obtain SAR distribution in a subject's head for a specific commercial phone which had/have been used by him/her, an SAR correction factor using SAR compliance test results is determined. Cumulative dose is calculated by considering mobile phone characteristics and use pattern such as call time and laterality(right and left).

The Danish (Q)SAR Database Update Project

The Danish (Q)SAR Database Update Project

Comparative PBT screening using (Q)SAR tools within REACH legislation

Small to medium sized enterprises (SMEs) in the EU are facing challenges due to the introduction of new legislation designed to protect consumers and the environment, REACH (Registration, Evaluation, Authorisation and Restriction of CHemicals). There can be high costs associated with implementing REACH because data on mammalian toxicity, environmental toxicity and environmental fate properties is required and if this data is obtained experimentally the cost is significant. These costs can be reduced if reliable quantitative structure–activity relationships ((Q)SAR) models are instead used to obtain the required information. In this paper we investigate how easily freely available (Q)SAR models can be applied for persistent, bioaccumulative and toxic (PBT) screening of 17 chemicals of interest to SMEs. In this study the PBT predictions obtained from the more user-friendly PBT Profiler and the Danish(Q)SAR database for the chemicals were compared with the results taken directly from the EPI Suite software. It was found that these widely used (Q)SAR databases might have some errors and examples are provided. It was concluded that extra care must be taken when considering the use of these databases for PBT screening. In addition, to increase the likelihood of a correct prediction, data estimates from various (Q)SAR models relevant to the PBT endpoints must be compared.

An optimized architecture for classification combining data fusion and data-mining

This paper presents a new architecture to integrate a library of feature extraction, Data-mining, and fusion techniques to automatically and optimally configure a classification solution for a given labeled set of training patterns. The most expensive and scarce resource in any detection problem (feature selection/classification) tends to be the acquiring of labeled training patterns from which to design the system. The objective of this paper is to present a new Data-mining architecture that will include conventional Data-mining algorithms, feature selection methods and algorithmic fusion techniques to best exploit the set of labeled training patterns so as to improve the design of the overall classification system. The paper describes how feature selection and Data-mining algorithms are combined through a Genetic Algorithm, using single source data, and how multi-source data are combined through several best-suited fusion techniques by employing a Genetic Algorithm for optimal fusion. A simplified version of the overall system is tested on the detection of volcanoes in the Magellan SAR database of Venus.