Computational Toxicology最新文献

{"title":"Estimating the reliability of simulated metabolism using documented data and theoretical knowledge. QSAR application","authors":"Irina A. Dermen ,&nbsp;Hristiana I. Ivanova ,&nbsp;Elena K. Kaloyanova ,&nbsp;Nadezhda H. Dimitrova ,&nbsp;Antonia D. Kesova ,&nbsp;Todor S. Pavlov ,&nbsp;Terry W. Schultz ,&nbsp;Ovanes G. Mekenyan","doi":"10.1016/j.comtox.2022.100218","DOIUrl":"10.1016/j.comtox.2022.100218","url":null,"abstract":"<div><p>Establishing the reliability of simulated metabolism continues to be pivotal in accepting predictions of both fate and toxicological endpoints, especially when metabolic activation of a parent chemical is deemed crucial. A quintessential way of estimating the reliability of simulated metabolism is by comparing a simulated metabolic map with an appropriate documented metabolic map. The approach is constructed on two core parts - experimental and theoretical corroboration. Specifically, the three-layer algorithm is used to support experimentally the adequacy of the simulated maps. The first layer defines similarity boundaries between the parent chemical or metabolite starting the sequence, the root of the simulated series of biotransformations, and the corresponding initial structure of the analogue from the database with documented maps. Different criteria (e.g., the commonality between organic functional groups) are used for this rationale. The second layer delineates the metabolic transformation sequences applied to the target chemical or the initial metabolite of the transformation sequence. The last layer establishes the similarity between the final transformation product in the simulated and documented sequences. To support the adequacy of the simulated molecular transformations, a library of theoretical knowledge is used, providing mechanistic justification on applied transformations. The results of applications of the above procedure are shown using two examples.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100218"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45295400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an in silico consensus model for the prediction of the phospholipigenic potential of small molecules","authors":"Sebastian Schieferdecker,&nbsp;Andreas Eberlein,&nbsp;Esther Vock,&nbsp;Mario Beilmann","doi":"10.1016/j.comtox.2022.100226","DOIUrl":"10.1016/j.comtox.2022.100226","url":null,"abstract":"<div><p>Phospholipidosis (PL) describes the accumulation of phospholipids in lysosomes of cells of various tissues after prolonged exposure with drug like compounds. These cellular findings can result in a delay of drug development, cause increased costs in affected projects and potentially may halt a drug development program. The early detection of compounds which potentially cause phospholipidosis therefore is desirable for risk mitigation. Here we describe an <em>in silico</em> consensus model for the detection of phospholipigenic potential of small molecules. The model was trained on in house <em>in vitro</em> data yielding an accuracy of 94%. By employing model agnostic explainability methods, we could show that the model learns reasonable molecular properties. The consensus model showed good performance on underrepresented PL-active compounds in clusters of similar molecules of the test dataset and on external <em>in vitro</em> and <em>in vivo</em> validation data of highly structural dissimilarity to the training data. Using the external <em>in vitro</em> data, an applicability domain of the model was deduced.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100226"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42331934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physiologically based kinetic model for assessing intermittent chronic internal exposure to chemicals: Application for disinfection by-products in swimming pool water","authors":"Zijian Li ,&nbsp;Jie Xiong ,&nbsp;Yuan Guo","doi":"10.1016/j.comtox.2022.100227","DOIUrl":"10.1016/j.comtox.2022.100227","url":null,"abstract":"<div><p>Chronic exposure to disinfection by-products (DBPs) via swimming in chlorinated pools can damage the genetic material and even cause cancers in humans. To assess the intermittent chronic internal exposure to DBPs in swimming pool water, a physiologically based kinetic (PBK) modeling framework was introduced to simulate daily average internal exposure doses of DBPs that can be linked to the corresponding daily average external doses. Biotransfer factor (BTF), i.e., the steady-state concentration ratio between human bodies and swimming pool water, was applied to measure the bioaccumulation potential of chemicals in organs and tissues. The results simulated for the four selected trihalomethanes (THMs) (i.e., chloroform, bromoform, dibromochloromethane, and bromodichloromethane) showed that lungs had the highest simulated BTF among human organs and tissues, with the inhalation route showing the maximum contribution to the overall external dose. In addition, route-specific analysis indicated that chronic internal exposure doses of THMs via oral and dermal routes were negligible compared to the inhalation route. Theoretical simulation using the dissipation coefficient of THMs in the air can help optimize the design and operation of swimming pools to substantially reduce chronic internal exposure doses of THMs. The simulated results for time-dependent chloroform concentration in human blood agreed with the reported data and can be further improved once more information about the THM concentrations in breathing zones of swimmers is obtained, indicating that the proposed model can be used as a practical tool to assess intermittent chronic internal exposure of THMs in swimming pool water. In future studies, human exposure to THMs via other pathways (e.g., drinking water, showering, and bathing) can be incorporated into the proposed model to comprehensively evaluate the internal exposure doses of THMs in humans.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100227"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42158969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences between in vitro and in vivo genotoxicity due to metabolism: The role of kinetics","authors":"P.I. Petkov ,&nbsp;H. Ivanova ,&nbsp;M. Honma ,&nbsp;T. Yamada ,&nbsp;T. Morita ,&nbsp;A. Furuhama ,&nbsp;S. Kotov ,&nbsp;E. Kaloyanova ,&nbsp;G. Dimitrova ,&nbsp;O. Mekenyan","doi":"10.1016/j.comtox.2022.100222","DOIUrl":"10.1016/j.comtox.2022.100222","url":null,"abstract":"<div><p>Traditional QSAR models predict mutagenicity solely based on structural alerts for the interaction of parent chemicals or their metabolites with target macromolecules. In the present work, it is demonstrated that the presence of an alert is necessary to identify damage but it is not always sufficient to assess mutagenic potential. This is addressed by accounting for the kinetics of simulating metabolism and formation of adducts with macromolecules. The mutagenic potential of chemicals is related to the degree to which selected macromolecules are altered. This extent is estimated by the amount of formed DNA/protein adducts. Here the effect of modelling kinetic factors is investigated for chemicals having documented <em>in vitro</em> negative and <em>in vivo</em> positive data in mutagenicity and clastogenicity tests of similar capacity - <em>in vitro</em> Ames vs <em>in vivo</em> TGR and <em>in vitro</em> CA vs <em>in vivo</em> MN tests. Two factors justify the conflict in mutagenicity data: the differences in enzyme expression in the <em>in vitro</em> vs <em>in vivo</em> metabolism and the difference in exposure time for <em>in vitro</em> and <em>in vivo</em> tests. Addressing these factors required simulating the formation of DNA/protein adducts and introducing empirically-defined thresholds for the amounts of the adducts leading to mutagenic potential.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100222"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43568343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of uncertainty and credibility of predictions by the OECD QSAR Toolbox automated read-across workflow for predicting acute oral toxicity","authors":"Terry W. Schultz ,&nbsp;Atanas Chapkanov ,&nbsp;Stela Kutsarova ,&nbsp;Ovanes G. Mekenyan","doi":"10.1016/j.comtox.2022.100219","DOIUrl":"10.1016/j.comtox.2022.100219","url":null,"abstract":"<div><p>The platform of OECD Toolbox version 4.5 was used for building an automated decision tree for filling data gaps for rat acute oral toxicity (AOT) by read-across (RA). Our previous publications have described the workflow of the AOT tree and conducted verification and validation studies on it. The overall uncertainty in the AOT workflow is low as the similarity in mechanistic probability, metabolism and 2D structure are maximized in the RA analogue selection process. The endpoint, rat oral LD50, is well-defined and has universal regulatory acceptance. Since OECD test guidelines are followed in generating the database, the data are widely recognized to be of the highest quality. The credibility of the workflow is high as it meets the critical factors of being based on confirmed assumptions, having demonstrated concordance and consistency, permitting the ability to explain AOT-related mechanisms and modes of action, and being simple in design. Additionally, the Z-score and probability distribution methods of assessing the uncertainty of a particular RA are discussed. Two examples of numerical and classification uncertainty are presented. These cases represent the extremes observed in a series of target chemical-based predictions that the authors observed when testing the workflow. The reliability and relevance associated with the workflow are high. However, the completeness and weights-of-evidence varied markedly among possible RA scenarios and particular target substances.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100219"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49576598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-linearity in cancer dose-response: The role of exposure duration","authors":"Andrey A. Korchevskiy ,&nbsp;Arseniy Korchevskiy","doi":"10.1016/j.comtox.2022.100217","DOIUrl":"10.1016/j.comtox.2022.100217","url":null,"abstract":"<div><h3>Context</h3><p>An apparent deviation from nonlinearity in cancer dose-response was reported for various carcinogens. In particular, some studies hypothesized that in mesothelioma, the exposure-response relationship can be modelled as a power function with exponent from 0.6 to 1. However, various factors can affect the shape of the dose-response, producing the apparent supralinear trend.</p></div><div><h3>Objective</h3><p>To develop a mathematical model that would demonstrate a relationship of mesothelioma lifetime risk and exposure duration, with various assumptions about a hazard rate function.</p></div><div><h3>Methods</h3><p>Two different hazard rate functions – the Peto model and the two-stage clonal expansion (TSCE) model – were considered. The analytical formulas for lifetime risk were developed, with and without a lifetable correction. Standard calculus methods were applied to test the shape of the lifetime risk curve.</p></div><div><h3>Results</h3><p>For both Peto and TSCE models, it was shown that mesothelioma lifetime risk changes supralinearly with duration; the exponent of the power function was ranging from 0.68 to 0.89. However, the dose-response curve by cumulative exposure is close to linearity and is linear if the exposure duration would be constant. The model has been tested for chrysotile asbestos cohorts, with a good agreement demonstrated with published mesothelioma excess mortality (R=0.88, p&lt;0.0041).</p></div><div><h3>Conclusion</h3><p>For mesothelioma, the observed deviation from linearity in the dose-response relationship can be potentially explained by the impact of a change in the duration of exposure. In a meta-analysis, this deviation can be eliminated by standardizing the mortality data for various cohorts by duration of exposure.</p></div><div><h3>Short Abstract</h3><p>An apparent deviation from nonlinearity in cancer dose-response was reported for various carcinogens. We applied two different hazard rate equations – the Peto model and the two-stage clonal expansion (TSCE) model – to pleural mesothelioma mortality. The analytical formulas for lifetime risk were developed. For both the Peto and TSCE models, it was shown that mesothelioma lifetime risk changes supralinearly with duration. However, the dose-response curve for cumulative exposure is close to linearity.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100217"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44861217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying in silico approaches to nanotoxicology: Current status and future potential","authors":"Natalia Lidmar von Ranke ,&nbsp;Reinaldo Barros Geraldo ,&nbsp;André Lima dos Santos ,&nbsp;Victor G.O. Evangelho ,&nbsp;Flaminia Flammini ,&nbsp;Lucio Mendes Cabral ,&nbsp;Helena Carla Castro ,&nbsp;Carlos Rangel Rodrigues","doi":"10.1016/j.comtox.2022.100225","DOIUrl":"10.1016/j.comtox.2022.100225","url":null,"abstract":"<div><p>Nanomaterial development is one of the most significant technological advances of the 21st century, with considerable impact in several fields. However, nanomaterials can pose risks to human health and the environment. Therefore, it is imperative to perform toxicological tests; nonetheless, identification and analysis of all preparations is laborious. In this regard, <em>in silico</em> approaches facilitate nanotoxicity assessment at low cost and without involving animal testing. In this paper we review the use of computational approaches for nanotoxicology prediction. First, we present computational nanotoxicology in a regulatory context. Next, we discuss the primary computational methods used in toxicology, such as (quantitative) structure–activity relationship models, physiologically based pharmacokinetic models, and molecular modeling, and address the singularities of each method for nanomaterial analyses. Lastly, we describe several integrative approaches for computational nanotoxicology. Various database analyses combined with complementary computational approaches can lead to creative solutions for predicting toxicological effects during the design of new nanomaterials. Therefore, data-integration methods promote understanding of complex nanotoxicological events and can be used to develop successful precision models.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100225"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49518432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches","authors":"Kevin M. Crofton ,&nbsp;Arianna Bassan ,&nbsp;Mamta Behl ,&nbsp;Yaroslav G. Chushak ,&nbsp;Ellen Fritsche ,&nbsp;Jeffery M. Gearhart ,&nbsp;Mary Sue Marty ,&nbsp;Moiz Mumtaz ,&nbsp;Manuela Pavan ,&nbsp;Patricia Ruiz ,&nbsp;Magdalini Sachana ,&nbsp;Rajamani Selvam ,&nbsp;Timothy J. Shafer ,&nbsp;Lidiya Stavitskaya ,&nbsp;David T. Szabo ,&nbsp;Steven T. Szabo ,&nbsp;Raymond R. Tice ,&nbsp;Dan Wilson ,&nbsp;David Woolley ,&nbsp;Glenn J. Myatt","doi":"10.1016/j.comtox.2022.100223","DOIUrl":"10.1016/j.comtox.2022.100223","url":null,"abstract":"<div><p>Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including <em>in silico</em> approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. <em>In silico</em> approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of <em>in silico</em> methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100223"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9748808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physiologically-based modeling of cholate disposition in beagle dog with and without treatment of the liver transporter inhibitor simeprevir","authors":"Shu-Wen Teng ,&nbsp;Michael Hafey ,&nbsp;Jeanine Ballard ,&nbsp;Xinjie Lin ,&nbsp;Changhong Yun ,&nbsp;Vijay More ,&nbsp;Robert Houle ,&nbsp;Ravi Katwaru ,&nbsp;Ann Thomas ,&nbsp;Grace Chan ,&nbsp;Kim Michel ,&nbsp;Yutai Li ,&nbsp;Kara Pearson ,&nbsp;Christopher Gibson","doi":"10.1016/j.comtox.2022.100224","DOIUrl":"10.1016/j.comtox.2022.100224","url":null,"abstract":"<div><p>BSEP inhibition is one risk factor for Drug-Induced Liver Injury (DILI). While in vitro screening of BSEP inhibition may prevent compounds with BSEP liability from progressing into the clinic, these in vitro data alone can result in false-positives and as such a specific in vivo biomarker would further enhance our BSEP inhibition de-risking strategy. Measurement of endogenous bile acids as biomarkers of BSEP inhibition in vivo is complicated by several factors, including drugs that inhibit BSEP can also inhibit other bile acid transporters such as NTCP. Here, we developed a novel translational framework, including an in vivo biomarker with a corresponding mechanistic model, and attempted to decouple the effect of liver sinusoidal uptake inhibition from efflux inhibition on bile acid disposition in the beagle dog. Specifically, we hypothesized that the change of a stable isotope-labeled (SIL) bile acid tracer’s exposure would yield a toxicodynamic signal that can provide insight into BSEP inhibition and ensuing bile salt accumulation. For this purpose we dosed the stable isotope-labeled cholic acid (¹³C-CA) and taurocholic acid (D4-TCA) as biomarker tracers in dogs, with and without the liver transporter inhibitor simeprevir, and determined the plasma and bile exposure of ¹³C-CA, ¹³C-TCA, D4-CA and D4-TCA in vivo. Key bile acid clearance and transporter inhibition parameters were determined in vitro. We developed a novel Physiologically Based Pharmacokinetic model (PBPK) to integrate the mechanistic physiological understanding, literature knowledge, and in vitro laboratory data to model bile acid disposition. Using modeling and simulation, we provided an increased mechanistic understanding of how to use plasma bile acid tracer data to inform on potential liver transporters inhibition and limitations to in vivo translation. The novel translational framework can enhance the future BSEP inhibition de-risking strategy, particularly if the experimental confounders to studying kinetics in dog hepatocytes in vitro models are solved.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100224"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468111322000123/pdfft?md5=56a90a95a905ed980c1c5a2a975df2c8&pid=1-s2.0-S2468111322000123-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44313768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-silico profiling of SLC6A19, for identification of deleterious ns-SNPs to enhance the Hartnup disease diagnosis","authors":"Wahidah H. Al-Qahtani ,&nbsp;Dinakarkumar Yuvaraj ,&nbsp;Anjaneyulu Sai Ramesh ,&nbsp;Haryni Jayaradhika Raghuraman Rengarajan ,&nbsp;Muthusamy Karnan ,&nbsp;Jothiramalingam Rajabathar ,&nbsp;Arokiyaraj Charumathi ,&nbsp;Sayali Harishchandra Pangam ,&nbsp;Priyanka Kameswari Devarakonda ,&nbsp;Gouthami Nadiminti ,&nbsp;Prikshit Sharma","doi":"10.1016/j.comtox.2022.100215","DOIUrl":"10.1016/j.comtox.2022.100215","url":null,"abstract":"<div><p>The mutation in the solute carrier 6 (SLC6A19) gene causes the Hartnup disorder, affecting the absorption of non-polar amino acids. Recent DNA sequencing advances have increased the identification of single nucleotide polymorphisms (SNPs) in<!--> <!-->the SLC6A19 gene, but no further information regarding their deleterious probability is available. Hence, this study aims to comprehensively analyze and identify the potentially deleterious non-synonymous-SNPs of the SLC6A19 gene with a computational approach using openly accessible online software tools including SIFT, PolyPhen2, SAVES 5.0, SPIDER, <em>etc</em>. and also to determine effective lead compound for its treatment by docking. The SLC6A19 gene translates to B⁰AT1 tetramer protein, amongst chain A was taken into consideration. The analysis revealed mutation G490S (chain A) of the said protein as the candidate ns-SNP among the screened 539 missense mutations, retrieved from the National Centre for Biotechnology Information (NCBI). Moreover, the binding energy of the candidate ns-SNP had a higher affinity for benztropine over conventional drugs such as nicotinamide and niacin. Yet, clinical validation is required to support the above findings.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100215"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42470003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}