SAR and QSAR in Environmental Research This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines
SAR QSAR Environ Res. 2023 Dec 19:1-9. doi: 10.1080/1062936X.2023.2289050. Online ahead of print.ABSTRACTIn silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell li...
Source: SAR and QSAR in Environmental Research - December 19, 2023 Category: Environmental Health Authors: A A Lagunin A S Sezganova E S Muraviova A V Rudik D A Filimonov Source Type: research

Prioritizing pharmaceutically active compounds (PhACs) based on occurrence-persistency-mobility-toxicity (OPMT) criteria: an application to the Brazilian scenario
SAR QSAR Environ Res. 2023 Oct-Dec;34(12):1023-1039. doi: 10.1080/1062936X.2023.2287516. Epub 2023 Dec 4.ABSTRACTA study of Quantitative Structure Activity Relationship (QSAR) was performed to assess the possible adverse effects of 25 pharmaceuticals commonly found in the Brazilian water compartments and to establish a ranking of environmental concern. The occurrence (O), the persistence (P), the mobility (M), and the toxicity (T) of these compounds in the Brazilian drinking water reservoirs were evaluated. Moreover, to verify the predicted OPMT dataset outcomes, a quality index (QI) was also developed and applied. The mai...
Source: SAR and QSAR in Environmental Research - December 4, 2023 Category: Environmental Health Authors: V Roveri L Lopes Guimar ães A T Correia Source Type: research

Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project
SAR QSAR Environ Res. 2023 Oct-Dec;34(12):983-1001. doi: 10.1080/1062936X.2023.2284902. Epub 2023 Dec 4.ABSTRACTQuantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Se...
Source: SAR and QSAR in Environmental Research - December 4, 2023 Category: Environmental Health Authors: A Furuhama A Kitazawa J Yao C E Matos Dos Santos J Rathman C Yang J V Ribeiro K Cross G Myatt G Raitano E Benfenati N Jeliazkova R Saiakhov S Chakravarti R S Foster C Bossa C Laura Battistelli R Benigni T Sawada H Wasada T Hashimoto M Wu R Barzilay P R Da Source Type: research

Prioritizing pharmaceutically active compounds (PhACs) based on occurrence-persistency-mobility-toxicity (OPMT) criteria: an application to the Brazilian scenario
SAR QSAR Environ Res. 2023 Oct-Dec;34(12):1023-1039. doi: 10.1080/1062936X.2023.2287516. Epub 2023 Dec 4.ABSTRACTA study of Quantitative Structure Activity Relationship (QSAR) was performed to assess the possible adverse effects of 25 pharmaceuticals commonly found in the Brazilian water compartments and to establish a ranking of environmental concern. The occurrence (O), the persistence (P), the mobility (M), and the toxicity (T) of these compounds in the Brazilian drinking water reservoirs were evaluated. Moreover, to verify the predicted OPMT dataset outcomes, a quality index (QI) was also developed and applied. The mai...
Source: SAR and QSAR in Environmental Research - December 4, 2023 Category: Environmental Health Authors: V Roveri L Lopes Guimar ães A T Correia Source Type: research

Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project
SAR QSAR Environ Res. 2023 Oct-Dec;34(12):983-1001. doi: 10.1080/1062936X.2023.2284902. Epub 2023 Dec 4.ABSTRACTQuantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Se...
Source: SAR and QSAR in Environmental Research - December 4, 2023 Category: Environmental Health Authors: A Furuhama A Kitazawa J Yao C E Matos Dos Santos J Rathman C Yang J V Ribeiro K Cross G Myatt G Raitano E Benfenati N Jeliazkova R Saiakhov S Chakravarti R S Foster C Bossa C Laura Battistelli R Benigni T Sawada H Wasada T Hashimoto M Wu R Barzilay P R Da Source Type: research

Prioritizing pharmaceutically active compounds (PhACs) based on occurrence-persistency-mobility-toxicity (OPMT) criteria: an application to the Brazilian scenario
SAR QSAR Environ Res. 2023 Oct-Dec;34(12):1023-1039. doi: 10.1080/1062936X.2023.2287516. Epub 2023 Dec 4.ABSTRACTA study of Quantitative Structure Activity Relationship (QSAR) was performed to assess the possible adverse effects of 25 pharmaceuticals commonly found in the Brazilian water compartments and to establish a ranking of environmental concern. The occurrence (O), the persistence (P), the mobility (M), and the toxicity (T) of these compounds in the Brazilian drinking water reservoirs were evaluated. Moreover, to verify the predicted OPMT dataset outcomes, a quality index (QI) was also developed and applied. The mai...
Source: SAR and QSAR in Environmental Research - December 4, 2023 Category: Environmental Health Authors: V Roveri L Lopes Guimar ães A T Correia Source Type: research

Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project
SAR QSAR Environ Res. 2023 Oct-Dec;34(12):983-1001. doi: 10.1080/1062936X.2023.2284902. Epub 2023 Dec 4.ABSTRACTQuantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Se...
Source: SAR and QSAR in Environmental Research - December 4, 2023 Category: Environmental Health Authors: A Furuhama A Kitazawa J Yao C E Matos Dos Santos J Rathman C Yang J V Ribeiro K Cross G Myatt G Raitano E Benfenati N Jeliazkova R Saiakhov S Chakravarti R S Foster C Bossa C Laura Battistelli R Benigni T Sawada H Wasada T Hashimoto M Wu R Barzilay P R Da Source Type: research